INFORMATIONAL ASYMMETRIES, FINANCIAL STRUCTURE, AND FINANCIAL INTERMEDIATION.
金融发展与经济增长：观点与目的【外文翻译】
外文翻译Financial Development and Economic Growth: Views and AgendaMaterial Source: Journal of Economic Literature Author: ROSS LEVINE The Functions of the Financial SystemA.Facilitating Risk AmeliorationIn the presence of specific information and transaction costs, financial markets and institutions may arise to ease the trading, hedging, and pooling of risk. This subsection considers two types of risk: liquidity and idiosyncratic risk. Liquidity is the ease and speed with which agents can convert assets into purchasing power at agreed prices. Thus, real estate is typically less liquid than equities, and equities in the United States are typically more liquid than those traded on the Nigerian Stock Exchange. Liquidity risk arises due to the uncertainties associated with converting assets into a medium of exchange. Informational asymmetries and transaction costs may inhibit liquidity and intensify liquidity risk. These frictions create incentives for the emergence of financial markets and institutions that augment liquidity. Liquid capital markets, therefore, are markets where it is relatively inexpensive to trade financial instruments and where there is little uncertainty about the timing and settlement of those trades.Theory, however, suggests that enhanced liquidity has an ambiguous affect on saving rates and economic growth.'' In most models, greater liquidity (a) increases investment returns and (b) lowers uncertainty. Higher returns ambiguously affect saving rates due to well-known income and substitution effects. Further, lower uncertainty ambiguously affects savings rates (David Levhari and T. N. Srinivasan 1969). Thus, saving rates may rise or fall as liquidity rises. Indeed, in a model with physical capital externalities, saving rates could fall enough, so that growth actually decelerates with greater liquidity (Tullio Jappelli and Marco Pagano 1994).Besides reducing liquidity risk, financial systems may also mitigate the risks associated with individual projects, firms, industries, regions, countries, etc. Banks, mutual funds, and securities markets all provide vehicles for trading, pooling, and diversifying risk. The financial system's ability to provide risk diversification services can affect long-run economic growth by altering resource allocation and the saving rates. The basic intuition is straightforward. While savers generally do notlike risk, high-return projects tend to be riskier than low-return projects. Thus, financial markets that ease risk diversification tend to induce a portfolio shift toward projects with higher expected returns (Gilles Saint-Paul 1992; Michael Deverettx and Gregor Smith 1994; and Maurice Obstfeld 1994). Greater risk sharing and more efficient capital allocation, however, have theoretically ambiguous effects on saving rates as noted above. The savings rate could fall enough so that, when coupled with an externality-based or linear growth model, overall economic growth falls. With externalities, growth could fall sufficiently so that overall welfare falls with greater risk diversification.Besides the link between risk diversification and capital accumulation, risk diversification can also affect technological change. Agents are continuously trying to make technological advances to gain a profitable market niche. Besides yielding profits to the innovator, successful innovation accelerates technological change. Engaging in innovation is risky, however. The ability to hold a diversified portfolio of innovative projects reduces risk and promotes Investment in growth-enhancing innovative activities (with sufficiently risk averse agents). Thus, financial systems that ease risk diversification can accelerate technological change and economic growth (Robert King and Levine 1993c).B. Facilitating ExchangeBesides easing savings mobilization and thereby expanding the of set production technologies available to an economy, financial arrangements that lower transaction costs can promote specialization, technological innovation, and growth. The links between facilitating transactions, specialization, innovation, and economic growth were core elements of Adam Smith's (1776) Wealth of Nations. Smith (1776, p, 7) argued that division of labor-specialization-is the principal factor underlying productivity improvements. With greater specialization, workers are more likely to invent better machines or production processes.The critical issue for our purposes is that the financial system can promote specialization. Adam Smith argued that lower transaction costs would permit greater specialization because specialization requires more transactions than an autarkic environment. Smith phrased his argument about the lowering of transaction costs and technological innovation in terms of the advantages of money over barter (pp. 26-27). Information costs, however, may also motivate the emergence of money. Because it is costly to evaluate the attributes of goods, barter exchange is very costly. Thus, an easily recognizable medium of exchange may arise to facilitate exchange(King and Charles Plosser 1986; and Williamson and Randall Wright 1994).The drop in transaction and information costs is not necessarily a one-time fall when economies move to money, however. For example, in the 1800s, “it was primarily the development of institutions that facilitated the exchange of technology in the market that enabled creative individuals to specialize in and become more productive at invention"(Lamoreaux and Sokoloff 1996, p. 17).Thus, transaction and information costs may continue to fall through a variety of mechanisms, so that financial and institutional development continually boost specialization and innovation via the same channels illuminated over 200 years ago by Adam Smith.Financial Structure and Economic GrowthThere exists considerable debate, with sparse evidence and insufficient theory, about the relationship between financial structure and economic growth. After briefly outlining the major examples used in discussions of financial structure, I describe the major analytical limitations impeding research on financial structure and economic growth. The classic controversy involves the comparison between Germany and the United Kingdom. Starting early in this century, economists argued that differences in the financial structure of the two countries help explain Germany's more rapid economic growth rate during the latter half of the 19th century and the first decade of the 20th century (Alexander Gerschenkron 1962). The premise is as follows. Germany's bank-based financial system, where banks have close ties to industry, reduces the costs of acquiring information about firms, This makes it easier for the financial system to identify good investments, exert corporate control, and mobilize savings for promising investments than in England's more securities market oriented financial system, where the ties between banks and industry are less intimate. Indeed, quite a bit of evidence suggests that German bankers were more closely tied to industry than British bankers. Unlike England, nearly all German bankers started as merchants. The evolution from entrepreneur to banker may explain the comparatively close bonds between bankers and industrialists.There are severe analytical problems with linking financial structure to economic performance. First, existing research on financial structure does not quantify the structure of financial systems or how well different financial systems function overall. For example, German bankers may have been more closely connected to industrialists than their British counterparts, but less capable at providing liquidity and facilitating transactions. Similarly, while Japanese Keiretsumay lower information acquisition costs between banks and firms, this does not necessarily imply that the Japanese financial system provides greater risk sharing mechanisms or more accurately spot promising new lines of business. Furthermore, while Japan is sometimes viewed as a bank-based system, it has one of the best developed stock markets in the world (Demirguc-Kunt and Levine 1996a). Thus, the lack of quantitative measures of financial structure and the functioning of financial system make it difficult to compare financial structures.Second, given the array of factors influencing growth in Germany, Japan, the United Kingdom, and the United States, it is analytically difficult-and perhaps reckless-to attribute differences in growth rates to differences in the financial sector. Moreover, over the post World War II period, the devastated Axis powers may simply have been converging to the income levels of the United States, such that observed growth rate differentials have little to do with financial structure. Thus, before linking financial structure with economic growth, researchers need to control for other factors influencing long-run growth.A third factor that complicates the analysis of financial structure and economic growth is more fundamental. The current debate focuses on bank-based systems versus market-based systems. Some aggregate and firm level evidence, however, suggest that this dichotomy is inappropriate. The data indicate that both stock market liquidity-as measured by stock trading relative to GDP and market capitalization-and the level of banking development-as measured by bank credits to private firms divided by GDP predict economic growth over subsequent decades {Levine and Zervos 1996). Thus, it is not banks or stock markets; bank and stock market development indicators both predict economic growth. Perhaps, the debate should not focus on bank-based versus market-based systems because these two components of the financial system enter the growth regression significantly and predict future economic growth. It may be that stock markets provide a different bundle of financial functions from those provided by financial intermediaries. For example, stock markets may primarily offer vehicles for trading risk and boosting liquidity. In contrast, banks may focus on ameliorating information acquisition costs and enhancing corporate governance of major corporations. This is merely a conjecture, however. There are important overlaps between the services provided by banks and stock markets. As noted above, well-functioning stock markets may ameliorate information acquisition costs, and banks may provide instruments for diversifying risk and enhancing liquidity. Thus, to understand the relationshipbetween financial structure and economic growth, we need theories of the simultaneous emergence of stock markets and banks and we need empirical proxies of the functions performed by the different components of financial systems.A fourth factor limiting our understanding of the links between financial structure and economic growth is that researchers have focused on a few industrialized countries due to data limitations. The United States, Germany, Japan, and the United Kingdom have basically the same standard of living. Averaged over a sufficiently long time period, they must also have very similar growth rates. Thus, comparisons of financial structure and economic development using only these countries will tend to suggest that financial structure is unrelated to the level and growth rate of economic development. Future studies will need to incorporate a more diverse selection of countries to have even a chance of identifying patterns between financial structure and economic development.Finally, there are important interactions between stock markets and banks during economic development that have not been the focus of bank-based versus market-based comparisons. As noted, greater stock market liquidity is associated with faster rates of capital formation. Nonetheless, new equity sales do not finance much of this new investment (Cohn Mayer 1988), though important differences exist across countries (AjitSingh and Javed Hamid 1992). Most new corporate investment is financed by retained earnings and debt. This raises a quandary: stock market liquidity is positively associated with investment, but equity sales do not finance much of this investment. This quandary is confirmed by firm-level studies. In relatively poor countries, enhanced stock market liquidity actually tends to boost corporate debt-equity ratios; stock market liquidity does not induce a substitution out of debt and into equity finance (Demirgu-Kunt and Maksimovic 1996a).However, for industrialized countries, debt-equity ratios fall as stock market liquidity rises; stock market liquidity induces a substitution out of debt finance. The evidence suggests complex interactions between the functioning of stock markets and corporate decisions to borrow from banks that depend on the overall level of economic development. Thus, we need considerably more research into the links among stock markets, banks, and corporate financing decisions to understand the relationship between financial structure and economic growth.ConclusionTheory and evidence make it difficult to conclude that the financial system merely-and automatically-responds to industrialization and economic activity, or thatfinancial development is an inconsequential addendum to the process of economic growth. I believe that we will not have a sufficient understanding of long-run economic growth until we understand the evolution and functioning of financial systems. This conclusion about financial development and long-run growth has an important corollary: although financial panics and recessions are critical issues, the finance-growth link goes beyond the relationship between finance and shorter-term fluctuations.Undoubtedly, the financial system is shaped by nonfinancial developments. Changes in telecommunications, computers, nonfinancial sector policies, institutions, and economic growth itself influence the quality of financial services and the structure of the financial system. Technological improvements lower transaction costs and affect financial arrangements (Merton 1992). Monetary and fiscal policies affect the taxation of financial Intermediaries and the provision of financial services (Bencivenga and B. Smith 1992; Roubini and Sala-i-Martin 1995). Legal systems affect financial systems (LaPorta et al. 1996), and political changes and national institutions critically influence financial development (Haber 1991, 1996). Furthermore, economic growth alters the willingness of savers and investors to pay the costs associated with participating in the financial system (Greenwood and Jovanovic 1990). Much more information about the determinants and implications of financial structure will move us closer to a comprehensive view of financial development and economic growth.金融发展与经济增长：观点与目的标题：金融发展与经济增长：观点与目的资料来源: 经济学文献杂志作者：罗斯·莱文（1）金融系统的作用第一，促进分散风险。
金融与经济发展的关系
金融与经济发展的关系内容摘要：金融已逐步由最初中介商品交换的辅助工具发展成为经济活动中一个相对独立因素。
一方面，金融通过促进储蓄和投资增长、优化资源配置、便利交换等活动，推动经济增长；另一方面，金融风险的存在以及不合理的金融发展又令经济增长受阻。
因此，合理发展金融不仅能促进经济发展、更能抑制其副作用。
这对发展中国家尤为重要。
关键词：金融经济发展促进阻滞金融是货币与信用的融合，它是商品交换与市场经济发展到一定阶段的产物。
在经济的发展过程中，以货币为媒介的商品交换打破了直接的物物交换中买卖双方在时空上的限制。
随后信用的发展又令货币与商品的交换在时空上的限制进一步放开，以至即使在交换双方商品所有权转移后市场仍继续存在，货币也逐渐作为一种可有偿转让的特殊商品成为市场交易对象之一。
于是，从商品流通中独立出了一种特殊商品——资本，金融也开始具有真正意义。
此后，金融工具逐步由单一的货币形式发展为货币、商业票据、股票债券等多种形式并存，出现了专门经营金融业务的金融机构以及从事金融活动的金融市场，金融开始由最初中介商品交换的辅助地位逐渐发展成为经济活动中一个相对独立的因素，通过其自身的货币发行、信用创造、资源配置等功能影响着社会再生产和经济发展的速度和质量。
一、如何理解金融与经济发展的关系？（一）经济发展决定金融1、金融是依附于商品经济的一种产业，是在商品经济的发展过程中产生并随着商品经济的发展而发展的。
2、商品经济的不同发展阶段决定着同期的金融状况。
（二）金融对现代经济发展的推动作用1、通过金融运作为经济发展提供条件2、通过金融的基本功能为经济发展提供资金支持3、通过金融机构的经营运作节约交易成本，促进资金融通，便利经济活动，合理配置资源，提高经济发展的效率。
4、通过金融业自身的产值增长直接为经济发展作出贡献。
（三）金融对经济发展可能出现的不良影响1、因金融总量失控出现通货膨胀、信用膨胀，导致社会总供求失衡，危害经济发展。
最新国际结算(英文版)清华大学出版社-答案(1)
KEY OF INTERNATIONAL SETTLEMENTChapter 12.Put the following sentences into English(1)国际结算涉及有形贸易和无形贸易，外国投资，从其他国家借贷资金，等等。
The international settlement involves tangible trades, intangible trades, foreign investments, funds borrowed from or lent to other countries and so on.(2)许多银行注重发展国际结算和贸易融资的业务。
Many banks have focused on their business of international settlement and trade finance. (3)大多数国际间的支付来自于世界贸易。
Most of the international payments originate from transactions in the world trade.(4)一般来说，国际结算的方式分为三类：汇款、托收和信用证。
Usually the international settlement is divided into three broad categories: remittance, collection and letter of credit.3. True or False1)International payments and settlements are financial activities conducted in the domesticcountry. (F)2)Fund transfers are processed and settled through certain clearing systems.(T)3)Using the SWIFT network, banks can communicate with both customers and colleagues in astructured, secure, and timely manner.(T)4)SWIFT can achieve same day transfer.(T)4.Multiple Choice1)SWIFT is __B__A.in the united statesB. a kind of communications belonging to TT system for interbank’s fund transferC.an institution of the United NationsD. a governmental organization2)SWIFT is an organization based in __A___A.BrusselsB.New YorkC.LondonD.Hong Kong3) A facility in fund arrangement for buyers or sellers is referred to __A___A.trade financeB.sale contractC.letter of creditD.bill of exchange4)Fund transfers are processed and settled through __C___A.banksB.SWIFTC.clearing systemD.telecommunication systems5)__C__is the reason why international trade first began.A.Uneven distribution of resourcesB.Patterns of demandC.Economic benefitsparative advantages5. Answer the following questions1)Where are the medium of exchange originated from?Tracing back the history of international settlement, the medium of exchange originated from coins to notes.2)What will inevitably lead to under the international political, economic and culturalexchanges?The international political, economic and cultural exchange inevitably leads to credits and debts owed by one country to another.3)Why do banks focus on the development of the businesses of international settlement?Banks focus more and more on the development of the businesses because it is a major resource of profits.4)What will banks do to meet the higher and higher demand of the international market?Banks need to develop innovative products and deliver the best services possible in whatever way they can.Chapter 2(1)用于国际结算的货币是可兑换的货币。
银行资产分类词汇
acetate yarn?醋酸纤维acetic acid?醋酸acetone?丙酮acetyl chemicals?乙酰(xian-1)化学品acrylonitrile?丙烯腈amorphouspolyolefins?无结晶聚烯烃benzene?苯biodegradablepolyesters?生物裂解聚酯butadiene?丁烷butylene?丁烯cellulose acetate fiber ?醋酸纤维coatings and paint raw materials?涂料和油漆原料copolyesters?共聚酯custom chemicals ?专门定购化学品Eastotac?树脂engineering compounded plastics?工程复合塑料ethane?乙烷ethylanmine?乙胺ethylene?乙烯ethylene glycol(MEG)?乙二醇film?薄膜filter tow?过滤用长丝fine chemicals ?精细化学品foodingredients?食品添加剂glycol-modified polyethylene terephthalate(PETG)?醇化聚酯heavy-gauge sheeting?厚板材
on-site inspection?现场检查on-sitevisit?现场访问out-of-area loan?外地信贷outstandingbalance?未清偿余额overdue?逾期pass, overdue, idle & bad loans(POIB)?一逾两呆past due loans?逾期贷款pending factor?未决因素poorly structuredloan?结构不合理贷款problem loans?有问题贷款Profit and loss?损益（表）provision?准备金provisioning?准备金提取quick ratio?速动比率rehabilitation?repaymentschedule?还款计划restructured loans?重组贷款risk-weightedasset?风险加权资产ROCA?洛卡评级法roll-overs?展期securityenforcement?行使抵押权side agreement?附件special mentionasset?特别提及资产special reserve?特殊准备金specific reserve?专项准备金substandardassets?次级资产suspense account?挂帐term loan?定期贷款to credit?贷记todebit?借记trading on equity?财务杠杆；举债经营troubled loan?有问题贷款turnoverratio?周转比率weak loan?低质量贷款work outproblem?核销有问题write-off?冲销write-up ?(贷款)批评报告
经济财务术语中英文对照
财务术语中英文对照一、会计与会计理论会计accounting决策人DecisionMaker投资人Investor股东Shareholder债权人Creditor财务会计FinancialAccounting管理会计ManagementAccounting负债Liability业主权益Owner'sEquity收入Revenue费用Expense收益Income亏损Loss历史成本原则CostPrinciple收入实现原则RevenuePrinciple配比原则MatchingPrinciple全面披露原则Full-disclosure(Reporting)Principle客观性原则ObjectivePrinciple一致性原则ConsistentPrinciple可比性原则ComparabilityPrinciple重大性原则MaterialityPrinciple稳健性原则ConservatismPrinciple权责发生制AccrualBasis现金收付制CashBasis财务报告FinancialReport流动资产Currentassets流动负债CurrentLiabilities长期负债Long-termLiabilities投入资本ContributedCapital库存现金Cashinhand流动资产Currentassets偿债基金Sinkingfund定额备用金Imprestpettycash支票Check(cheque)银行对帐单Bankstatement银行存款调节表Bankreconciliationstatement 在途存款Outstandingdeposit在途支票Outstandingcheck应付凭单Voucherspayable应收帐款Accountreceivable应收票据Notereceivable起运点交货价F.O.Bshippingpoint目的地交货价F.O.Bdestinationpoint商业折扣Tradediscount现金折扣Cashdiscount销售退回及折让Salesreturnandallowance坏帐费用Baddebtexpense备抵法Allowancemethod寄销Consignment寄销人Consignor承销人Consignee定期盘存Periodicinventory永续盘存Perpetualinventory购货Purchase购货折让和折扣Purchaseallowanceanddiscounts 存货盈余或短缺Inventoryoveragesandshortages 分批认定法Specificidentification加权平均法Weightedaverage先进先出法First-in,first-outorFIFO后进先出法Lost-in,first-outorLIFO移动平均法Movingaverage成本或市价孰低法LowerofcostormarketorLCM市价Marketvalue重置成本Replacementcost可变现净值Netrealizablevalue上限Upperlimit下限Lowerlimit到期日Maturitydate到期值Maturityvalue直线摊销法Straight-Linemethodofamortization实际利息摊销法Effective-interestmethodofamortization--------------------------------------------------------- 六、固定资产固定资产PlantassetsorFixedassets原值Originalvalue预计使用年限Expectedusefullife预计残值Estimatedresidualvalue折旧费用Depreciationexpense累计折旧Accumulateddepreciation帐面价值Carryingvalue应提折旧成本Depreciationcost净值Netvalue在建工程Construction-in-process磨损Wearandtear过时Obsolescence直线法Straight-linemethod(SL)应付帐款Accountpayable应付票据Notespayable贴现票据Discountnotes长期负债一年内到期部分Currentmaturitiesoflong-termliabilities 应付股利Dividendspayable预收收益Prepaymentsbycustomers存入保证金Refundabledeposits应付费用Accrualexpense增值税valueaddedtax营业税Businesstax应付所得税Incometaxpayable应付奖金Bonusespayable产品质量担保负债Estimatedliabilitiesunderproductwarranties 赠品和兑换券Premiums,couponsandtradingstamps或有事项Contingency或有负债Contingent或有损失Losscontingencies或有利得Gaincontingencies永久性差异Permanentdifference折价Discount面值Parvalue直线法Straight-linemethod实际利率法Effectiveinterestmethod到期直接偿付Repaymentatmaturity提前偿付Repaymentatadvance偿债基金Sinkingfund长期应付票据Long-termnotespayable抵押借款Mortgageloan--------------------------------------------------十、业主权益权益Equity业主权益Owner'sequity股东权益Stockholder'sequity投入资本Contributedcapital缴入资本Paid-incapital股本Capitalstock资本公积Capitalsurplus留存收益Retainedearnings现金股利Cashdividend股票股利Stockdividend拨款appropriation------------------------------------------------------------ 十一、财务报表财务报表FinancialStatement资产负债表BalanceSheet收益表IncomeStatement帐户式AccountForm报告式ReportForm编制（报表）Prepare工作底稿Worksheet多步式Multi-step单步式Single-step----------------------------------------------------------- 十二、财务状况变动表财务状况变动表中的现金基础SCFP.CashBasis（现金流量表）财务状况变动表中的营运资金基础SCFP.WorkingCapitalBasis存货周转率Inventoryturnover应收帐款周转率Accountsreceivableturnover流动比率Currentratio速动比率Quickratio酸性试验比率Acidtestratio------------------------------------------------------------ 十四、合并财务报表合并财务报表Consolidatedfinancialstatements吸收合并Merger创立合并Consolidation控股公司Parentcompany附属公司Subsidiarycompany少数股权Minorityinterest权益联营合并Poolingofinterest购买合并Combinationbypurchase权益法Equitymethod成本法Costmethod------------------------------------------------------------ 十五、物价变动中的会计计量一、资产类11001库存现金cashonhand21002银行存款bankdeposit51015其他货币资金othermonetarycapital91101交易性金融资产transactionmonetaryassets111121应收票据notesreceivable121122应收账款Accountreceivable131123预付账款accountprepaid141131应收股利dividendreceivable151132应收利息accruedinterestreceivable211231其他应收款accountsreceivable-others221241坏账准备haddebtsreserve281401材料采购procurementofmaterials291402在途物资materialsintransit301403原材料rawmaterials321406库存商品commoditystocks331407发出商品goodsintransitproductivelivingassetsaccumulateddepreciationexclusivelyforagriculture641623公益性生物资产农业专用non-profitlivingassetsexclusivelyforagriculture 651631油气资产石油天然气开采专用oilandgasassetsexclusivelyforoilandgasexploitation661632累计折耗石油天然气开采专用accumulateddepletionexclusivelyforoilandgasexploitation671701无形资产intangibleassets681702累计摊销accumulatedamortization691703无形资产减值准备intangibleassetsreductionreserve701711商誉businessreputation711801长期待摊费用long-termdeferredexpenses721811递延所得税资产deferredincometaxassets731901待处理财产损溢waitingassetsprofitandloss二、负债类debtgroup742001短期借款short-termloan812101交易性金融负债transactionfinancialliabilities 832201应付票据notespayable842202应付账款accountpayable1164002资本公积contributedsurplus1174101盈余公积earnedsurplus1194103本年利润profitforthecurrentyear1204104利润分配allocationofprofits1214201库存股treasurystock五、成本类1225001生产成本productioncost1235101制造费用costofproduction1245201劳务成本servicecost1255301研发支出researchanddevelopmentexpenditures1265401工程施工建造承包商专用engineeringconstructionexclusivelyforconstructioncontractor1275402工程结算建造承包商专用engineeringsettlementexclusivelyforconstructioncontractor1285403机械作业建造承包商专用mechanicaloperationexclusivelyforconstructioncontractor六、损益类1296001主营业务收入mainbusinessincomeaccountingprofit会计利润adverseselection逆向选择allocation配置allocationofresources资源配置allocativeefficiency配置效率antitrustlegislation反托拉斯法arcelasticity弧弹性assumption假设asymmetricinformation非对称性信息average平均averagecost平均成本averagecostpricing平均成本定价法averagefixedcost平均固定成本averageproductofcapital资本平均产量averageproductoflabour劳动平均产量averagerevenue平均收益averagetotalcost平均总成本averagevariablecost平均可变成本B12changeinsupply供给变化choice选择closedset闭集Coasetheorem科斯定理Cobb-Douglasproductionfunction柯布--道格拉斯生产函数cobwebmodel蛛网模型collectivebargaining集体协议工资collusion合谋commandeconomy指令经济commodity商品commoditycombination商品组合commoditymarket商品市场commodityspace商品空间commonproperty公用财产comparativestaticanalysis比较静态分析compensatedbudgetline补偿预算线compensateddemandfunction补偿需求函数compensationprinciples补偿原则compensatingvariationinincome收入补偿变量consumptionpossibilitycurve消费可能曲线consumptionpossibilityfrontier消费可能性前沿consumptionset消费集consumptionspace消费空间continuity连续性continuousfunction连续函数contractcurve契约曲线convex凸convexfunction凸函数convexpreference凸偏好convexset凸集corporation公司cost成本costbenefitanalysis成本收益分析costfunction成本函数costminimization成本最小化Cournotequilibrium古诺均衡Cournotmodel古诺模型cross-priceelasticity交叉价格弹性disequilibrium非均衡distribution分配divisionoflabour劳动分工duopoly双头垄断、双寡duality对偶durablegoods耐用品dynamicanalysis动态分析dynamicmodels动态模型E50economicagents经济行为者economiccost经济成本economicefficiency经济效率economicgoods经济物品economicman经济人economicmode经济模型economicprofit经济利润economicregulation经济调节economicrent经济租金exchange交换equivalentvariationinincome收入等价变量excess-capacitytheorem过度生产能力定理existence存在性existenceofgeneralequilibrium总体均衡的存在性expansionpaths扩展径expectation期望expectedutility期望效用expectedvalue期望值expenditure支出explicitcost显性成本externalbenefit外部收益externalcost外部成本externaleconomy外部经济externaldiseconomy外部不经济externalities外部性F24factor要素factordemand要素需求factormarket要素市场Giffengoods吉芬商品Giffen'sParadox吉芬之谜Ginicoefficient吉尼系数goldenrule黄金规则governmentfailure政府失败governmentregulation政府调控grandutilitypossibilitycurve总效用可能曲线grandutilitypossibilityfrontier总效用可能前沿H9heterogeneousproduct异质产品Hicks-kaldorwelfarecriterion希克斯－卡尔多福利标准homogeneity齐次性homogeneousdemandfunction齐次需求函数homogeneousproduct同质产品homogeneousproductionfunction齐次生产函数horizontalsummation水平和humancapital人力资本hypothesis假说I52industryequilibrium产业均衡industrysupplycurve产业供给曲线inelastic缺乏弹性的inferiorgoods劣品inflectionpoint拐点information信息informationcost信息成本initialcondition初始条件initialendowment初始禀赋innovation创新input投入input-output投入－产出institution制度institutionaleconomics制度经济学insurance保险intercept截距interest利息interestrate利息率intermediategoods中间产品least-costcombinationofinputs最低成本的投入组合leisure闲暇Leontiefproductionfunction里昂惕夫生产函数licenses许可证lineardemandfunction线性需求函数linearhomogeneity线性齐次性linearhomogeneousproductionfunction线性齐次生产函数longrun长期longrunaveragecost长期平均成本longrunequilibrium长期均衡longrunindustrysupplycurve长期产业供给曲线longrunmarginalcost长期边际成本longruntotalcost长期总成本Lorenzcurve洛伦兹曲线lossminimization损失极小化lumpsumtax一次性征税luxury奢侈品M45marketmechanism市场机制marketstructure市场结构marketseparation市场分割marketregulation市场调节marketshare市场份额markuppricing加减定价法Marshalliandemandfunction马歇尔需求函数maximization最大化microeconomics微观经济学minimumwage最低工资misallocationofresources资源误置mixedeconomy混合经济monopolisticcompetition垄断竞争monopolisticexploitation垄断剥削monopoly垄断，卖方垄断monopolyequilibrium垄断均衡monopolypricing垄断定价monopolyregulation垄断调控monopolyrents垄断租金optimalchoice最佳选择optimalconsumptionbundle消费束optimalresourceallocation最佳资源配置optimalscale最佳规模optimalsolution最优解optimization优化orderingofoptimization(social)preference （社会）偏好排序ordinalutility序数效用ordinarygoods一般品output产出outputelasticity产出弹性outputmaximization产出极大化P68parameter参数Paretocriterion帕累托标准Paretoefficiency帕累托效率Paretoimprovement帕累托改进Paretooptimality帕累托优化pricedifference价格差别pricediscrimination价格歧视priceelasticityofdemand需求价格弹性priceelasticityofsupply供给价格弹性pricefloor最低限价pricemaker价格制定者pricerigidity价格刚性priceseeker价格搜求者pricetaker价格接受者privatebenefit私人收益principal-agentissues委托－代理问题privatecost私人成本privategoods私人用品privateproperty私人财产producerequilibrium生产者均衡producertheory生产者论producttransformationcurve产品转换曲线productdifferentiation产品差异productgroup产品集团rationality理性reactionfunction反应函数regulation调节，调控relativeprice相对价格rent租金rentseeking寻租rentseekingeconomics寻租经济学resource资源resourceallocation资源配置returns报酬、回报returnstoscale规模报酬revealedpreference显示性偏好revenue收益revenuecurve收益曲线revenuefunction收益函数revenuemaximization收益最大化ridgeline脊线S43satiation饱和，满足space空间stability稳定性stableequilibrium稳定的均衡Stackelbergmodel斯塔克尔贝格模型staticanalysis静态分析stock存量stockmarket股票市场strategy策略subsidy补贴substitutes替代品substitutioneffect替代效应substitutionparameter替代参数sufficientcondition充分条件supplyschedule供给表Sweezymodel斯威齐模型symmetry对称性symmetryofinformation信息对称T16tangency相切valuejudge价值判断valueofmarginalproduct边际产量价值variablecost可变成本variableinput可变投入variables变量vector向量visiblehand看得见的手vulgareconomics庸俗经济学W8wagerate工资率Walrasgeneralequilibrium瓦尔拉斯总体均衡Walras'slaw瓦尔拉斯法则Wants需要Welfarecriterion福利标准Welfareeconomics福利经济学Welfarelosstriangle福利损失三角形Welfaremaximization福利最大化Z4zerocost零成本期货期权术语中英文对照一、期货1 Futuresmarket期货市场2 Futurescontract期货合约3 Financialfutures金融期货4 Commodityfutures商品期货5 Financialfuturescontract金融期货合约6 Currencyfuturescontract货币期货合约7 Interestratefuturescontract利率期货合约8 Stockindexfuturescontract股票指数期货合约34 Converge集聚（期货和现货价格）35 Swing变动（幅度），摆动，涨跌36 Crosshedge交叉套做37 Volatile易变的，不稳定的38 Volatilemarket不稳定的市场行情39 Marginmoney预收保证金，开设信用证保证金40 position头寸，交易部位，部位41 Longposition多头寸，买进的期货合同42 Shortposition空头43 Exchangeposition外汇头寸，外汇动态44 Interestposition利率头寸45 Swapposition调期汇率头寸46 Squareposition差额轧平（未抵冲的外汇买卖余额的轧平状况）47 Brokeragefirm经纪商（号）48 Securitybond保付单49 Post登记总帐，过帐50 Brokerage经纪业，付给经纪人的佣金51 FXfuturescontract外汇期货合约52 Foreigncurrencyfutures外汇期货78 Closingorder收市价订单79 Basisorder基差订单80 Corners垄断81 Outrightposition单笔头寸82 Directhedging直接套做83 Indirecthedging间接套做84 Shorthedging空头套做85 Longarbitrage多头套做86 Backspreads反套利87 Margincall保证金统治88 Pricediscovery价格发现二、期权1 Option期权，选择权，买卖期权2 Callandputoptions买入期权和卖出期权3 Optionbuyer期权的买方4 Optionseller期权的卖方5 Underlyingsecurities标的证券6 Exerciseprice,strikingprice履约价格，认购价格7 Optionfee=optionpremiumorpremiumonoption期权费33 Out-of-the-money无内在价值的期权34 In-the-money有内在价值的期权35 At-the-money平值期权36 Cropup(out)出现，呈现37 Cap带利率上限的期权38 Floor带利率下限的期权39 Floortrader交易员40 Break-even不亏不盈，收支相抵41 Asymmetry不对称42 Symmetry对称43 Sellforward远期卖出44 Up-frontfee预付费用，先期费用45 Changehands交换，换手46 Contractualvalue合同价格47 Over-the-counter场外的，不同过交易所的48 Customize按顾客要求制作49 Futuresmargin期货保证金50 Initialmargin初始保证金51 Openposition头寸77 Optionpurchaseprice期权的购进价格78 Optionsonfuturescontract期货合同的期权交易79 Forwardswap远期掉期80 Swaprate掉期率81 Risktransformation风险转移82 Contractsize合约容量83 Dailylimit每日涨跌停板84 Doubleoption双向期权三、市场1 Physicaltrading现货交易2 Arbitrage市场间套利3 BasisPrice/StrikePrice基本价格，履约价格4 Bear卖空者，看跌者5 Bearmarket空头市场，熊市6 Bullmarket7 Bottom底价：某时间段内的最低价8 Peak 高价：某时间段的最高价9 Businessday交易日10 Primarymarket初级市场36 European-styleoptions欧式期权37 Arbitration仲裁38 Assignment转让39 Averagedailyvolume平均每日交易量40 Boardoftrade交易委员会41 Breakeven平衡点（收支相抵）42 Brokerage/Commission佣金43 Brokeragehouse经纪行44 Buytoclose 买进平仓45 Buytoopen买入建仓46 Cancelingorder取消订单47 Clearingfee结算费48 Close收盘、收市49 Closingprice收盘价50 Coupon票面利率51 Customermargin客户保证金52 Dailytradinglimits日交易限制53 Daytrader当日交易者54 Deferred延期80 Mark-to-market逐日结算81 Marketorder市价委托单82 Marketsegment市场划分83 Marketvalue市场价值84 Matchedtrade配对交易85 Maturity到期期间86 Noticeday通知日87 Positionlimit持仓限额88 Purchasingpower购买力89 Quotation报价90 Referenceprice参考价格91 Resistanceline阻力线92 Retracement背离93 Supportline支撑线94 Symbol符号95 Targetprice目标价格96 Tradebalance贸易收支97 Treasurybill美国短期国债98 Variablelimit可变限度。
1-1. 信息不对称与财务报告质量在债务契约中的作用：来自次级贷款市场的证据
The role of information asymmetry and financial reporting quality in debt contracting:Evidence from the secondary loan market*Regina Wittenberg Moerman§First version: December 2004This version: December 2005AbstractI employ unique data on secondary loan trades to explore how information asymmetry and thequality of financial reporting affect the trading spreads of private debt securities. There are twoprimary findings. First, the bid-ask spread in secondary loan trading is positively related to firm-and loan-specific characteristics associated with a high information asymmetry environment.Loans of private firms, loans without an available credit rating, loans syndicated by less reputablearrangers, distressed loans, and loans of loss firms are traded at significantly higher bid-askspreads. Second,timely incorporation of economic losses into borrowers’ financial statementsreduces the bid-ask spread at which their loans are traded. This finding suggests that high qualityfinancial reporting reduces the information costs associated with debt agreements and increasesthe efficiency of the secondary trade.*I am especially grateful to the members of my dissertation committee: Ray Ball (Chair), PhilipBerger, Douglas Diamond, Douglas Skinner and Abbie Smith for many insightful comments andhelpful discussions. I also thank Zahi Ben-David, Steven Crawford, Ellen Engel, Wendy Heltzer,Eugene Kandel, Randall Kroszner, Darren Roulstone, Gil Sadka, Haresh Sapra, Tony Tang andparticipants in the University of Chicago Accounting Seminar and the University of ChicagoFinance Brown Bag for valuable comments and suggestions. I would like to thank the LoanPricing Corporation for letting me use their loan trading data. I gratefully acknowledge thefinancial support of the University of Chicago, Graduate School of Business.§Graduate School of Business, University of Chicago, 5807 S. Woodlawn Ave., Chicago, IL60637; email: rwittenb@1. IntroductionThe U.S. syndicated loan market bridges the private and public debt markets and provides borrowers and lenders with a highly valuable source of financing and investment. The market consists of a wide-range primary loan market, where syndicated loans1 are originated, and an active secondary market, where loans are traded after the close of primary syndication. In the past 20 years, the syndicated loan market has been one of the most rapidly growing and innovative sectors of the U.S. capital market (Yago and McCarty, 2004). U.S. firms obtain over $1 trillion in new syndicated loans each year, which represents more than 50 percent of the annual U.S. equity and debt issuance (Weidner, 2000). The trading of syndicated loans has expanded from $8 billion in 1991 to $144.6 billion in 2003, a compound annual growth rate of 27 percent.In this paper, I employ a sample of traded syndicated loans to explore two fundamental concepts in accounting and finance research: information asymmetry and financial reporting quality. The existing literature that examines information asymmetry does so mainly in a context of equity markets,2 leaving the role of information asymmetry in the debt markets largely unexplored. The secondary loan market is a promising empirical setting to examine information asymmetry because it involves trading of debt securities of both public and private firms. Moreover, the secondary loan market provides unique information regarding trading of private debt issues.The first contribution of this paper is to explore how information asymmetry, as reflected in firm- and loan-specific characteristics, affects secondary loan trading spreads. Prior research primarily addresses loan sales by investigating banks’ incentives for loan trading3 and by1 In the syndicated loan market a loan is identified as a “facility”. Usually, a number of facilities with different maturities, interest rate spreads and repayment schedules are structured and syndicated as one transaction (deal) with a borrower. The analysis in this paper is performed at the individual facility level.2 See, for example, Copeland and Galai (1983), Glosten and Milgrom (1985), Kyle (1985), Amihud and Mendelson (1986), Diamond and Verrecchia (1991), Botosan (1997), Leuz and Verrecchia (2000), Easley et al. (2002), Easley and O’Hara (2004), Ertimur (2004) and Schrand and Verrecchia (2005).3 See Pavel and Phillis (1987), Pennacchi (1988), Gorton and Pennacchi (1995), Froot and Stein (1998), Demsetz (2000) and Cebenoyan and Strahan (2004).examining returns and price formation across the loan, bond and equity markets4. To the best of my knowledge, this study is the first to examine the determinants of the bid-ask spread in the secondary loan market.The empirical findings confirm that the bid-ask spread in the secondary loan trade is positively related to firm- and loan-specific characteristics associated with a high information asymmetry environment. There is clear evidence that loans of private firms are traded at higher spreads than loans of publicly reporting firms. The bid-ask spread is also significantly higher on loans without an available credit rating. Emphasizing the dominant role of the arranger of syndication in resolving information asymmetry, the results indicate that loan spreads are higher for loans syndicated by less reputable arrangers. I also find that loans of loss firms are traded at significantly higher spreads than facilities of profitable ones. Furthermore, the stronger adverse selection associated with distressed loans is reflected in the higher trading spreads of these loans.The analysis presented in this paper enriches our understanding of how information asymmetry is resolved in trading of private debt securities. I identify the determinants of the efficiency of the secondary loan trade5 and quantify their impact on the trading spreads. While a number of these determinants are documented by prior research to be associated with information asymmetry, others address the specificity of trading on the secondary loan market. The empirical analysis employs unique characteristics of the information environment of syndicated loans, such as the reputation of the arranger of syndication, the identity of the lender (i.e., institutional investor or bank), the loan-specific ratings, and the distinction between both distressed6 and par loans and profit and loss borrowing firms. The analysis of the firm- and loan-specific characteristics associated with a high information asymmetry environment not only widens our4 See Allen et al. (2004), Altman et al. (2004), and Allen and Gottesman (2005).5 Copeland and Galai (1983), Glosten and Milgrom (1985) and Kyle (1985) confirm that information asymmetry between potential buyers and sellers introduces adverse selection and reduces the liquidity in the secondary markets. Following this line of research, by “more efficient secondary trading” I imply more liquid trading, which is reflected in relatively lower bid-ask spreads.6 According to the secondary loan market’s convention, distressed loans are loans traded at a bid price below 90 percent of the par value.understanding of the role of information asymmetry in loan trading, but it is also a necessary step for exploring the impact of financial reporting quality on trading of private debt securities.The second contribution of this paper is to examine how financial reporting quality affects loan trading on the secondary market. Studies of financial reporting quality have mainly focused on equity markets,7 although Watts and Zimmerman (1986), Watts (1993, 2003a,b) and Holthausen and Watts (2001) conclude that the reporting demands of the debt markets principally influence accounting reporting. Therefore, the secondary loan market is both a natural and an important empirical setting in which to examine the role of financial reporting quality. More specifically, I investigate how the quality of financial reporting affects loan trading spreads, with a particular emphasis on exploring the impact of timely loss recognition.Since debt holders’ returns are mainly determined by the downside region of a borrower’s earnings distribution, investors in debt securities are more sensitive to borrowers’ losses than to borrowers’ profits. In addition, timely loss recognition more quickly triggers ex-post violations of debt covenants based on financial statement variables. By triggering debt covenant violations, timely loss recognition allows lenders to more rapidly employ their decision rights following economic losses, which increases the efficiency of debt agreements (Ball, 2001, Watts, 2003a, and Ball and Shivakumar, 2005a). The asymmetric payoff function of investors in debt securities and the effect of timely loss recognition on the debt contracting efficiency make the secondary loan market an excellent empirical setting in which to explore the importance of timely loss recognition.The impact of timely loss recognition on debt agreements should be particularly important for private debt contracts because private debt issues typically contain more extensive covenants than do public debt issues (Smith and Warner, 1979). Previous literature also demonstrates that private lenders set debt covenants fairly tightly relative to the underlying financial variables,7 The exceptions include Sengupta (1998), Ahmed et al. (2002), Beatty et al. (2002), Bharath, Sunder and Sunder (2004), Zhang (2004) and Francis et al. (2005).especially when compared to the covenants set by public lenders (DeAngelo et al., 1994, Assender, 2000, Dichev et al., 2002, and Dichev and Skinner, 2002).These differences between private and public debt contracts make the secondary loan market an especially promising setting for an empirical analysis of how timely loss recognition affects debt agreements.I employ three measures of timely loss recognition. First, following Ball and Shivakumar (2005a,b), timely loss recognition is estimated by the coefficient on a firm’s negative cash flows in a piecewise-linear regression of accruals on cash flows.8 Second, following Basu (1997), the timeliness of income in reflecting economic losses is measured by the coefficient on the current year negative stock returns in a piecewise-linear regression of earnings on the contemporaneous stock returns. Estimating Basu’s (1997) model by industry-specific and firm-specific regressions provides two additional measures of timely loss recognition.I find evidence that timely incorporation of economic losses in borrowers’ financial statements reduces the bid-ask spread at which their loans are traded. The effect of timely loss recognition on the trading spreads is statistically and economically significant; the evidence is consistent across different measures of timely loss recognition. These empirical findings confirm that high quality financial reporting reduces the information costs associated with debt agreements and thus increases the efficiency of the secondary loan trade. To the best of my knowledge, this paper is the first to document and quantify the efficiency gain from timely loss recognition in trading of securities on secondary markets.Although accounting theory suggests that timely incorporation of economic losses enhances the efficiency of debt contracting, there is little empirical evidence supporting this proposition.9 By providing evidence that timely loss recognition decreases information asymmetry regarding the borrower, my paper confirms that conservative reporting creates efficiency gains in debt contracting.8 Because of data limitations, this estimation is performed at the industry level.9 The exceptions include Ahmed et al. (2002) and Zhang (2004), who document that timely incorporation of economic losses reduces the cost of debt capital.To further examine the impact of financial reporting quality on loan trading, I investigate the relation between the bid-ask spread and timely gain recognition, the overall timeliness of a borrower’s financial reporting, as measured by R2 of the Basu regression, and unconditional conservatism. The results demonstrate that these attributes of accounting reporting are not significantly related to the loan trading spread. These findings further support the special role timely loss recognition plays in debt contracting.I also examine whether abnormal accruals influence loan trading spreads.10 While I do not observe a significant relation between unsigned abnormal accruals and the bid-ask spread, I find a positive and significant relation between signed abnormal accruals and the loan spread. I interpret these results as evidence that managers choose income-increasing accounting procedures to avoid or to mitigate debt covenant violations. Secondary market participants perceive loans with binding covenants as being subject to higher information uncertainty and this is reflected in the higher spreads of these facilities. The high information asymmetry environment associated with loans subject to binding covenants might be driven by managers’ manipulative behavior, as well as by the general uncertainty regarding the borrower’s creditworthiness and liquidity.My interpretation of the positive relation between the loan bid-ask spread and the signed abnormal accruals is consistent with the “debt covenant” hypothesis that suggests that managers make accounting choices which decrease the likelihood of debt covenant violations (Watts and Zimmerman, 1986, Healy and Palepu, 1990, DeFond and Jiambalvo, 1994, Sweeney, 1994, and Dichev and Skinner, 2002). To strengthen the empirical findings, I conduct a detailed examination of the loan contracts of the loans in the highest decile of signed abnormal accruals. Consistent with the “debt covenant” hypothesis, I find that the majority of firms with high positive abnormal accruals either violate debt covenants or have corresponding financial measures which are only two to four percent higher than the covenant threshold.10 Abnormal accruals are estimated by the Jones (1991) model, adjusted for the incorporation of the negative cash flow indicator variable. This adjustment reflects the role of accruals in timely recognition of economic losses, as suggested by Ball and Shivakumar (2005b).I also examine earnings volatility which the literature sees as being associated with a firm’s information environment. I find a positive relation between bid-ask spread and earnings volatility.11 The significance of this relation is, however, sensitive to the earnings category employed in the analysis. This sensitivity is potentially explained by the equivocal relation between earnings volatility and the quality of financial reporting. Highly predictable and smooth earnings decrease uncertainty about the borrower. However, if managers report opportunistically to achieve lower earnings variability, earnings are less informative (Francis et al., 2004).The following section provides a brief description of the secondary loan market. The third section outlines the research hypotheses. The fourth section describes the data and summary statistics. The fifth section focuses on the research design. The sixth section discusses empirical findings. The seventh section concludes.2. The secondary loan market: Background and developmentSecondary loan sales occur after the close of primary syndication; loan sales are structured as either assignments or participations.12 When interests in the loan are transferred by assignment, the buyer becomes a direct signatory to the loan. In participation, the original lender remains the holder of the loan and the buyer takes a participating interest in the existing lender’s commitment (Standard &Poor’s, 2003). While assignments usually require the consent of both the borrower and the arranger for the loan sale, in participations such consents are almost never required. Today, loan sales are performed through loan trading desks in more than 30 institutions which act as the market makers in the secondary loan market (Taylor and Yang, 2004).The secondary loan market has grown rapidly in recent years, with trading volume increasing from $8 billion in 1991 to $144.6 billion in 2003 (Loan Pricing Corporation (LPC), 2003). The market expanded in both par and distressed loans; the trading volume of loans traded11 Earnings volatility is estimated relative to a firm’s volatility of cash flows (Leuz et al., 2003).12 The majority of the loan sales in the secondary loan market are performed via assignment.at par and of distressed loans reached $87 billion and $57 billion in 2003, respectively. Leveraged loans represent the largest and the fastest growing part of the secondary loan market.13 Since 2001, trading of leveraged loans has constituted 80 percent of the total value of par loan trades.The involvement of institutional investors in the secondary loan market has increased considerably with the market’s development. Banks, loan participation mutual funds (prime funds)14, Collateralized Loan Obligations (CLOs)15 and finance companies constitute the main secondary loan market participants. Additionally, hedge funds and pension funds are increasing their activity in loan trading (Yago and McCarty, 2004).Several reasons contributed to the strong growth in loan sales. New bank regulatory requirements, such as the 1989 Highly Leveraged Transaction guidelines and the 1988 Basel Capital Accord, encourage banks to decrease their credit risk exposure (Altman et al., 2004, and Barth et al, 2004). Additionally, the adoption of SEC Rule 144A in 1990 provided a safe-harbor relief from the registration requirements of Section 5 of the Securities Act of 1933 for the resale of privately held debt and equity securities to qualified institutional buyers (QIB) (Allen et al., 2004, Hugh and Wang, 2004, and Yago and McCarty, 2004).16 The foundation of the Loan Syndication and Trading Association (LSTA)17 in 1995 was an additional factor that stimulated the development of the secondary loan market (Hugh and Wang, 2004).Development of the secondary loan market coincided with improvements in the market’s transparency. In 1987, LPC initiated the publication of Gold Sheets which provide a detailed 13 LPC defines leveraged loans as loans rated below BBB- or Baa3 or unrated and priced at the spread equal or higher than 150 bps above Libor.14 Prime funds are mutual funds that invest in leveraged loans. For the most part, prime funds are continuously offered funds with quarterly tender periods or true closed-end, exchange-traded funds (Standard &Poor’s, 2003).15 The CLOs purchase assets subject to credit risk (such as syndicated loans and mainly leveraged syndicated loans), and securitize them as bonds of various degrees of creditworthiness.16 QIB is defined as an institution that owns and manages $100 million ($10 million in the case of a registered broker-dealer) or more in qualifying securities. For a banking institution to qualify as a QIB, a $25 million minimum net worth test must also be satisfied. The objective of Rule 144A is to increase the efficiency and liquidity of the U.S. market for equity and debt securities issued in private placements by allowing large institutional investors to trade restricted securities more freely with each other.17 LSTA is a not-for-profit organization dedicated to promoting the orderly development of a fair, efficient, liquid and professional trading market for corporate loans and other similar private debt ().analysis of the market trends, loan price indexes and news coverage. In the late nineties, LSTA created standard documentation for primary and secondary loan markets and, jointly with LPC, started providing mark-to-market loan pricing based upon dealer quotes (Yago and McCarty, 2004). These initiatives significantly increased the amount of information available to secondary loan market participants. In addition, Standard & Poor’s, Moody’s and Fitch-ICBA started rating corporate syndicated loans in 1995. The rapid increase in the number of rated loans considerably reduced information uncertainty in the secondary loan market.3. Research hypotheses3.1 Impact of information asymmetry on secondary loan tradingCopeland and Galai (1983), Glosten and Milgrom (1985) and Kyle (1985) confirm that information asymmetry between potential buyers and sellers introduces adverse selection into secondary markets and reduces market liquidity. Following these theoretical models, many papers rely on the bid-ask spread as the main measure of information asymmetry.18 Because private debt contracts are subject to high information asymmetry, I expect information asymmetry, as reflected in firm- and loan-specific characteristics, to significantly influence loan trading spreads.The majority of loan trading involves leveraged loans; borrowers with this credit rating spectrum are expected to rely mainly on bank monitoring (Diamond, 1991). Diamond (1984) establishes that banks provide unique services in the form of credit evaluation and the monitoring of borrowers.19 For a bank to have the incentive to provide these services, it seems necessary that it hold a significant fraction of each loan that it originates. Although prior research addresses a bank’s motivation to monitor a loan after a portion of the loan has been sold, the efficiency of the18 See, for example, Lee et al. (1993), Yohn (1998), Leuz and Verrecchia (2000), Kalimipalli and Warga (2002), Ertimur (2004) and Sadka and Sadka (2004).19 Lummer and McConnell (1989) further support the importance of bank monitoring. Their study suggests that a bank is not producing information upon first contact with a borrower; rather, it learns information or takes action later in a course of a loan.post-sale bank monitoring remains an open theoretical and empirical question (Pennacchi, 1988, Gorton and Pennacchi, 1995, and Gorton and Winton, 2000). Since the relative advantage of bank monitoring is significantly higher for loans subject to high information asymmetry, I expect these facilities to be traded at higher information costs on the secondary loan market.By monitoring a borrower, lenders typically get access to a firm’s private sources of information which indicate its creditworthiness. However, the trading of syndicated loans involves secondary loan market participants who do not possess information sources available to lenders holding a loan contract. Therefore, information asymmetry should considerably affect the bid-ask spreads in the loan trading.20 Additionally, most secondary loan market participants are large institutions, such as banks and institutional investors, and Diamond and Verrecchia (1991) demonstrate that large traders are especially concerned about liquidity.The significant impact of information asymmetry on secondary market trading and its particular importance in private debt contracting lead to the following research hypothesis: H1: The bid-ask spread in secondary loan trading is positively related to firm- and loan-specific characteristics associated with a high information asymmetry environment.First, I focus on variables which previous research suggests as being related to information asymmetry. Second, to address the specificity of trading on the secondary loan market, I explore the unique characteristics of the information environment of the syndicated loans.Publicly reporting vs. private firmsWhen a borrower does not report to the SEC, secondary market participants have less publicly available information regarding a borrower’s creditworthiness and profitability. In addition, private firms are not subject to the rigorous monitoring by market forces, such as the SEC, auditors, analysts and public exchanges. Private firms are also less subject to litigations20 This prediction is strengthened by Gorton and Pennacchi (1990), who show that trading losses associated with information asymmetries can be mitigated by designing securities which split the cash flows of underlying assets into safer and riskier cash flows. Their analysis implies that loans of borrowers with more transparent information should be more efficiently traded by the “uninformed investors”.related to financial reporting and disclosure. Therefore, investing in debt securities of private firms usually requires that the lender have a higher screening and monitoring ability.Diamond and Verrecchia (1991), Leuz and Verrecchia (2000) and Verrecchia (2001) establish that a commitment to higher disclosure quality reduces information asymmetry. Since public firms have an inherent commitment to higher disclosure levels compared to private firms, this information underscores how important public reporting is to the reduction of information asymmetry regarding the borrower. In addition, private firms have less conservative reporting than public firms (Ball and Shivakumar, 2005a), which further emphasizes important differences in their information environments. I expect public borrowers’ debt securities to be traded with less information costs on the secondary loan market. Firms with public reporting are identified by an indicator variable taking the value of one if a borrower is a publicly reporting firm in the year when the facility is traded on the secondary loan market, zero otherwise.Availability of public credit ratingIf an independent credit agency does an evaluation of the borrower’s credit quality, then the availability of this estimate is anticipated to be associated with a lower information asymmetry environment (Dennis and Mullineaux, 2000, Lee and Mullineaux, 2004, and Gonas et al., 2004). The significance of the availability of a credit rating is also supported by the theoretical model of Diamond (1991) which emphasizes the importance of publicly available information, such as credit ratings, to the lender-borrower relationship. The existence of a credit rating is measured by an indicator variable taking the value of one if a firm and/or facility has an available credit rating, zero otherwise. More specifically, I carefully account for all potentially available credit rating categories, including Moody’s Sr. Debt, Moody’s Loan Rating, S&P Sr. Debt, S&P Loan Rating, Fitch LT and Fitch Loan Rating.Loan sizeFollowing previous literature, I use loan size as an additional measure associated with the amount and quality of information available regarding a borrower. According to Jones et al.(2005), information asymmetries tend to be less severe for large loans, since any fixed costs associated with obtaining information about a borrower are less of an obstacle for large loans. Bharath, Dahiya, Saunders, and Srinivasan (2004) also suggest that small borrowers have greater information asymmetries, and a loan’s size is typically positively correlated with its borrower’s size. Additionally, Diamond and Verrecchia (1991) demonstrate that large firms receive a larger benefit from disclosure than small firms. Generally, firm size is a widely used proxy for the amount of public information available regarding a company (Harris, 1994). As a result, larger loans are anticipated to be associated with lower information asymmetry environment.Reputation of the arranger of syndicationTo address the arranger’s dominant role in resolving information asymmetry in the syndicated loan market, the analysis incorporates the reputation of the syndicated facility’s arranger. The arranger negotiates the loan agreement, coordinates the documentation process and the loan closing, recruits loan participants and arranges the administration of repayments (Dennis and Mullineaux, 2000, Panyagometh and Roberts, 2002, and Lee and Mullineaux, 2004). While there is technically an independent loan agreement between the borrower and each of the investors, in practice, the syndicate participants typically rely on the information provided by the arranging bank (Jones et al., 2005).21 Therefore, the arranger’s reputation is expected to be negatively associated with information costs in the secondary loan trade.The importance of the arranger’s reputation is further motivated by the empirical evidence that more reputable arrangers are more likely to syndicate loans and are able to sell off a larger portion of a loan to the syndicate participants (Dennis and Mullineaux, 2000, Panyagometh and Roberts, 2002, and Casolaro et al., 2004). The literature interprets these findings as consistent with the proposition that the arranger’s status is a certification of the borrower’s financial 21 Prior literature suggests that the arranger does not exploit asymmetric information to distribute lower-quality loans to syndicate participants. A number of studies find that the arranger holds larger proportions of information-problematic and riskier loans in its own portfolio (Simons, 1993, Dennis and Mullineaux, 2000, Lee and Mullineaux, 2004, Jones et al., 2005, and Sufi, 2005). In addition, the arranger has been found to syndicate a larger proportion of a loan subsequently upgraded (Panyagometh and Roberts, 2002).。
IAS国际会计准则英文版
IAS国际会计准则英文版IFRS covers a wide range of accounting topics, including the recognition, measurement, presentation, and disclosure of financial information. It provides detailed guidelines on how to account for various assets, liabilities, equity, revenue, expenses, and other financial transactions. Some of the key accounting concepts and principles outlined in IFRS include:1. Fair value measurement: IFRS encourages the use of fair value as the basis for measuring assets and liabilities, where reliable and relevant market prices are available. This ensures that financial statements reflect the current economic value of an entity's assets and liabilities.2. Accrual basis accounting: IFRS requires the recognition of revenues and expenses in the period they are earned or incurred, regardless of when cash is received or paid. This provides a more accurate representation of an entity's financial performance.3. Going concern assumption: IFRS assumes that an entitywill continue its operations in the foreseeable future, unless there is evidence to the contrary. This enables financial statements to reflect the long-term nature of businessactivities and the related financial implications.4. Substance over form principle: IFRS emphasizes the economic substance of a transaction rather than its legal form. This ensures that financial statements reflect the underlying economic reality and prevent manipulation of financial results through artificial structures.However, the implementation of IFRS also poses challenges, particularly for smaller entities and emerging economies. These challenges include the need for additional training and expertise, potential costs associated with system upgrades, changes in accounting policies, and adaptation to new reporting requirements. Nevertheless, the long-term benefits of adopting IFRS are expected to outweigh these challenges, as it promotes global harmonization and convergence of accounting standards.。
宏观经济学原理曼昆-名词解释
宏观经济学原理(第七版)曼昆-名词解释(带英文)(总6页)--本页仅作为文档封面，使用时请直接删除即可----内页可以根据需求调整合适字体及大小--宏观经济学原理曼昆名词解释微观经济学（microeconomics），研究家庭和企业如何做出决策，以及它们如何在市场上相互影响。
宏观经济学（macroeconomics），研究整体经济现象，包括通货膨胀、失业和经济增长。
国内生产总值GDP（gross?domestic?product），在某一既定时期，一个国家内生产的所有最终物品与服务的市场价值。
消费（consumption），家庭除购买新住房之外，用于物品与服务的支出。
投资（investment），用于资本设备、存货和建筑物的支出，包括家庭用于购买新住房的支出。
政府购买（government?purchase），地方、州和联邦政府用于物品与服务的支出。
净出口（net?export），外国人对国内生产的物品的支出（出口），减国内居民对外国物品的支出（进口）。
名义GDP（nominal?GDP），按现期价格评价的物品与服务的生产。
真实GDP（real?GDP），按不变价格评价的物品与服务的生产。
（总之，名义GDP是用当年价格来评价经济中物品与服务生产的价值，真实GDP是用不变的基年价格来评价经济中物品与服务生产的价值。
）GDP平减指数（GDP,?deflator），用名义GDP与真实GDP的比率乘以100计算的物价水平衡量指标。
消费物价指数CPI（consumer?price?index），普通消费者所购买的物品与服务的总费用的衡量指标。
通货膨胀率（inflation?rate），从前一个时期以来，物价指数变动的百分比。
生产物价指数（producer?price?index），企业所购买的一篮子物品运服务的费用的衡量指标。
指数化（indexation），根据法律或合同按照通货膨胀的影响，对货币数量的自动调整。
[经济学]第二专题金融中介理论与我国银行业改革_OK
![[经济学]第二专题金融中介理论与我国银行业改革_OK](https://img.taocdn.com/s3/m/415215fe4a7302768f99399d.png)
• 在为借款人提供的贷款服务中，由于专门 从事贷款业务非银行金融中介业务发展 很快，而其筹集资金是通过发行股票和债 券，而不是存款，解决了银行资产和负债 在安全性和流动性方面可能出现的严重失 衡现象。而且伴随资本市场的发展，越来 越多的企业可以通过资本市场直接获得资 金，因此银行将不再是唯一合适的组织机 构。
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• （四）罗伯特. 默顿和兹维. 博迪在《金融学》中 提出六大功能
• （1）在不同的时间、地区和行业之间提供经济资 源转移的途径；
• （2）提供管理风险的方法； • （3）提供清算和结算支付的途径以完成交易； • （4）为储备资源和在不同企业分割所有权提供有
关机制； • （5）提供价格信息，帮助协调不同经济部门的决
第二专题 金融中介理论与我国银行业改革
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一、金融中介理论
• （一）金融中介机构 (financial intermediaries) 金融中介机构是指从资金的盈余单 位吸收资金提供给资金赤字单位以及提 供各种金融服务的经济体。
• 作 者：龚明华 • 出 版 社：经济科学出版社 • 出版时间：2006年06月
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• 谁监督监督者？金融中介一旦被赋子监督者 一的角色，又产生了金融中介本身的激励问题 和相应的代理成本。对此，Diamond认为银行制 度可以提供有效激励：存款人监督银行的最优 安排是存款合约，而银行通过分散投资降低风 险，使代理成本降到最低。活期存款为约束银 行行为提供了可置信威胁——如果银行监督企 业不力，委托人即存款人就会通过挤提对银行 进行惩罚。这就是著名的代理监督模型。它证 明了即使考虑金融中介自身的代理成本，金融 中介仍具有信息处理和监督的比较优势。
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• 4．参与成本说 Allen&Santomero（1998）最早提出了参
货币银行学外语专业词汇
货币银行学外语专业词汇Standard of Value 价值标准Medium of exchange 流通手段/交易媒介Store of Value 价值储藏Standard of deferred payment 延期支付Payment system 支付制度Universal equivalent 一般等价物Electronic funds transfer system, EFTS 资金调拨电子系统Price specie-flow mechanism 物价金币流动机制Standard coin 本位币Negotiable order of withdraw, NOW 通知存款Financial market 中介市场Saver-lenders 盈余单位Borrower-Spenders 赤字单位Financial intermediaries 金融机构间接融资Nominal interest rate 名义利率Effective rate of interest 实际利率Simple interest 单利Compound interest/interest on interest 复利/利滚利annuity 年金Coupon rate 息票利率Prepaid annuity 预付年金Perpetual annuity/perpetuity 永续年金Loanable Funds Theory of interest 可贷资金Present value 现值Future value 终值Interest arbitrage 套利Direct investment 直接投资Open financial markets 公开金融市场Primary market 一级市场Secondary market 二级市场Mutual fund 互助基金Negotiated-loan markets 协议贷款市场Money market 货币市场derivatives 衍生金融工具Convertible bonds 可转换债券Offshore market 离岸市场Kerb market/ over the counter 场外市场Federal Funds 联邦基金Repurchased agreements 回购协议forwards 远期合约option 期权swap 互换Bank for International Settlement, BIC 国际清算银行Financial Computerizing 金融电子化Legal reserve fund 法定存款准备金Static gap management 静态缺口管理The Japanese main bank system 日本主银行体系Universal bank 全能型银行Financial leasing company 金融租赁公司Central bank/ Bundesbank 中央银行Base money 基础货币The Quantity Theory of Money 货币数量论Equation of exchange 交易方程式Equation of balance 余额方程式The Cambridge Approach/ Cash-balance approach 现金余额说（剑桥方程式）Liquidity Preference Theory 流动性偏好论Transaction Motives 交易性动机Precautionary Motives 预防性动机Speculative Motives 投机性动机Liquidity trap 流动性陷阱monetarism 货币主义/现代货币数量说Demand-pull inflation 需求拉上型通货膨胀Cost-push inflation 成本推动型通货膨胀Structural inflation 结构性通货膨胀stagflation 滞涨Wage push inflation 工资推动型通货膨胀Profit-pull inflation 利润推动型通货膨胀Adverse selection 逆向选择Phillips curve 菲利浦斯曲线Expansionary 扩张性政策Discretionary 政策滞后效应Marginal propensity to consume 边际消费倾向Partial crowding out 部分挤出效应Off-balance-sheet activities 表外业务On-balance-sheet activities 表内业务Transmission mechanisms of monetary policy 货币政策的传导机制Gilt-edged 金边债券Asymmetric information 信息不对称Expected returns 预期回报率Automated teller machines, ATMs 自动取款机Financial globalization 金融全球化Financial innovations 金融创新Financial engineer 金融工程Gold standard 金本位制Gold exchange standard 金汇兑本位制Eurodollars 欧洲美元The Glass Steagall act 格拉斯-斯蒂格尔法案Regulation Q Q条款Credit crunch 信贷紧缩Bank runs 银行挤兑Bank panic 银行恐慌Basel accord 巴塞尔协议High powered money 高能货币Money multiplier 货币乘数Dealers 交易商Brokers 经纪商Junk bonds 垃圾债券Greshaw’ s law格雷欣法则Money market mutual funds(MMMF) 货币市场共同基金Money market deposit account (MMDA) 货币市场存款账户Certificates of deposits (CDs) 大额可转让定期存单Securities and exchange commission 证券交易委员会Federal deposit insurance company 联邦存款保险公司Strong-efficient market 有效市场recession 经济衰退stagnancy 经济不景气Market value of equity sensitivity analysis 股本市值敏感性分析Virtual bank 网上银行Open-end investment companies 开放式投资公司Closed-end investment companies 封闭式投资公司Credit union 信用社Savings and loan association 储蓄贷款协会货币银行学外文资料指导性教材1、Lawrence S.ritter, William L. Silber, Gregory. Udell, Principles of Money,Banking, and Financial Markets, Tenth Edition,19992、Frederic S.Mishkin, The Economics of Money, Banking and FinancialMarkets,19953、Bhattacha and Thakor, The Contemporary Banking Theory,19934、James A. Barry, JR., CFP, Let’s talk money, Dearborn trade Publishing, 1999货币银行学教学内容、方法、手段改革的方案、计划和措施1、丰富教学内容引入最新货币、金融领域的相关理论和实务。
ites 金融术语
ites 金融术语ITES金融术语ITES（Information Technology Enabled Services）是指通过信息技术实现的各种服务，其中金融术语是指在金融领域中常用的专业术语和概念。
下面将介绍一些常见的ITES金融术语。
1. 电子支付（Electronic Payment）电子支付是指通过网络或其他电子设备进行的支付活动。
包括网上银行、移动支付、电子钱包等多种形式。
电子支付的出现极大地方便了人们的支付方式，提高了支付的效率和安全性。
2. 金融科技（Financial Technology）金融科技是指应用先进的技术手段来改进金融服务和业务流程的领域。
包括人工智能、大数据、区块链等技术的应用，使金融行业更加高效、便捷和安全。
3. 云计算（Cloud Computing）云计算是指通过互联网将计算资源进行虚拟化和集中管理，为用户提供按需使用的计算服务。
在金融领域，云计算可以提供弹性计算能力和存储服务，降低金融机构的IT成本，提高数据处理和分析的效率。
4. 人工智能（Artificial Intelligence）人工智能是一种模拟人类智能的技术，通过机器学习和深度学习等算法，使计算机具备感知、理解、判断和决策的能力。
在金融领域，人工智能可以应用于风险管理、投资决策、客户服务等方面，提高金融机构的智能化水平。
5. 区块链（Blockchain）区块链是一种分布式账本技术，可以实现信息的去中心化和可追溯性。
在金融领域，区块链可以应用于数字货币、智能合约、供应链金融等方面，提高交易的安全性和透明度。
6. 大数据（Big Data）大数据是指由于数据量过大、数据类型多样等原因所产生的无法用传统数据库进行处理和分析的数据。
在金融领域，大数据可以用于风险评估、市场分析、个性化推荐等方面，提供更准确的决策支持。
7. 互联网金融（Internet Finance）互联网金融是指通过互联网技术和平台，进行金融活动的模式。
金融学期刊(JF)创刊以来50篇最经典论文
金融学期刊（JF）创刊以来50篇最经典论文1) Portfolio Selection证券组合选择Harry Markowitz Volume 7, Issue 1March 19522) Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk资本资产价格：风险条件下的市场均衡理论William F. SharpeVolume 19, Issue 3September 19643) Efficient Capital Markets: Review Of Theory And Empirical Work有效市场：理论与经验研究的评论Eugene F. FamaVolume 25, Issue 2May 19704) The Cross-Section Of Expected Stock Returns股票预期收益的横截面（分析）Eugene F. Fama, Kenneth R. FrenchVolume 47, Issue 2June 19925) Counterspeculation, Auctions, And Competitive Sealed Tenders反投机、拍卖和竞争性密封投标William VickreyVolume 16, Issue 1March 19616) A Survey Of Corporate Governance关于公司治理的调查Andrei Shleifer, Robert W. VishnyVolume 52, Issue 2June 19977) Legal Determinants Of External Finance外部融资的法律层面决定因素Rafael La Porta, Florencio Lopez-De-Silanes, Andrei Shleifer, Robert W. VishnyVolume 52, Issue 3July 19978) Corporate Ownership Around The World世界各地的企业所有权Rafael La Porta, Florencio Lopez-De-Silanes, Andrei ShleiferVolume 54, Issue 2April 19999) On the Pricing Of Corporate Debt: The Risk Structure Of Interest Rates 企业债务的定价：利率的风险结构Robert C. MertonVolume 29, Issue 2May 197410) Financial Ratios, Discriminant Analysis And Prediction Of Corporate Bankruptcy财务比率，判别分析和企业破产预测Edward I. AltmanVolume 23, Issue 4September 196811) The Modern Industrial Revolution, Exit, And The Failure Of Internal Control-Systems近代工业革命，退出，和内部控制系统的失灵Michael C. JensenVolume 48, Issue 3July 199312) On Persistence In Mutual Fund Performance共同基金绩效的持久性Mark M. CarhartVolume 52, Issue 1March 199713) On The Relation Between The Expected Value And The Volatility Of The Nominal期望值和名义股票超额回报波动性的关系Lawrence R. Glosten, Ravi Jagannathan, David E. RunkleVolume 48, Issue 5December 199314) Returns To Buying Winners And Selling Losers: Implications For Stock Market Efficiency购买赢家和卖掉输家的回报：对股市效率的启示Narasimhan Jegadeesh, Sheridan TitmanVolume 48, Issue 1March 199315) Informational Asymmetries, Financial Structure, And Financial Intermediation信息不对称、金融结构和金融中介Hayne E. Leland, David H. PyleVolume 32, Issue 2May 197716) The Pricing Of Options On Assets With Stochastic Volatilities具有随机波动性资产期权定价John Hull, Alan WhiteVolume 42, Issue 2June 198717) Efficient Capital Markets: II有效资本市场IIEugene F. FamaVolume 46, Issue 5December 199118) Does The Stock Market Overreact?股市反应过度了吗？Werner F. M. De Bondt, Richard ThalerVolume 40, Issue 3July 198519) Multifactor Explanations Of Asset Pricing Anomalies对资产定价异常现象的多因素解释Eugene F. Fama, Kenneth R. FrenchVolume 51, Issue 1March 199620) The Capital Structure Puzzle资本结构之谜Stewart C. MyersVolume 39, Issue 3July 198421) The Performance Of Mutual Funds In Period 1945-1964共同基金在1945年-1964年的绩效Michael C. JensenVolume 23, Issue 2May 196822) Debt And Taxes负债和税收Merton H. MillerVolume 32, Issue 2May 197723) What Do We Know About Capital Structure? Some Evidence From International Data我们对资本结构了解多少呢？来自国际数据的一些证据Raghuram G. Rajan, Luigi ZingalesDecember 199524) The Benefits Of Lending Relationships: Evidence From Small Business Data借贷关系的好处：来自小企业数据的证据Mitchell A. Petersen, Raghuram G. RajanVolume 49, Issue 1March 199425) Measuring And Testing The Impact Of News On Volatility衡量和检验新闻对波动性的影响Robert F. Engle, Victor K. NgVolume 48, Issue 5December 199326) Investor Psychology And Security Market Under- And Overreactions投资者心理和证券市场的过度反应/反应迟钝Kent Daniel, David Hirshleifer, Avanidhar SubrahmanyamVolume 53, Issue 6December 199827) Contrarian Investment, Extrapolation, And Risk逆向投资、外推法和风险Josef Lakonishok, Andrei Shleifer, Robert W. VishnyVolume 49, Issue 5December 199428) A Simple Model Of Capital Market Equilibrium With Incomplete Information 一个简单的信息不完全的资本市场均衡模型Robert C. MertonVolume 42, Issue 3July 198729) Insiders And Outsiders: The Choice Between Informed And Arms-Length DebtRaghuram G. RajanSeptember 199230) Why Does Stock Market Volatility Change Over Time? 为什么随着时间推移股市波动性会发生变化？G. William SchwertVolume 44, Issue 5September 198931) The Determinants Of Capital Structure Choice资本结构决策的决定因素Sheridan Titman, Roberto WesselsVolume 43, Issue 1March 198832) Inferring Trade Direction From Intraday Data从当日数据推断交易方向Charles M.C. Lee, Mark J. ReadyVolume 46, Issue 2June 199133) The New Issues Puzzle新股发行之谜Tim Loughran, Jay R. RitterVolume 50, Issue 1March 199534) The Limits Of Arbitrage套利限制Andrei Shleifer, Robert W. VishnyVolume 52, Issue 1March 199735) Noise噪声Fischer BlackVolume 41, Issue 3July 198636) Investor Protection And Corporate Valuation投资者保护和公司估值Rafael La Porta, Florencio Lopez-De-Silanes, Andrei Shleifer, Robert Vishny Volume 57. Issue 3June 200237) The Theory Of Capital Structure资本结构理论Milton Harris, Artur RavivVolume 46, Issue 1March 199138) The Long-Run Performance Of Initial Public Offerings首次公开发行股票的长期绩效Jay R. RitterVolume 46, Issue 1March 199139) Initial Public Offerings And Underwriter Reputation首次公开发行和承销商商誉Richard Carter, Steven ManasterVolume 45, Issue 4September 199040) Dividend Policy Under Asymmetric Information信息不对称下的股利政策Merton H. Miller, Kevin RockVolume 40, Issue 4September 198541) A Simple Implicit Measure Of The Effective Bid-Ask Spread In An Efficient Market买卖价差(Bid-Ask Spread)有效市场下有效买卖差价的简单内隐测量Richard RollSeptember 198442) Empirical Performance Of Alternative Option Pricing Models备选的期权定价模型的实证绩效Gurdip Bakshi, Charles Cao, Zhiwu ChenVolume 52, Issue 5December 199743) Compensation And Incentives: Practice vs. Theory薪酬和激励：实践和理论George P. Baker, Michael C. Jensen, Kevin J. MurphyVolume 43, Issue 3July 198844) Are Investors Reluctant To Realize Their Losses?投资者不愿意意识到他们的损失？Terrance OdeanVolume 53, Issue 5October 199845) Size And Book-To-Market Factors In Earnings And Returns盈余和收益的规模和账面-市值因素Eugene F. Fama, Kenneth R. FrenchVolume 50, Issue 1March 199546) Security Prices, Risk, And Maximal Gains From Diversification证券价格、风险和来自多元化的最大收益John LintnerVolume 20, Issue 4December 196547) An Empirical Comparison Of Alternative Models Of The Short-Term Interest-Rate对短期利率备选模型的实证比较K. C. Chan, G. Andrew Karolyi, Francis A. Longstaff, Anthony B. SandersJuly 199248) Risk Management Coordinating Corporate Investment And Financing Policies风险管理协调企业投融资政策Kenneth A. Froot, David S. Scharfstein, Jeremy C. SteinVolume 48, Issue 5December 199349) Disentangling The Incentive And Entrenchment Effects Of Large Shareholdings解析大股东激励和壕沟防御效应Stijn Claessens, Simeon Djankov, Joseph P. H. Fan, Larry H. P. Lang Volume 57, Issue 6December 200250) Valuing Corporate Securities: Some Effects Of Bond Indenture Provisions 公司证券估值：债券契约条款的一些作用Fischer Black, John C. CoxVolume 31, Issue 2May 1976。
Financial institutions and markets [学习笔记]
![Financial institutions and markets [学习笔记]](https://img.taocdn.com/s3/m/a56c67661eb91a37f1115c3d.png)
Financial institutions and markets in developing countries我们要先了解什么是Adverse Selection and Moral Hazard。
在微观经济学中，我们讨论的完全竞争模型有一个非常重要的前提，那就是假设信息的完全性，即市场的供求双方对于所交换的商品都具有充分的信息了解。
比如说，消费者知道自己的偏好，了解在什么地方，什么时候存在有何种质量的以怎样的价格出售的商品；生产者则明白自己的生产情况，了解在什么地方，什么时候存在有何种质量的以怎样的价格出售的生产要素；等等。
然而，非常显而易见的是，有关信息完全性的假设是不符合现实的。
在现实经济中，信息往往是不完全的，或者我们可以说是不对称的。
在这里，信息不对称不仅是绝对意义上的不对称，即由于认知能力的有限，人们不可能知道在任何时候，任何地方发生的或没有发生却即将发生的任何情况；而且信息不对称也指相对意义上的不对称，其市场经济本身不能够生产出足够的信息并有效地进行配置。
信息并不同于普通的商品。
人们在购买普通商品时，首先会了解它的价值，然后决定是否购买；但是对于信息商品，购买时却很难对其价值做到完全的了解。
人们之所以愿意花钱去购买信息商品，是因为还不知道这个商品是什么，一旦知道了商品，也就是知道了信息的内容，就没有人还愿意为此进行支付了。
这种情况下，就出现了一个难题：究竟卖者让不让买者在购买之前就充分了解要购买的信息的价值呢？让，购买者可能就会因为知道了信息而不再去购买；不让，购买者也可能因为不知道值不值得买而不去购买。
这时，若想买卖成功，就只能依靠双方并不十分可靠的依赖：卖者让买者充分了解信息的用处，买者则答应了解信息的用处后会购买它。
可以看出来，市场的作用受到了很大的限制。
信息不对称就是在市场交易中，当市场的一方无法观测和监督另一方的行为或无法获知另一方行动的完全信息，亦或观测和监督成本高昂时，交易双方掌握的信息所处的不对称状态。
THE JOURNAL OF FINANCE
THE JOURNAL OF FINANCE . VOL. LVII, NO. 4 . AUGUST 2002Rational Asset PricesGEE M. CONSTANTINIDES*ABSTRACTThe mean, covariability, and predictability of the return of different classes offinancial assets challenge the rational economic model for an explanation. The unconditional mean aggregate equity premium is almost seven percent per yearand remains high after adjusting downwards the sample mean premium by introducing prior beliefs about the stationarity of the price–dividend ratio and the ~non!forecastability of the long-term dividend growth and price–dividend ratio. Recognitionthat idiosyncratic ine shocks are uninsurable and concentrated in recessions contributes toward an explanation. Also borrowing constraints over the investors’life cycle that shift the stock market risk to the saving middle-aged consumers contribute toward an explanation.A central theme in finance and economics is the pursuit of a unified theoryof the rate of return across different classes of financial assets. In particular,we are interested in the mean, covariability,and predictability of the returnof financial assets. At the macro level, we study the short-term risk-freerate, the term premium of long-term bonds over the risk-free rate, and theaggregate equity premium of the stock market over the risk-free rate. Atthe micro level, we study the premium of individual stock returns and ofclasses of stocks, such as the small-capitalization versus large-capitalizationstocks, the ―value‖ versus ―growth‖ stocks, and the past losing versus winning stocks.The neoclassical rational economic model is a unified model that viewsthese premia as the reward to risk-averse investors that process informationrationally and have unambiguously defined preferences over consumption thattypically ~but not necessarily!belong to the von Neumann–Menstern class.Naturally, the theory allows for market inpleteness, market imperfections, informational asymmetries, and learning. The theory also allows fordifferences among assets for liquidity, transaction costs, tax status, and other institutional factors.The cause of much anxiety over the last quarter of a century is evidenceinterpreted as failure of the rational economic paradigm to explain the pricelevel and the rate of return of financial assets both at the macro and micro*University of Chicago and NBER. I thank John Campbell, Gene Fama, Chris Geczy, Lars Hansen, John Heaton, Rajnish Mehra, L’ubosˇ Pástor, Dick Thaler, and particularly Alon Brav and John Cochrane, for their insightful ments and constructive criticism. Finally, I thankLior Menzly for his excellent research assistance and insightful ments throughout this project. Naturally, I remain responsible for errors.1567The Journal of Financelevels. A celebrated example of such evidence, although by no means the only one, is the failure of the representative-agent rational economic paradigm to account for the large average premium of the aggregate return of stocks over short-term bonds and the small average return of short-term bonds from the last quarter of the 19th century to the present. Dubbed the ―Equity Premium Puzzle‖ by Mehra a nd Prescott ~1985!, it has generated a cottage industryof rational and behavioral explanations of the level of asset pricesand their rate of return.Another example is the large increase in stock prices in the early andmiddle 1990s, which Federal Reserve Chairman Alan Greenspan decried as “Irrational Exuberance‖ even before the unprecedented further increase in stock prices and price–dividend ratios in the late 1990s.My objective is to revisit some of this evidence and explore the extent to which the rational economic paradigm explains the price level and the rate of returnof financial assets over the past 100.years, both at the macro and micro levels.In Section I, I reexamine the statistical evidence on the size of the unconditional mean of the aggregate equity return and premium. First, I draw asharp distinction between conditional, short-term forecasts of the mean equity return and premium and estimates of the unconditional mean. I argue thatthe currently low conditional short-term forecasts of the return and premiumdo not lessen the burden on economic theory to explain the large unconditional mean equity return and premium, as measured by their sampleaverage over the past 130 years. Second, I argue that even though one may introduce one’s own strong prior beliefs and adjust downwards the sample- average estimate of the premium, the unconditional mean equity premium isat least 6 percent per year and the annual Sharpe ratio is at least 32 percent. These numbers are large and call for an economic explanation.In Section II, I discuss limitations of the current theory to explain empirical regularities. I argue that per capita consumption growth covaries toolittle with the return of most classes of financial assets and this implies thatthe observed aggregate equity return, the long-term bond return, and the observed returns of various subclasses of financial assets are too large, too variable,and too predictable.In the remaining sections, I revisit and examine the extent to which wecan explain the asset returns by relaxing the assumptions of plete consumptioninsurance, perfect markets, and time-separable preferences. As thereader will readily observe—and I offer my apologies—my choice of issues is eclectic and mirrors in part my own research interests.In Section III, I show that idiosyncratic ine shocks concentrated inperiods of economic recession play a key role in generating the mean equity premium, the low risk-free rate, and the predictability of returns. I arguethat insufficient attention has been paid to the fact that the annual aggregate labor ine exceeds annual dividends by a factor of over 20. Labor ineis by far the single most important source of household savings and consumption. The shocks to labor ine are uninsurable and persistent andarrive with greater frequency during economic contractions. IdiosyncraticRational Asset Pricesine shocks go a long way toward explaining the unconditional momentsof asset returns and the predictability of returns. The construct of per capita consumption is largely irrelevant in explaining the behavior of asset returns because idiosyncratic ine shocks are averaged out in per capita consumption.In Section IV, I show that borrowing constraints over the life cycle play an important role in simultaneously addressing the above issues and the demandfor bonds. I argue that insufficient attention has been paid to the consumers’ life cycle consumption and savings decisions in a market with borrowing constraints. These considerations are important in addressing the limited participation of consumers in the capital markets, the irrelevanceof the construct of per capita consumption, and the demand for short-term bonds by consumers with moderate risk aversion, given that equities earnon average a large premium over short-term bonds.In Section V, I discuss the role of limited market participation. In SectionVI, I discuss the role of habit persistence in addressing the same classof issues. In Section VII, I conclude that the observed asset returns do not support the case for abandoning the rational economic theory as our null hypothesis. Much more remains to be done to fully exploit the ramificationsof the rational asset-pricing paradigm.I. How Large Is the Equity Premium?The average premium of the arithmetic rate of return of the S&P positeIndex over the risk-free rate, measured over the last 130 years, isalmost 7 percent and the annual Sharpe ratio is 36 percent. If the equity premium is a stationary process, then the average premium is an unbiased estimate of the unconditional mean equity premium. One may introduceone’s own prior beliefs and shave about 1 percent off the premium. The premium and the Sharpe ratio are still large and challenge economic theory foran explanation.In Table I, I report the sample mean of the annual arithmetic aggregateequity return and of the equity premium. I proxy the aggregate equity return with the S&P posite Index return. I proxy the annual risk-free ratewith the rolled-over return on three-month Treasury bills and certificates.The reported real return is CPI-adjusted for inflation. Over the period 1872to 2000, the sample mean of the real equity return is 8.9 percent and of the premium is 6.9 percent. Over the period 1926 to 2000, the sample mean ofthe equity return is 9.7 percent and that of the premium is 9.3 percent. Overthe postwar period 1951 to 2000, the sample mean of the equity return is9.9 percent and that of the premium is 8.7 percent. These sample means are large. Siegel ~1998, 1999!, Ibbotson Associates ~2001!, Ibbotson and Chen~2001!, Dimson, Marsh, and Staunton ~2002!, Fama and French ~2002!, Mehra and Prescott ~2002!, and several others report the sample means of the equity return and premium in the United States and other countries and concludethat they are large. Some differences arise based on the proxy used for therisk-free rate.The Journal of FinanceTable IThe Equity Return and PremiumThis table shows the sample mean and standard deviation of the annualized real arithmetic return on the S&P posite Index total return series, the sample mean of the real risk-freerate, and the sample mean of the equity premium. The arithmetic rate of return on equity from the beginning to the end of year t is defined as Rt 1 .~Pt 1 .Dt 1 .Pt !0Pt , where Pt is the realprice of the aggregate equity at the beginning of year t and Dt 1 is the aggregate real dividend from the beginning to the end of year t. All returns and premia are in percent. Real returns are CPI adjusted. The table also displays the mean annual growth, ~1000T !$ln~PT 1 0XT 1!.ln~P10X1!%, of the price0X ratio, where X is the dividends, earnings, book equity, or National Ine. The pre-1926 S&P Index price series, the CPI series, the earnings series, and the dividends series are obtained from Shiller’s database. The S&P posite Index returns series post-1926 is obtained from the Ibbotson database. For years prior to 1926, the returns are calculated from the S&P 500 Index and dividend series, assuming no dividend reinvestment. The book equity series is obtained from Davis, Fama, and French ~2000!and Vuolteenaho~2000!. The National Ine is obtained from the Bureau of Labor Statistics. The risk-free rate series is the one constructed by Mehra and Prescott ~2002!and is based on an annual averagenominal return on three-month Treasury certificates and bills.1872–2000 1872–1950 1951–2000 1926–2000Sample mean S&P return 8.87 8.24 9.87 9.70Std of return 18.49 19.28 17.32 20.33Sample mean risk-free rate 2.00 2.54 1.15 0.40Sample mean premium 6.87 5.69 8.72 9.30Std of premium 19.19 20.23 17.45 20.50Sharpe ratio 0.36 0.28 0.50 0.45Mean annual growth ofPrice0dividends 1.18 0.22 3.39 1.81Price0earnings 0.71 0.57 2.73 1.28Price0book equity 1.18 0.11 3.18 2.26Price0national ine NA NA 1.27 NAI draw a sharp distinction between conditional, short-term forecasts of themean equity return and premium and estimates of the unconditional mean.The conditional forecasts of the mean equity return and premium at the endof the 20th century and the beginning of the 21st are substantially lowerthan the estimates of the unconditional mean by at least three measures.First, based on evidence that price–dividend and price–earnings ratios forecastaggregate equity returns and that the values of these ratios prevailingat the beginning of the 21st century are well above their historic averages,Campbell and Shiller ~1998!and Shiller ~2000!forecast a conditional equitypremium well below its sample average.1 Second, Claus and Thomas ~2001!1 Shiller ~1984!, Campbell and Shiller ~1988a, 1988b!, and Fama and French ~1988!provideearly evidence that the aggregate price–dividend and price–earnings ratios forecast aggregate equity returns. Goyal and Welch ~1999!argue that the out-of-sample evidence is less convincing.I do not review here the debates and extensions relating to this literature. In the following paragraphsand in Appendix A, I argue that the forecastability results provide little, if any, guidanceto my primary goal in this section, the estimation of the unconditional mean equity return.Rational Asset Pricescalculate the expected aggregate equity premium to be a little above 3 percentin the period 1985 to 1998, based on analysts’ earnings forecasts. Third,Welch ~2001!reports that the mean forecast among finance and economicsprofessors for the one-year conditional equity premium is 3.5 percent in 2001, down from 6 percent in 1997. These findings are important in their ownright and relevant in asset allocation.However, the currently low conditional, short-term forecasts of the equity premium do not necessarily imply that the unconditional estimate of themean premium is lower than the sample average. Therefore, the low conditional forecasts do not necessarily lessen the burden on economic theory toexplain the large sample average of the equity return and premium over thepast 130 years.The predictability of aggregate equity returns by the price–dividend andprice–earnings ratios raises the possibility that use of these financial ratiosmay improve upon the estimates of the unconditional mean equity return~and premium!that are based on the sample mean, an approach pursuedearlier by Fama and French ~2002!.2 Over the period 1872 to 2000, the price–dividend ratio increased by a factor of 4.6 and the price–earnings ratio by a factor of 2.5. Over the period 1926 to 2000, the price–dividend ratio increasedby a factor of 3.9 and the price–earnings ratio increased by a factorof 2.6.3 One may consider adjusting downwards the sample-mean estimate of the unconditional mean return on equity, but it is unclear by how much.The size of the adjustment ought to relate to the perceived cause of the increase of these financial ratios. In the year 1998, 52 percent of the U.S.adult population held equity either directly or indirectly, pared to 36 percentof the adult population in 1989. This equitization has been broughtabout by the increased accessibility of information on the stock market, electronic trading, the growth of mutual funds, the growth of defined-contribution pension plans, and demographic changes. Other regime shifts include the advent of the technology0media0teles ―new economy‖ and changes in the taxation of dividends and capital gains. Explanations of the price increasethat rely on economic models that are less than fully rational include cultural and psychological factors and tap into the rich and burgeoning literatureon behavioral economics and finance.4How does one process this information and adjust the sample mean estimateof the unconditional mean return and premium? To address this issue,I denote by yt [ln~Pt 0Xt !the logarithm of the ratio of the price to the2 The estimators employed in Fama and French ~2002!and in this section are discussed inAppendix A.3 The increase in these financial ratios should be interpreted with caution. The increase inthe price–dividend ratio is due in part to an increase in share repurchases and a decrease in the fraction of dividend-paying firms.4 I do not provide a systematic review of the offered explanations. Heaton and Lucas ~1999!, Shiller ~2000!, and McGrattan and Prescott ~2001!provide lucid accounts of a number of theseexplanations in the context of both rational economic models and models that deviate from full rationality.The Journal of Financenormalizing variable Xt , where the normalizing variable stands for the aggregate dividends, earnings, book equity, National Ine, or some binationof these and other economic variables.5 I choose the normalizing variable Xtin a way that I can plausibly assert that the log financial ratio is stationary.Over the sample period of length T years, the mean annual ~geometric!growthof the financial ratio Pt 0Xt is given by ~yT 1 .y1!0T. I define the adjustedestimator of the unconditional mean of the annual aggregate real equityreturn as the sample mean return, less some fraction beta of the samplemean annual growth of the financial ratio, RZSAMPLE .b~yT 1 .y1!0T.Iftheequity return and the log financial ratio are stationary processes, then the adjusted estimator is unbiased for any value of beta.6 However, the assumption of stationarity alone is insufficient to determine the value of beta.The beta of the most efficient ~mean squared error!adjusted estimator isequal to the slope coefficient of the regression of the sample mean return onthe sample mean growth of the financial ratio, ~yT 1 .y1!0T. Since I haveonly one sample ~of length T !, I cannot run such a regression and must relyon information outside the sample and0or prior beliefs about the underlying economic model. In Appendix A, I present a set of sufficient conditions that imply that the beta of the most efficient estimator within this class of adjusted estimators is equal to one, when the adjustment is based on the price–dividend ratio. In addition to stationarity, the other main conditions are thatthe price–dividend ratio does not forecast the long-run growth in dividendsand the long-run dividend growth does not forecast the price–dividend ratio. Adoption of the stationarity and ~non!forecastability conditions requires strong prior beliefs.In Table I, I report the mean annual growth of various financial ratios.Over the period 1951 to 2000, the mean annual growth of the price–dividend ratio is 3.4, the price–earnings ratio is 2.7, the price–book equity ratio is 3.2, and the price–National Ine ratio is 1.3. Even if I subtract the entiremean annual growth of the price–earnings ratio from the sample mean, the adjusted estimate of the unconditional mean premium is 6.0 percent and is large. The corresponding estimate over the 1926 to 2000 period is 8.0 percent.An alternative approach is to consider the longer sample period 1872 to2000. Over this period, the mean annual growth of the price–dividend ratioand price–earnings ratio is 1.2 percent and 0.7 percent, respectively. Thus,this type of adjustment is largely a nonissue over the full sample. Essentially,the change in the financial ratios is ―amortized‖ over 129 years andmakes little difference in the estimate. Over the full period 1872 to 2000, thesample mean equity premium is 6.9 percent and the annual Sharpe ratio is5 The ratio of the stock market value to the National Ine is discussed in Mehra ~1998!.6 A caveat is in order: Without additional assumptions, it is unclear what optimality properties ~beyond unbiasedness!are associated with this class of estimators. Neither least squares,nor maximum likelihood, nor Bayesian methods motivate this class of estimators without further assumptions.Rational Asset Prices36 percent. Any adjustment with the average growth of the financial ratiosstill leaves the unconditional mean premium large and in need of an economic explanation.II. Limitations of the Current TheoryThe neoclassical rational-expectations economic model parsimoniously linksthe returns of all assets to the per capita consumption growth through theEuler equations of consumption ~see Merton ~1973!, Rubinstein ~1976!, Lucas ~1978!, and Breeden ~1979!!. According to the theory, the risk premia of financial assets are explained by their covariance with per capita consumptiongrowth. However, per capita consumption growth covaries too little with the returns of most classes of financial assets and this creates a whole class ofasset-pricing puzzles: the aggregate equity return, the long-term bond return,and the returns of various subclasses of financial assets are too large,too variable, and too predictable. Attempts to leverage the low covariability typically backfire, implying that the observed risk-free rate is too low andhas too low variance. I discuss in some depth the aggregate equity puzzle because it exemplifies many of the problems that arise in attempting toexplain the premium of any subclass of financial assets.The covariance of the per capita consumption growth with the aggregateequity return is positive. The rational model explains why the aggregateequity premium is positive. However, the covariance is typically one order of magnitude lower than what is needed to explain the premium. Thus, theequity premium is a quantitative puzzle.7The equity premium puzzle is robust. One may address the problem bytesting the Euler equations of consumption or by calibrating the economy.Either way, it is a puzzle. In calibrating an exchange economy, the modelcannot generate the first and second unconditional moments of the equity returns. In testing and rejecting the Euler equations of consumption, one abstracts from the market clearing conditions. The rejections tell us that variations in the assumptions on the supply side of the economy do not resolve the puzzle.The challenge is a dual puzzle of the equity premium that is too high andthe risk-free rate that is too low relative to the predictions of the model. In calibrating an economy, the strategy of increasing the risk aversion coefficientin order to lever the effect of the problematic low covariance of consumption growth with equity returns increases the predicted risk-free rate7 Grossman and Shiller ~1981!, Hansen and Singleton ~1982!, Ferson and Constantinides ~1991!, Hansen and Jagannathan ~1991!, and many others test and reject the Euler equations of consumption. Mehra and Prescott ~1985!calibrate an economy to match the process of consumptiongrowth. They demonstrate that the unconditional mean annual premium of the aggregate equity return over the risk-free rate is, at most, 0.35 percent. This is too low, no matterhow one estimates the unconditional mean equity premium. Weil ~1989!stresses that the puzzleis a dual puzzle of the observed too high equity return and too low risk-free rate.The Journal of Financeand aggravates the risk-free-rate puzzle. In testing the Euler equations ofconsumption, the rejections are strongest when the risk-free rate is includedin the set of test assets.Several generalizations of essential features of the model have been proposedto mitigate its poor performance. They include alternative assumptionson preferences,8 modified probability distributions to admit rare butdisastrous market-wide events,9 inplete markets,10 and market imperfections.11 They also include a better understanding of data problems suchas limited participation of consumers in the stock market,12 temporal aggregation,13 and the survival bias of the U.S. capital market.14 Many of thesegeneralizations contribute in part toward our better understanding of theeconomic mechanism that determines the pricing of assets. I refer the readerto the excellent reviews in the textbooks by Campbell, Lo, and MacKinlay~1997!and Cochrane ~2001!, and in the articles by Cochrane and Hansen~1992!, Kocherlakota ~1996!, Cochrane ~1997!, Campbell ~2001, 2002!, andMehra and Prescott ~2002!.III. Idiosyncratic Ine Shocks and Inplete MarketsA. The Role of Idiosyncratic Ine ShocksIn economic recessions, investors are exposed to the double hazard of stockmarket losses and job loss. Investment in equities not only fails to hedge therisk of job loss but also accentuates its implications. Investors require ahefty equity premium in order to be induced to hold equities. In sum, this isthe argument that I formalize below and address the predictability of assetreturns and their unconditional moments.The observed correlation of per capita consumption growth with stock returnsis low. Over the years, I have grown skeptical of how meaningful aneconomic construct aggregate ~as opposed to disaggregate!consumption is,8 For example, Abel ~1990!, Constantinides ~1990!, Epstein and Zin ~1991!, Ferson and Constantinides~1991!, Benartzi and Thaler ~1995!, Campbell and Cochrane ~1999!, Anderson, Hansen,and Sargent ~2000!, Bansal and Yaron ~2000!, and Boldrin, Christiano, and Fisher ~2001!.9 The merits of this explanation are discussed in Mehra and Prescott ~1988!and Rietz ~1988!.10 For example, Bewley ~1982!, Mehra and Prescott ~1985!, Mankiw ~1986!, Constantinides and Duffie ~1996!, Heaton and Lucas ~1996!, Storesletten, Telmer, and Yaron ~2001!, Brav, Constantinides,and Geczy ~2002!, and Krebs ~2002!.11 For example, Aiyagari and Gertler ~1991!, Danthine, Donaldson, and Mehra ~1992!,Heand Modest ~1995!, Bansal and Coleman ~1996!, Heaton and Lucas ~1996!, Daniel and Marshall ~1997!, and Constantinides, Donaldson, and Mehra ~2002a!.12 Mankiw and Zeldes ~1991!, Brav and Geczy ~1995!, Attanasio, Banks, and Tanner ~2002!, Brav et al. ~2002!, and Vissing-Jensen ~2002!.13 Heaton ~1995!, Lynch ~1996!, and Gabaix and Laibson ~2001!.14 See Brown, Goetzmann, and Ross ~1995!. However, Jorion and Goetzmann ~1999, Table 6! find that the average real capital gain rate of a U.S. equities index exceeds the average rate ofa global equities index that includes both markets that have and have not survived by merelyone percent per year.Rational Asset Pricesand how hard we should push aggregate or per capita consumption to explain returns. At a theoretical level, aggregate consumption is a meaningfuleconomic construct if the market is plete or effectively so.15 In a pletemarket, heterogeneous households are able to equalize, state by state,their marginal rate of substitution. The equilibrium in a heterogeneous-household, full-information economy is isomorphic in its pricing implicationsto the equilibrium in a representative-household, full-information economy,if households have von Neumann–Menstern preferences.16 The strong assumptionof market pleteness is indirectly built into asset pricing modelsin finance and neoclassical macroeconomic models through the assumptionof the existence of a representative household.Bewley ~1982!, Mehra and Prescott ~1985!, and Mankiw ~1986!suggest thepotential of enriching the asset-pricing implications of the representative-household paradigm, by relaxing the assumption of plete markets.17 Constantinides and Duffie ~1996!find that inplete markets substantiallyenrich the implications of the representative-household model. Their mainresult is a proposition demonstrating, by construction, the existence of householdine processes, consistent with given aggregate ine and dividendprocesses, such that equilibrium equity and bond price processes match thegiven equity and bond price processes.The theory requires that the idiosyncratic ine shocks must have threeproperties in order to explain the returns on financial assets. First, theymust be uninsurable. If the ine shocks can be insured, then the household consumption growth is equal, state by state, to the aggregate consumptiongrowth, and household consumption growth cannot do better thanaggregate consumption growth in explaining the returns. Second, the ineshocks must be persistent. If the shocks are transient, then householdscan smooth their consumption by borrowing or by drawing down their savings.18 Third, the ine shocks must be heteroscedastic, with countercyclicalconditional variance.A good example of a major uninsurable ine shock is job loss. Job lossis uninsurable because unemployment pensation is inadequate. Layoffshave persistent implications on household ine, even though the laid-off15 The market is effectively plete when all households have preferences that imply one- fund or two-fund separation.。
选题的目的和意义
---------------------------------------------------------------最新资料推荐------------------------------------------------------选题的目的和意义一、选题的目的和意义现代公司制度的显著特征之一是两权分离，兼得资本聚集和专业化管理的优势。
但是,这种优势是有代价的,即公司股东与公司管理层之间的委托代理关系带来的激励不相容。
从股东一方来看,股东把公司看成是一种投资工具,以投入公司的资本承担风险,期望经理能够为实现股东利益最大化而勤勉工作。
从管理层一方来看,管理层将公司作为领取报酬、额外奖赏和实现自我价值的场所,以自身利益的最大化为目的。
因此，产生了由二者利益冲突导致的激励不相容。
股权激励是一种以公司股票为标的，对公司的董事、高级管理人员及、骨干员工及其他人员进行的长期性激励机制。
通过股权激励，被激励者能够以股东身份参与企业决策﹑分享利润﹑承担风险，从而勤勉尽责地为公司的长期发展服务，以解决管理层和股东利益冲突问题。
股权激励制度产生于 20 世纪 50 年代的美国， 1952 年，辉瑞（pfizer）公司于率先推出股票期权。
从此以后，以股票期权为代表的股权激励制度在赢得世界上各大企业集团的青睐。
近代西方股权激励理论源于公司治理理论和人力资源管理理论在实践中的有机结合。
1 / 13一方面，股权激励是为了解决企业委托代理问题，通过股权激励使代理人和委托人的利益最大程度地达成一致，促使代理人切实关注企业长期发展和股东的利益，充分发挥其主观能动性，从而降低企业代理成本。
另一方面，股权激励属于薪酬激励范畴，属于薪酬结构中的长期激励部分。
其激励对象为企业核心人员，尤其是高层管理者。
其目的是吸引并激励核心人才为企业长期战略目标努力。
现代企业理论和国外实践证明，规范的股权激励对于改善公司治理结构，降低代理成本，提升管理效率，增强公司凝聚力和市场竞争力起到非常积极的作用，与公司管理者实现了双赢的结果。
Noninterest income and financial performance at US commercial banks
The Financial Review39(2004)101--127Noninterest Income and Financial Performance at mercial BanksRobert DeYoungFederal Reserve Bank of ChicagoTara Rice∗Federal Reserve Bank of ChicagoAbstractNoninterest income now accounts for over40%of operating income in the -mercial banking industry.This paper demonstrates a number of empirical links between bank noninterest income,business strategies,market conditions,technological change,and financial performance between1989and2001.The results indicate that well-managed banks expand more slowly into noninterest activities,and that marginal increases in noninterest income are associated with poorer risk-return tradeoffs on average.These findings suggest that noninter-est income is coexisting with,rather than replacing,interest income from the intermediation activities that remain banks’core financial services function.Keywords:banks,noninterest income,deregulationJEL Classifications:G21,G28∗Corresponding author:Economist,Department of Bank Supervision and Regulation,Federal Re-serve Bank of Chicago,230South LaSalle Street,Chicago,IL60604;Phone:(312)322-5274;E-mail: tara.rice@.The views expressed herein are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Chicago or the Federal Reserve System.The authors thank Phil Bartholomew,Steven Dennis,Gerry Hanweck,Iftekhar Hasan,Cathy Lemieux,Tom Lutton,Larry Wall,and an anonymous reviewer for their help,comments,and encouragement,and Jennifer Blair for expert research assistance.101102R.DeYoung and T.Rice/The Financial Review39(2004)101–1271.IntroductionA number of theories have been advanced to explain why banks,and more gen-erally financial intermediaries,exist.In most of these theories,banks exist because they mitigate a host of problems that otherwise prevent liquidity from flowing di-rectly from agents with excess liquidity(depositors)to agents in need of liquidity (borrowers).These problems arise because of informational asymmetries,contract-ing costs,and scale mismatches between liquidity suppliers and liquidity demanders. Intermediation-based theories of financial institutions see banks as the solution to these problems,because:banks have a comparative advantage at gathering informa-tion on borrower creditworthiness;banks are better able than individual lenders to monitor borrowers;banks provide increased liquidity by pooling funds from many households and businesses and by issuing demandable deposits in exchange for these funds;and banks diversify away idiosyncratic credit risk by holding portfolios of multiple loans.1Much of the empirical literature in commercial banking has followed these rich theoretical leads,analyzing the financial flows fundamental to the intermediation process(e.g.,interest paid on deposits,interest received from loans and securities, and the resulting net interest margins)and the risks associated with those flows (e.g.,liquidity risk associated with deposits,credit risk associated with loans,market risk associated with fixed income securities,and interest-rate risk associated with the relative maturities of deposits,loans,and securities).However,commercial bank business models have evolved over the past two decades,and today banks generate an increased portion of their income from nonintermediation and/or noninterest activi-ties.For example,between1980and2001,noninterest income in the mercial banking system increased from0.77%to2.39%of aggregate banking industry as-sets,and increased from20.31%to42.20%of aggregate banking industry operating income.The increasing presence of noninterest income at commercial banks has been widely documented and discussed in the industry press and regulatory publications (for example,Feldman and Schmidt,1999),but only a few academic studies have investigated the impact of increased noninterest income on the financial performance of commercial banks.While it is well known that large banks and banks with spe-cialized strategies(e.g.,credit card banks,mortgage banks)rely more heavily on noninterest income than do small banks with traditional business strategies,there is little systematic understanding of why noninterest income varies across banks and how noninterest income is associated with bank financial performance.1Seminal theoretical studies in this area include Gurley and Shaw(1960),Pyle(1971),Benston and Smith (1976),Leland and Pyle(1977),Fama(1980),Diamond and Dybvig(1983),Diamond(1984),Boyd and Prescott(1986),James(1987),and Gorton and Pennacchi(1990).See Saunders(2000,chapter6)and Freixas and Rochet(1999,chapter2)for general discussions of why banks exist and overviews of the theoretical literature.R.DeYoung and T.Rice/The Financial Review39(2004)101–127103 This paper attempts to fill in some of these gaps.In Section2we document the long-run trends in the amount and composition of noninterest income at U.S. commercial banks.In Section3we discuss the regulatory and technological deter-minants of noninterest income at commercial banks,and consider why noninterest income has grown more quickly at some banks than at others.In Section4we discuss the potential effects of increased noninterest income on the financial performance of commercial banks.We refer to the existing literature on noninterest income at commercial banks throughout each of these first three sections.In Section5we specify an econometric model designed to answer two broad questions:Which bank characteristics,market conditions,and technological developments are most closely associated with increased noninterest income?Is noninterest income associated with improvements or declines in bank financial performance?In Section6we describe the1989–2001panel data set on mercial banks that we use to estimate the econometric model.We report the results of our econometric model in Section7.We find numerous strong statistical associations between noninterest income and bank characteristics, market conditions,technological progress,and bank performance.For example,our results suggest that well-managed banks rely relatively less on noninterest income; that banks that stress customer relationships and service quality tend to generate more noninterest income;and that the development of new financial technologies such as cashless transactions and mutual funds are associated with higher levels of noninterest income in the banking system.We also find that increases in noninterest income tend to be associated with higher profitability,higher variation in profits,and a worsened risk-return tradeoff for the average commercial bank during this time period.These results are consistent with previous research findings,extend our knowledge beyond the small existing literature on this topic,and are robust to changes in estimation technique and data subsampling.In Section8we briefly discuss the implications of our results for the future roles of intermediation and nonintermediation activities in bank business models.2.The changing sources of bank incomeThere are a number of different ways to measure the incidence of noninter-est income at commercial banks.Table1illustrates how two of those measures—noninterest income as a percentage of bank assets,and noninterest income as a percentage of bank operating income—have increased over time for“large”(assets greater than$1billion)and“small”(assets less than$1billion)mercial banks ing operating income as the financial benchmark suggests a relatively small increase over time:noninterest income increased by17%on aver-age at large banks(from25.47%to29.89%of operating income)and increased by 16%on average at small banks(from14.07%to16.38%of operating income).Using total assets as the financial benchmark indicates a substantially larger increase over time:noninterest income increased by79%on average at large banks(from1.20%104R.DeYoung and T.Rice/The Financial Review 39(2004)101–127T a b l e 1A v e r a g e i n c i d e n c e a n d c o m p o s i t i o n o f n o n -i n t e r e s t i n c o m e a t U .S .c o m m e r c i a l b a n k s ,1984–2001.A v e r a g e s f o r l a r g e r b a n k s A v e r a g e s f o r s m a l l e r b a n k s I n d u s t r y a g g r e g a t e s(a s s e t s >$1b i l l i o n i n 2001d o l l a r s )(a s s e t s <$1b i l l i o n i n 2001d o l l a r s )N o n i n t e r e s t i n c o m eN o n i n t e r e s t i n c o m eC o m p o s i t i o n o f N o n i n t e r e s t i n c o m e C o m p o s i t i o n o f n o n i n t e r e s t i n c o m en o n i n t e r e s t i n c o m ea s %o f a s %o f a s %o f a s %o f o p e r a t i n g a s %o f o p e r a t i n g S e r v i c e F i d u c i a r y a s %o f o p e r a t i n g S e r v i c e F i d u c i a r y a s s e t si n c o m ea s s e t si n c o m ec h a r g e s I n c o m e O t h e ra s s e t s i n c o m e c h a r g e sI n c o m eO t h e r20012.39%42.20%2.15%29.89%.3189.1146.56660.91%16.38%.5921.0297.378220002.46%42.93%1.97%28.09%.3251.1269.54790.90%15.36%.5959.0254.378719992.52%42.92%2.05%29.86%.3095.1367.55380.91%15.47%.5851.0255.389419982.27%40.36%2.19%29.82%.3037.1520.54430.91%15.39%.5846.0248.390619972.08%37.45%1.83%27.49%.3207.1577.52160.96%15.11%.5995.0250.375519962.04%36.50%1.84%27.87%.3254.1651.50960.94%15.36%.5999.0247.375419951.91%34.83%1.76%27.95%.3211.1631.51590.91%15.10%.6086.0255.366119941.90%34.23%1.81%28.08%.3577.1722.47010.94%15.30%.6075.0250.367419932.02%34.98%1.87%28.97%.3246.1681.50730.96%15.87%.5999.0248.375419921.87%32.98%1.85%28.76%.3258.1696.50420.89%15.51%.6007.0251.374219911.74%32.89%1.72%28.85%.3125.1749.51210.86%15.89%.6101.0252.364719901.62%32.21%1.55%27.64%.3082.2186.47310.81%15.39%.6063.0262.367519891.54%31.21%1.41%26.80%.3093.1932.49750.81%15.11%.5918.0261.382119881.44%29.54%1.37%25.86%.3080.1914.50060.77%14.85%.5900.0256.384419871.38%29.34%1.31%25.71%.2992.2041.49670.75%14.72%.5601.0242.415719861.22%27.43%1.24%26.21%.2925.2093.49820.72%14.56%.5803.0228.397019851.14%25.46%1.21%25.36%.3003.2134.48630.73%13.94%.5830.0219.395119841.06%24.60%1.20%25.47%.2866.2211.49220.72%14.07%.5765.0203.4031N o t e :O p e r a t i n g I n c o m e =I n t e r e s t I n c o m e +N o n -i n t e r e s t I n c o m e −I n t e r e s t E x p e n s e .R.DeYoung and T.Rice/The Financial Review 39(2004)101–127105Correlation of ROE and Net Interest Margin-0.100.000.100.200.300.40198419861988199019921994199619982000Figure 1Average annual cross-sectional correlations between commercial bank return-on-equity and commercial bank net interest margin.OLS trend lines are superimposed over each series of correlations.to 2.15%of assets)and increased by 26%on average at small banks (from 0.72%to 0.91%of assets).Finally,using industry aggregates rather than bank averages sug-gests still larger increases over time:industry noninterest income-to-operating income increased by 72%(from 24.60%to 42.20%of aggregate industry operating income)and industry noninterest income-to-assets increased by 125%(from 1.06%to 2.39%of aggregate industry assets).These figures illustrate several important points.First,noninterest income com-prises a larger portion of commercial bank income today than in 1984.This is not just a U.S.phenomenon:Kaufman and Mote (1994)find that noninterest income ratios increased in the banking sectors of virtually all developed countries between 1982and 1990.Second,noninterest income ratios are larger,and have grown more quickly over time,at large banks than at small banks.Third,the large industry aggregate ratios indicate that the lion ’s share of total noninterest income is being generated by a small number of banks.Indeed,the 1%of banks with the highest ratios of noninter-est income-to-assets accounted for almost 18%of all noninterest income in the mercial banking sector in 2001.The across-the-board growth of noninterest income at commercial banks sug-gests that intermediation activities are becoming a less important part of banking busi-ness strategies.The data displayed in Figure 1suggest otherwise.If intermediation106R.DeYoung and T.Rice/The Financial Review39(2004)101–127activities have become less important for banks over time,it stands to reason that the correlation between bank profitability and bank net interest margin would grow weaker over time.Figure1,which displays the average correlation of ROE and net interest margin each year between1984and2001,shows no such weakening.Al-though these data are crude and exhibit substantial noise over time,they suggest an intriguing possibility:increased noninterest income is coexisting with,rather than replacing,intermediation activities at the typical commercial bank.Table1also shows how the composition of noninterest income has changed over time.At large banks,service charges on deposit accounts have comprised a relatively stable portion of total noninterest income,fluctuating between about29%and36% and following no trend over time.Fee income from fiduciary activities has fallen by approximately half,from about22%to about11%,and may reflect the gradual movement of trust and investment departments out of commercial bank affiliates and into separate securities affiliates.“Other”noninterest income has increased from about49%to about57%;note that most of this increase occurred in the final years of the sample after rulings by federal regulators and industry deregulation allowed banks expanded product powers.In contrast,the composition of noninterest income at small banks has remained remarkably unchanged since1984.3.The regulatory,technological,and strategicdrivers of noninterest incomeOver the past two decades,the banking industry has been transformed by sweep-ing deregulation and rapid technological advances in information flows,commu-nications infrastructure,and financial markets.Deregulation fostered competition between banks,nonbanks,and financial markets where none existed before.In re-sponse to these competitive threats and opportunities,many banks embraced the new technologies that drastically altered their production and distribution strategies and resulted in large increases in noninterest income.In contrast,many other banks have continued to use traditional banking strategies for which noninterest income remains relatively less important.Banking industry deregulation removed a whole host of restrictions that had stunted the evolution of the banking industry,constrained the efficiency of financial product markets,and extended the lives of thousands of poorly run and/or suboptimal-sized commercial banks.First,the phase-out of Regulation Q interest rate ceilings allowed banks to pay market rates of interest to depositors.Banks gradually abandoned bundled pricing of retail deposit products—in which they compensated depositors for below-market interest rates by providing a“bundle”of products free of charge(e.g., check printing,safety deposit boxes,travelers checks)—in favor of explicit fees for individual retail deposit products.2Second,two decades of deregulation at the state2For evidence that fees charged on deposit accounts and other depositor services have increased over time,R.DeYoung and T.Rice/The Financial Review39(2004)101–127107 level,culminating with the Riegle-Neal Act of1994,eliminated barriers to expansion across state boundaries.Banking companies embraced this new freedom by acquiring banks in other states,by converting multiple bank charters into bank branches,and in rare cases by opening de novo branches in other states.The most geographically expansive banks grew large enough to profitably employ high-volume,automated lending technologies based on credit scoring and securitization—a business model that generates large amounts of noninterest income.Third,the Gramm-Leach-Bliley Act of1999allowed banks to expand further into financial services activities unrelated to traditional bank rge banking companies took quick advantage of this legislation to expand into nontraditional activities that generated noninterest income(e.g.,securities underwriting,insurance sales,retail brokerage).3 Advances in information and communications technology(e.g.,the Internet, ATMs),new intermediation technologies(e.g.,loan securitizations,credit scoring), and the introduction and expansion of financial instruments and markets(high-yield bonds,commercial paper,financial derivatives)all would have occurred in the ab-sence of deregulation.But deregulation allowed banks to achieve the scale to use these new technologies more efficiently,and the increased competition induced by deregulation provided banks with the incentives to adopt and adapt these new tech-nologies.Many of these new technologies have emphasized noninterest income while de-emphasizing interest income at banks.Banks can extract fee income from cus-tomers willing to pay a“convenience premium”for doing their banking at ATMs or over the Internet.Banks can earn loan origination,loan securitization,and loan servicing fees to offset the interest income that they lost with the disintermediation of consumer lending(e.g.,mortgages,credit cards).Banks can earn fees from selling backup lines of credit to firms that float commercial paper rather than borrowing from banks.By most accounts,deregulation and technological advances have fostered in-creased competitive rivalry among banks and nonbanks alike.Banks have faced in-creased competition in retail markets due to deregulation(e.g.,the Riegle-Neal Act), financial innovation(e.g.,mutual funds),and advances in communications technol-ogy(e.g.,online brokerage accounts),all of which have provided banks’retail cus-tomers with alternatives to traditional bank deposit accounts.Banks have also faced see Board of Governors of the Federal Reserve,“Annual Report to Congress on Retail Fees and Services of Depository Institutions,”June1997through June2002.3Kane(1996)and Kroszner and Strahan(1997,1999)argue that banks were routinely circumventing regulatory constraints on geographic and product market expansion years prior to deregulation,and that deregulation occurred because the relative cost of maintaining the restrictions to one interest group became less than the relative benefit to other interest groups.Indeed,Gramm-Leach-Bliley was preceded by a series of federal regulatory rulings that incrementally relaxed restrictions on banking powers.For example, during the1990s the Office of the Comptroller of the Currency granted national banks to power to sell insurance from offices in small towns,and the Federal Reserve relaxed the limitations on the amount of revenue a bank could generate in its Section20securities subsidiaries.108R.DeYoung and T.Rice/The Financial Review39(2004)101–127 increased competition in wholesale markets,due to increasingly deeper and more ef-ficient financial markets(e.g.,high-yield commercial debt,commercial paper,equity finance)which have provided banks’business customers with alternatives to tra-ditional bank loans.Well-managed banks responded to these competitive pressures by becoming more cost-efficient and more revenue-efficient.This included offering customers an expanded array of new and/or nontraditional fee-based products,selling increased amounts of existing fee-based products,pricing fee-based products more efficiently(e.g.,by unbundling retail deposit products),and improving the quality of fee-based products and services so that they commanded higher prices.Numerous studies have documented the response of local banks to out-of-state entry(Berger, Bonime,Goldberg,and White,forthcoming,2004;Berger,Goldberg,and White, 2001;Berger,Saunders,Scalise,and Udell,1998;DeYoung,Hasan,and Kirchhoff, 1998;Evanoff and Ors,2001;Keeton,2000;and Whalen,2001).There is emerging evidence that commercial banks are gravitating toward two di-vergent banking strategies in which noninterest income plays different roles.DeYoung and Hunter(2003)and DeYoung,Hunter,and Udell(2004)argue that two generic banking strategies are emerging from the fog of deregulation and technological change.In the first of these two strategies,large banks take advantage of economies of scale in the production,marketing,securitization,and servicing of consumer loans. Although these banks operate with very low unit costs,they tend to earn very low interest margins because the products they produce are essentially financial commodi-ties,and the markets they sell them into are extremely rge amounts of noninterest income(e.g.,from origination,securitization,and servicing fees)are essential for this model to be profitable.In the second of the two strategies,small com-munity banks operating in local markets develop relationships with their depositors and their borrowers.They add value to their depositor relationships through person-to-person contact at branch offices,and they make loans to informationally opaque, small,idiosyncratic borrowers who do not have direct access to financial markets. Although these small,locally-focused banks operate with relatively high unit costs, they can earn market returns because they earn high interest margins—they pay low interest rates to a loyal base of low-cost core depositors,and they charge high interest rates to borrowers over which they have market power(i.e.,high switching costs). Noninterest income is less important for these banks,although at the margin these banks’attention to high levels of service quality will command higher fees for any given product.The data in Table1are consistent with this large bank/small bank strategic dichotomy.4.Noninterest income andfinancial performanceThe consequences of noninterest income for the financial performance of com-mercial banks are not well understood.All else equal,an increase in noninterest income will improve earnings—but an increase in noninterest income seldom occurs without concomitant changes in interest income,variable inputs,fixed inputs,and/orR.DeYoung and T.Rice/The Financial Review39(2004)101–127109 financing structure.4As noninterest income trended up during the1990s,it was gen-erally believed that shifting banks’income away from intermediation-based activities (in which bank income was subject to credit-risk and interest rate risk),and toward fee-based financial products and services,would reduce banks’income volatility. Moreover,it was conventionally believed that expansion into new fee-based prod-ucts and services reduced earnings volatility via diversification effects.But recent empirical studies indicate that neither of these beliefs holds on average.DeYoung and Roland(2001)suggest three reasons why noninterest income may increase the volatility of bank earnings.First,most bank loans are relationship based and as a result have high switching costs,while most fee-based activities are not relationship based.Thus,despite credit risk and fluctuations in interest rates,interest income from loans may be less volatile than noninterest income from fee-based ac-tivities.Second,within the context of an ongoing lending relationship,the main input needed to produce more loans is variable(interest expense);in contrast,the main input needed to produce more fee-based products is typically fixed or quasi-fixed (labor expense).Thus,fee-based activities may require greater operating leverage than lending activities,which makes bank earnings more vulnerable to declines in bank revenues.Third,most fee-based activities require banks to hold little or no fixed assets,so unlike interest-based activities like portfolio lending,fee-based activities like trust services,mutual fund sales,and cash management require little or no regu-latory capital.Thus,fee-based activities likely employ greater financial leverage than lending ing data from U.S.banks during the1990s,the authors demon-strate that three traditional streams of income from intermediation activities—interest from loans,interest from securities,and service charges from deposits—were all less volatile than income from fee-based activities.Stiroh(forthcoming,a)finds that increased focus on noninterest activities at mercial banks is associated with declines in risk-adjusted performance.In a second study,Stiroh(forthcoming,b)finds potential diversification benefits within broad lines of banking business(e.g.,diversifying across different types of loans,or diversifying across different sources of fee-based income),but finds little potential for diversification benefits across broad lines of banking business.Staikouras and Wood(2003)investigate the diversification effects of noninterest income at banks in 15different European countries.While they also conclude that noninterest income is more volatile than interest income over time,they find negative correlations between these two income streams,which leads them to conclude(in contrast to the U.S. studies)that noninterest income tends to stabilize bank earnings.Structural and reg-ulatory differences may explain why these findings for European banks are different 4There are some narrow exceptions to this statement.For example,an exogenous increase in market power would allow a bank to increase its fees,thereby increasing its noninterest income without having to make any operational changes.Similarly,an exogenous improvement in bank management could result in more efficient pricing of existing fee-based products and services.110R.DeYoung and T.Rice/The Financial Review39(2004)101–127from the findings for U.S.banks.Fee-based services are relatively new to many U.S. banks,and thousands of small community banks lack the size and expertise to engage in many of these activities.In contrast,universal banking has been the historic norm in many European banking systems and small community banks are less prevalent. It is possible that this combination of experience,size,and expertise could allow the average European bank to better exploit the diversification potential of fee-based activities.Additional studies are necessary before such a conclusion could be drawn with any confidence,however.All else equal,an efficient bank should generate higher amounts of noninterest income.For example,a well-managed bank will set its fees to fully exploit market demand,and will cross-sell additional fee-based products to a larger percentage of its core customer base.Thus,holding product mix and banking strategy constant,the intensity of noninterest income is likely to be a forward-looking signal of a bank’s financial success.Surprisingly,little work has been done on this potential relation-ship between management quality,bank earnings,and noninterest income.DeYoung (1994)shows that cost-efficient commercial banks generate more noninterest income, but does not explore the causal relationship between these variables.Rogers(1998) finds similar results for profit-efficient commercial banks.5.Empirical modelThe available evidence indicates that noninterest income and financial perfor-mance are interrelated.Banks with large amounts of noninterest income have been shown to suffer declines in risk-adjusted performance,ceteris paribus,while banks with high-quality management(which is reflected in risk-adjusted performance) should be better at generating noninterest income,ceteris paribus.Our econometric model recognizes these interrelationships.The first equation in our model attempts to identify the bank characteristics,market conditions,and technological developments most closely associated with noninterest income:NIIRATIO t,i=a+b∗RELROE t,i+c∗CORERATIO t,i+d∗LOANRATIO t,i +f∗RESHARE t,i+g∗C&ISHARE t,i+h∗FTERATIO t,i+k∗lnASSETS t,i+m∗MBHC t,i+n∗GROWTH t,i+p∗CCBANK t,i+q∗SECTION20BANK t,i+r∗MKTHERF t,i+s∗TECHNOLOGY t+t∗JOBGROWTH i,t+u∗FOREIGN t,i+v∗TIME+w∗STATE+εt,i(1) where the subscripts i and t index banks and years,respectively.The dependent variable in equation(1)is the ratio of noninterest income-to-assets(NIIRATIO). We construct four different versions of NIIRATIO based on different definitions of noninterest income:NIIRATIO1=total noninterest income/assets;NIIRATIO2= (noninterest income generated from service charges on deposit accounts)/assets;。
解读财经素养必备名词,打造财务管理的专业知识体系
解读财经素养必备名词，打造财务管理的专业知识体系1. Financial literacy: Financial literacy refers to the knowledge and understanding of various financial concepts and skills, such as budgeting, saving, investing, and managing debt. It is the ability to make informed decisions regarding personal finance.2. Compound interest: Compound interest is the interest earned on both the initial principal amount and any accumulated interest from previous periods. It is calculated by adding the interest earned to the principal amount, and then calculating interest on the new total.3. Stock market: The stock market is a platform where buyers and sellers trade shares of publicly traded companies. It is a marketplace for investors to buy and sell stocks, bonds, and other securities.4. Inflation: Inflation is the rate at which the general level of prices for goods and services is rising, and subsequently, purchasing power is falling. It is measured by the Consumer PriceIndex (CPI) and can have a significant impact on the economy and personal finances.5. Credit score: A credit score is a numerical representation of an individual's creditworthiness. It is used by lenders to determine the likelihood of a borrower repaying their debts. A higher credit score indicates a lower risk borrower.中文回答：1. 财经素养：财经素养指的是对各种财经概念和技能的知识和理解，如预算、储蓄、投资和债务管理。
生产、信息费用与经济组织(中英文)
06.Production, Information Costs and Economic Organization生产、信息费用与经济组织A．A．阿尔钦H．登姆塞茨The mark of a capitalistic society is that resources are owned and allocated by such nongovernmental organizations as firms, households, and markets. 资本主义社会的标志是资源由一些非政府组织如企业、家庭、市场所有和配置。
Resource owners increase productivity through cooperative specialization and this leads to the demand for economic organizations which facilitate cooperation.资源的所有者通过专业化的协作来提高生产率，由此产生了对那种能促进合作的经济组织的需求。
When a lumber mill employs a cabinetmaker, cooperation between specialists is achieved within a firm, and when a cabinetmaker purchases wood from a lumberman, the cooperation takes place across markets (or between firms).一家木材加工厂雇佣一位木工时，专业化合作是在一个企业内部达成的，而当一位木匠从伐木工那儿购买木料时，合作则是通过市场（或企业之间）来实现的。
Two important problems face a theory of economic organization to explain the conditions that determine whether the gains from specialization and cooperative production can better be obtained within an organization like the firm, or across markets, and to explain the structure of the organization.当经济组织理论必须正视两个重要的问题——解释1）哪些条件决定了，在组织内部（企业）进行专业化及合作生产，比通过市场进行生产的收益更好；2）这种组织的结构It is common to see the firm characterized by the power to settle issues by fiat, by authority, or by disciplinary action superior to that available in the conventional market. 一般认为，企业的特点能够是以优于普通的市场的力量来解决问题（如命令、权威或纪律化行为）。
LP模型中文版
INFORMATIONAL ASYMMETRIES, FINANCIAL STRUCTURE, ANDFINANCIAL INTERMEDIATION信息不对称、融资结构和金融中介HAYNE E. LELAND AND DA VID H. PYLE**INTRODUCTION AND SUMMARYNUMEROUS MARKETS ARE characterized by informational differences between buyers and sellers. In financial markets, informational asymmetries are particularly pronounced. Borrowers typically know their collateral, industriousness, and moral rectitude better than do lenders; entrepreneurs possess "inside" information about their own projects for which they seek financing. 买卖双方之间的信息不对称存在于许多市场。
在金融市场中，信息不对称表现得尤为明显。
借款人通常比贷款人更为了解他们的抵押品、能力及品德；企业家拥有他们寻求融资的项目的“内部”信息。
Lenders would benefit from knowing the true characteristics of borrowers. But moral hazard hampers the direct transfer of information between market participants. Borrowers cannot be expected to be entirely straightforward about their characteristics, nor entrepreneurs about their projects, since there may be substantial rewards for exaggerating positive qualities. And verification of true characteristics by outside parties may be costly or impossible. 贷款人将从了解借款人的真实特征中受益。
90试论信息不对称理论在公司财务中的应用
[收稿日期]20040628[作者简介]赵珊(1972— ),女,山东临沂人,南京审计学院审计系讲师,南京农业大学博士研究生,主要从事会计、审计、农业经济管理研究。
第1卷 第3期2004年8月南京审计学院学报Journal of Nanjing Audit UniversityVol.1,No.3Aug.,2004试论信息不对称理论在公司财务中的应用赵 珊,薛 野(南京审计学院审计系,江苏南京 210029)[摘 要]经典财务理论大厦构建于信息的对称性假设基础之上。
然而现实世界中信息不对称现象几乎涉及每个领域。
本文结合国内外已有的研究成果对信息不对称前提下公司的财务理论与政策进行了分析与评价。
[关键词]公司财务;财务政策;不对称信息[中图分类号]F224.13 [文献标识码]A [文章编号]16728750(2004)03001003 经典财务理论的一个重要基础是“完美市场”假设。
在“完美市场”中,无论是投资者之间,还是投资者与管理者之间都不存在信息差异,信息的分布和流通速度是均匀的,且信息的获得是无成本的。
纵观经典财务理论的诸多领域,我们可以发现,这种信息的对称性假设无疑起到了删繁就简、突出主旨的作用,推动了财务理论的发展。
但经典财务理论因为构建于太多的理论假设条件之下,且实证支持不足,难以解释企业现实财务问题。
20世纪70年代现代西方经济学中引入不对称信息理论。
新理论的提出为财务学界进一步深入研究财务问题拓宽了视野。
在信息不对称的前提下,如何重新审视公司的财务理论与政策?本文拟结合国内外已有的研究成果就以下几个方面进行分析与评价。
一、资本市场中的“逆向选择”关于资本市场中的“逆向选择”最早的应用研究是由迈耶斯和马吉鲁夫(1984)做出的。
假设有若干家公司需要在资本市场中筹资。
不同的公司具有不同的盈利性和成长性,也即公司之间存在价值(质量)差别。
公司对自身的质量当然有着完全的信息,而潜在的投资者却无法区分不同质量的公司。