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Pearson LCCI Level 3 商业统计学指南说明书

Pearson LCCI Level 3 Certificate in Business Statistics (ASE20100) Reading and resource suggestions (Extracted from the Teacher’s Delivery Guide)Chapter 6Further reading and resource suggestionsText books that cover all aspects of the syllabuscation.Pearson LCCI Level 3 Certificate in Business Statistics (ASE20100): Teacher’s Delivery Guide36●Louise Swift and Sally Pitt (2014) Qu antitative Methods for Bu siness, Management and FinanceISBN: 978-1-137-37655 Palgrave Macmillan●Gordon Bancroft and George O’Sullivan (2000) Foundations in Quantitative Business TechniquesISBN: 007-709468-9 McGraw-Hill●Alan Anderson (2013) Business Statistics for DummiesISBN: 978-1-118-63069-3 John Wiley & Sons●Glyn Davis and Branko Pecar (2013) Business Statistics using ExcelISBN: 978-0-19-965951-7 Oxford University Press●David M Levene, Timothy C Kehbiel et al (2012) Business StatisticsISBN: 978-0-273-77092-3 Pearson●Norman Sharpe and Richard D De Veaux et al (2010) Business StatisticsISBN: 978-0321925831 PearsonHelpful websites – providing business data which can be used as a source for analysisTo get the most out of this qualification it is helpful if learners use real business data. Suchdata can be obtained from a variety of sources:●The internet as a source of official data●Government publications●NewspapersThere are a number of websites that contain useful data:●/The Office for N ational Statistics (ON S) produces and publishes a wide range of theinformation about Britain that can be used for social and economic policy making.Much of the data on which policy-makers depend is produced by ONS through a combi-nation of a decennial population census, samples and surveys and analysis of datagenerated by businesses and organisations such as the National Health Service. Bothits publications and its publicly available raw data, available free, are reported anddiscussed daily in the media as the basis for the public’s understanding of the countryin which they live.Similar information can be found on similar sites for other countries:●.my/Detailed information on Malaysian GDP, consumer and producer prices, trade andindustry.●/english/statisticaldataNational Bureau of Statistics of ChinaChapter 6 Further reading and resource suggestions37Other helpful websites include:●https://UK labour market statistics●/news/This is a website that can access international newspapers containing a range of inter-esting data.Student and tutor resources on business statistics from internet websitesThe following websites can be used as a further resource in developing knowledge about the various topics studied for the Business Statistics Certificates. These websites are generic websites that tend to develop a range of mathematical and statistical topics, some of which are relevant to the Certificates in Business Statistics.●/Relevant topics include graphing distributions, summarising distributions, describing bivariate data, probability●/Relevant topics include handling data probability, averages, sampling, standard deviation ●/courses/business/statisticsRelevant topics include frequency tables, probability, sampling techniques●/statistics-resources-for-businesses-and- educators.htmlRelevant topics include descriptive statistics, probability concepts, data collection。

A multi-product multi-echelon inventory control model with joint replenishment strategy

A multi-product multi-echelon inventory control model with joint replenishment strategyWei-Qi Zhou ⇑,Long Chen,Hui-Ming GeSchool of Automobile and Trafﬁc Engineering,Jiangsu University,Zhenjiang 212013,Chinaa r t i c l e i n f o Article history:Received 23January 2011Received in revised form 11April 2012Accepted 21April 2012Available online xxxx Keywords:InventoryMulti-product Multi-echelonGenetic Algorithm (GA)Joint replenishment strategya b s t r a c tOn the basis of analyzing the shortages of present studies on multi-echelon inventory con-trol,and considering some restrictions,this paper applies the joint replenishment strategy into the inventory system and builds a multi-product multi-echelon inventory control model.Then,an algorithm designed by Genetic Algorithm (GA)is used for solving the model.Finally,we respectively simulate the model under three different ordering strate-gies.The simulation result shows that the established model and the algorithm designed by GA have obvious superiority on reducing the total cost of the multi-product multi-echelon inventory system.Moreover,it illustrates the feasibility and the effectiveness of the model and the GA method.Crown Copyright Ó2012Published by Elsevier Inc.All rights reserved.1.IntroductionA supply chain is a network of nodes cooperating to satisfy customers’demands,and the nodes are arranged in echelons.In the network,each node’s position is corresponding to its relative position in reality.The nodes are interconnected through supply–demand relationships.These nodes serve external demand which generates orders to the downstream echelon,and they are served by external supply which responds to the orders of the upstream echelon.The problem of multi-echelon inventory control has been investigated as early as the 1950s by researchers such as Arrow et al.[1]and Love [2].The main challenge in these problems is to control the inventory levels by determining the size of the orders for each echelon during each period so as to optimize a given objective function.Many researchers have studied how to reduce the inventory cost of either suppliers or distributors,or have considered either the distribution system or the production system.Burns and Sivazlian [3]investigated the dynamic response of a multi-echelon supply chain to various demands placed upon the system by a ﬁnal consumer.Van Beek [4]carried out a model in order to compare several alternatives for the way in which goods are forwarded from factory,via stores to the cus-tomers.Zijm [5]presented a framework for the planning and control of the materials ﬂow in a multi-item production system.The prime objective was to meet a presanctiﬁed customer service level at minimum overall costs.Van der Heijden [6]deter-mined a simple inventory control rule for multi-echelon distribution systems under periodic review without lot sizing.Yoo et al.[7]proposed an improved DRP method to schedule multi-echelon distribution network.Diks and Kok [8]considered a divergent multi-echelon inventory system,such as a distribution system or a production system.Andersson and Melchiors [9]considered a one warehouse several retailers’inventory system,assuming lost sales at the retailers.Huang et al.[10]0307-904X/$-see front matter Crown Copyright Ó2012Published by Elsevier Inc.All rights reserved./10.1016/j.apm.2012.04.054⇑Corresponding author.Tel.:+8651188780074;fax:+8651188791900.E-mail address:zwqsky@ (W.-Q.Zhou).2W.-Q.Zhou et al./Applied Mathematical Modelling xxx(2012)xxx–xxxconsidered a one-warehouse multi-retailer system under constant and deterministic demand,which is subjected to transpor-tation capacity for every delivery godimos and Koukoumialos[11]developed closed-form customer service models.And many researchers have modeled an inventory system of only two-echelon or two-layer.Gupta and Albright[12] modeled a two-echelon multi-indentured repairable-item inventory system.Axsäter and Zhang[13]considered a two-level inventory system with a central warehouse and a number of identical retailers.Axsäter[14]considered a two-echelon distri-bution inventory system with stochastic demand.Chen et al.[15]considered a two-level inventory system in which there are one supplier and multiple retailers.Tee and Rossetti[16]developed a simulation model to explore the model’s ability to pre-dict system performance for a two-echelon one-warehouse,multiple retailer system.Seferlis and Giannelos[17]developed a new two-layered optimization-based control approach for multi-product,multi-echelon supply chain networks.Hill et al.[18]considered a single-item,two-echelon,continuous-review inventory model.Al-Rifai and Rossetti[19]presented a two-echelon non-repairable spare parts inventory system.Mitra[20]considered a two echelon system with returns under more generalized conditions,and developed a deterministic model as well as a stochastic model under continuous review for the system.There are also many researches on multi-echelon inventory control,considering either the distribution system or the sup-ply system.Choi et al.[21]evaluated conventional lot-sizing rules in a multi-echelon coalescence MRP system.Chikán and Vastag[22]described a multi-echelon production inventory system and developed a heuristic suggestion.Bregman et al.[23]introduced a heuristic algorithm for managing inventory in a multi-echelon environment.Van der Vorst et al.[24]pre-sented a method for modeling the dynamic behavior of multi-echelon food supply chains and evaluating alternative designs of the supply chain by applying discrete-event simulation.The model considered a producer,a distribution center and2re-tailer outlets.Iida[25]studied a dynamic multi-echelon inventory problem with nonstationary u and Lau[26] applied different demand-curve functions to a simple inventory/pricing model.Routroy and Kodali[27]developed a three-echelon inventory model for single product,which consists of single manufacturer,single warehouse and single retailer. Dong and Lee[28]considered a multi-echelon serial periodic review inventory system and3echelons for numerical exam-ple.The system extended the approximation to the time correlated demand process of Clark and Scarf[29],and studied in particular for an auto-regressive demand model the impact of leadtimes and auto-correlation on the performance of the se-rial inventory system.Gumus and Guneri[30]structured an inventory management framework and deterministic/stochas-tic-neurofuzzy cost models within the context of this framework for effective multi-echelon supply chains under stochastic and fuzzy environments.Caggiano et al.[31]described and validated a practical method for computing channelﬁll rates in a multi-item,multi-echelon service parts distribution system.Yang and Lin[32]provided a serial multi-echelon integrated just-in-time(JIT)model based on uncertain delivery lead time and quality unreliability considerations.Gumus et al.[33] structured an inventory management framework and deterministic/stochastic-neuro-fuzzy cost models within the context of the framework.Then,a numerical application in a three-echelon tree-structure chain is presented to show the applicabil-ity and performance of proposed framework.The model only handled one product type.Only one other paper we are aware of addresses a problem similar to ours and consideres inventory optimization in a multi-echelon system,considering both the distribution system and the supply system.Rau et al.[34]developed a multi-echelon inventory model for a deteriorating item and to derive an optimal joint total cost from an integrated perspective among the supplier,the producer,and the buyer.The model considered the single supplier,single producer and single buyer. The basic difference between our model and Rau et al.[34]is that our model considers multiple suppliers,one producer,and multiple distributors and buyers.Additionally,an algorithm designed by Genetic Algorithm(GA)is used for solving the mod-el,and we apply the joint replenishment strategy into the model.The remainder of this paper is organized as follows:In Section2,the various assumptions are made and the multi-product multi-echelon inventory control model is developed.In Section3,GA is used for solving the model and the algorithm based on GA is designed.Then,we simulate the model under three different ordering strategies,respectively.In Section4,conclu-sions and limitations in this research are presented.2.Mathematical model2.1.The multi-product multi-echelon inventory control model descriptionIn this model,the raw materials,accessories or products can be supplied from the nodal enterprise of layer k to the nodal enterprise of layer k +1,but there is no logistics between nodal enterprises of the same layer or the non-adjacent layers.And also there is no reverse logistics from the nodal enterprise of high-layer to the nodal enterprise of low-layer.The multi-prod-uct multi-echelon inventory system is divided into three subsystems (supply network,core enterprise and distribution net-work)by the core enterprise as a dividing line (Fig.1).The key issue to the multi-product multi-echelon inventory system is to determine the optimal order quantity and the optimal order cycle for each nodal enterprise in order to minimize the inventory cost of the whole system.In this paper,the (T ,S )inventory control strategy based on multi-product joint replenishment is used.The multi-product joint replenishment strategy is an ordering strategy that to order varieties of products in one order cycle.Each nodal enter-prise determines a minimum order cycle as the basic order cycle,and the order cycle of the same enterprise to order each product is an integral multiple of the basic order cycle.2.2.Assumptions(1)In this supply chain,there is only one core enterprise.(2)Allow a variety of products,but the price of each product is ﬁxed.And also allow a variety of raw materials or acces-sories,but one supplier only provides one raw material or accessory.(3)The demand of each nodal enterprise per day is random,but it obeys Poisson distribution.(4)Lead time of each nodal enterprise is ﬁxed.(5)Storage cost per product per unit time is constant.And the storage cost of different nodal enterprises is allowed to bedifferent.2.3.Notations P w price of product w (there are W kind of products,and w =1,2,...,W )P g k Àl price of raw material or accessory provided by the nodal enterprise g of layer k Àl (g =1,2,...,m k Àl ;l =1,2,...,k À1;m k Àl is the number of nodal enterprises of layer k Àl)T h k basic order cycle of the nodal enterprise h of layer k to order products from the nodal enterprises of layer k À1T ðg ;h Þk order cycle of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1Z ðg ;h Þkratio of T ðg ;h Þkand T h k ,which is a positive integer,so T ðg ;h Þk¼Z ðg ;h ÞkT hkA h k public ordering cost of the nodal enterprise h of layer k to order products from the nodal enterprises of layer k À1ineach order cycle,which is independent of the order quantity and the order varietiesA ðg ;h Þkindividual ordering cost of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1in each order cycle,which is dependent of the order quantity and the order varietiesA ðh ;i ;w Þk þl individual ordering cost of the nodal enterprise i of layer k +l to order the product w from the nodal enterprise h of layer k +l À1in each order cycle,in the distribution networkT i k þl basic order cycle of the nodal enterprise i of layer k +l to order products from the nodal enterprises of layer k +l À1,in the distribution networkT ði ;w Þk þl order cycle of the nodal enterprise i of layer k +l to order product w from the nodal enterprises of layer k À1,in the distribution networkZ ði ;w Þk þlratio of T ði ;w Þk þl and T i k þl ,which is a positive integer,so T ði ;w Þk þl ¼Z ði ;w Þk þl T i k þlS ðg ;h Þk maximum inventory level of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1E D ðg ;h Þk average demand of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1perdayL ðg ;h Þk lead time of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1L ði ;w Þk þl the average lead time of the nodal enterprise i of layer k +l to order the product w from the nodal enterprise of layer k +l À1H ðg ;h Þk storage cost of the nodal enterprise h of layer k per product per yearY ðg ;h Þk quantity demand of the nodal enterprise h of layer k to order products from the nodal enterprise g of layer k À1peryear,so Y ðg ;h Þk ¼365E D ðg ;h Þkn ðg ;h Þkthe number of trips from the nodal enterprise g of layer k À1to the nodal enterprise h of layer k per year,which isinversely proportional to order cycle,so n ðg ;h Þk ¼Z ðg ;h Þk T h kÀ1W.-Q.Zhou et al./Applied Mathematical Modelling xxx (2012)xxx–xxx3f ðg ;h Þkﬁxed transportation cost from the nodal enterprise g of layer k À1to the nodal enterprise h of layer k in each trans-portation (such as driver’s wage)t ðg ;h Þkvariable transportation cost to transport the unit product from the nodal enterprise g of layer k À1to the nodal enter-prise h of layer k (such as cost of fuels),which is the function of transport efﬁciency and order quantity in the case of ﬁxed transportation distanceX ðh ;i ;w Þkthe expected value of the produce w of the nodal enterprise h of layer k relative to order quantity of the nodal enter-prise i of layer k +11ðg ;h ;w Þk conversion rate of product w produced by the nodal enterprise h of layer k relative to raw materials or accessories supplied by the nodal enterprise g of layer k À1g ðh ;i ;w Þksupply coefﬁcient of product w supplied from the nodal enterprise h of layer k to the nodal enterprise i of layer k +1,and P m k þ1i ¼1g ðh ;i ;w Þk ¼1b ðg ;h ;w Þkproportionality coefﬁcient of raw materials or accessories used to produce product w ,which are supplied from thenodal enterprise g of layer k À1to the nodal enterprise h of layer k ,and P W w ¼1b ðg ;h ;w Þk¼1B ðh ;i ;w Þkshortage penalty per produce w per order cycle from the nodal enterprise i of layer k +1to the nodal enterprise h of layer k2.4.Multi-product multi-echelon inventory control modelWe divide the inventory cost into ordering cost,holding cost,transportation cost and shortage cost.(1)Ordering costThe total ordering cost of the core enterprise per year is deﬁned as follows:C Order C¼X m kh ¼1A h kT hkþXm k À1g ¼1X m k h ¼1A ðg ;h ÞkZ ðg ;h ÞkT hk:ð1ÞThe total ordering cost of the supply network per year is deﬁned as follows:C Order S¼X k À2l ¼1X m k Àl g ¼1Ag k ÀlT g k ÀlþX k À2l ¼1X m k Àl À1f ¼1X m k Àl g ¼1A ðf ;g Þk Àl Z ðf ;g Þk Àl T g k Àl:ð2ÞThe total ordering cost of the distribution network per year is deﬁned as follows:C Order D¼X N Àk l ¼1X m k þl i ¼1Ai k þl T ik þlþX N Àk l ¼1X m k þl À1h ¼1X m k þl i ¼1X W w ¼1A ðh ;i ;w Þk þl Z ði ;w Þk þl T ik þl:ð3ÞTherefore,the total ordering cost of the multi-product multi-echelon inventory system per year is deﬁned as follows:TC Order ¼C Order C þC Order S þC Order D:ð4Þ(2)Holding costThe inventory level of the nodal enterprise h of layer k when it has received the order quantity from the nodal enter-prise of layer k À1is:S ðg ;h ÞkÀE D ðg ;h Þk L ðg ;h Þk ;ð5Þand the inventory level of the nodal enterprise h of layer k before it receives the order quantity next order cycle is:S ðg ;h ÞkÀE D ðg ;h Þk L ðg ;h Þk ÀE D ðg ;h Þk Z ðg ;h Þk T h k :ð6ÞTherefore,the average inventory level in one order cycle is:12S ðg ;h Þk ÀE D ðg ;h Þk L ðg ;h Þk þS ðg ;h Þk ÀE D ðg ;h Þk L ðg ;h Þk ÀE D ðg ;h Þk Z ðg ;h Þk T h k hi ¼S ðg ;h Þk ÀE D ðg ;h Þk L ðg ;h Þk ÀE D ðg ;h ÞkZ ðg ;h Þk T h k 2:ð7ÞThe total holding cost of the core enterprise per year is deﬁned as follows:C Hold C¼Xm k À1g ¼1X m k h ¼1S ðg ;h Þk ÀE D ðg ;h Þk L ðg ;h Þk ÀE D ðg ;h Þk Z ðg ;h Þk T h k22435H ðg ;h Þk:ð8Þ4W.-Q.Zhou et al./Applied Mathematical Modelling xxx (2012)xxx–xxxAs a practical matter,we must ensure that the average inventory level is greater than zero,as shown in Eq.(9):Sðg;hÞk ÀE Dðg;hÞkLðg;hÞkÀE Dðg;hÞkZðg;hÞkT hk2>0:ð9ÞThe total holding cost of the supply network per year is deﬁned as follows:C Hold S ¼X kÀ2l¼1Xm kÀlÀ1f¼1X m kÀlg¼1Sðf;gÞkÀlÀE Dðf;gÞkÀlLðf;gÞkÀlÀE Dðf;gÞkÀlZðf;gÞkÀlT gkÀl22435Hðf;gÞkÀl;ð10Þunder the following constraint:Sðf;gÞkÀl ÀE Dðf;gÞkÀlLðf;gÞkÀlÀE Dðf;gÞkÀlZðf;gÞkÀlT gkÀl2>0:ð11ÞThe total holding cost of the distribution network per year is deﬁned as follows:C HoldD ¼X NÀkl¼1X m kþli¼1X Ww¼1Sði;wÞkþlÀE Dði;wÞkþlLði;wÞkþlÀE Dði;wÞkþlZði;wÞkþlT ikþl22435Hði;wÞkþl;ð12Þunder the following constraint:Sði;wÞkþl ÀE Dði;wÞkþlLði;wÞkþlÀE Dði;wÞkþlZði;wÞkþlT ikþl2>0:ð13ÞTherefore,the total holding cost of the multi-product multi-echelon inventory system per year is deﬁned as follows:TC Hold¼C HoldC þC HoldSþC HoldD:ð14Þ(3)Transportation costThe total transportation cost of the core enterprise per year is deﬁned as follows:C Trans C ¼Xm kÀ1g¼1X m kh¼1nðg;hÞkfðg;hÞkþtðg;hÞkYðg;hÞkh i:ð15ÞThe total transportation cost of the supply network per year is deﬁned as follows:C Trans S ¼X kÀ2l¼1Xm kÀlÀ1f¼1X m kÀlg¼1nðf;gÞkÀlfðf;gÞkÀlþtðf;gÞkÀl Yðf;gÞkÀlh i;ð16Þwhere nðf;gÞkÀl ¼Zðf;gÞkÀlT gkÀlÀ1;Yðf;gÞkÀl¼365E Dðf;gÞkÀlThe total transportation cost of the distribution network per year is deﬁned as follows:C TransD ¼X Ww¼1X NÀkl¼1Xm kþlÀ1h¼1X m kþli¼1nði;wÞkþlfðh;iÞkþlþtðh;iÞkþl Yðh;i;wÞkþlh i;ð17Þwhere nði;wÞkþl ¼Zði;wÞkþlT ikþlÀ1;Yðh;i;wÞkþl¼365E Dðh;i;wÞkþlTherefore,the total transportation cost of the multi-product multi-echelon inventory system per year is deﬁned as follows:TC Trans¼C TransC þC TransSþC TransD:ð18Þ(4)Shortage costAssuming Xðh;i;wÞk obeys Poisson distribution p kðh;i;wÞkZðg;hÞkT hkþLðg;hÞkh iduring the period Zðg;hÞkT hkþLðg;hÞk,so:Xðh;i;wÞk ¼X1u¼AuÀgðh;i;wÞk1ðg;h;wÞkbðg;h;wÞkSðg;hÞkp kðh;i;wÞkZðg;hÞkT hkþLðg;hÞkh i:ð19ÞThe total shortage cost of the core enterprise per year is deﬁned as follows:C Shortage C ¼X m kh¼1Xm kþ1i¼1X Ww¼1Bðh;i;wÞkXðh;i;wÞkZðg;hÞkT hk:ð20ÞW.-Q.Zhou et al./Applied Mathematical Modelling xxx(2012)xxx–xxx5The total shortage cost of the supply network per year is deﬁned as follows:C Shortage S¼X k À2l ¼1X m k Àl g ¼1X m k Àl þ1h ¼1B ðg ;h Þk Àl X ðg ;h Þk ÀlZ k Àl T g k Àl;ð21ÞwhereX ðg ;h Þk Àl¼P 1u ¼Au Àgðg ;h Þk Àl 1ðf ;g Þk Àl S ðf ;g Þk Àlp k ðg ;h Þk Àl Z ðf ;g Þk Àl T g k Àl þL ðf ;g Þk Àl h i ;g ðg ;h Þk Àl ¼E D ðg ;h Þk Àl þ1ÀÁP m k Àl þ1h ¼1E Dðg ;h Þk Àl þ1ÀÁ,and P m k Àl þ1h ¼1g ðg ;h Þk Àl ¼1.The total shortage cost of the distribution network per year is deﬁned as follows:C Shortage D¼X N Àk l ¼1X m k þl i ¼1X m k þl þ1j ¼1X W w ¼1B ði ;j ;w Þk þl X ði ;j ;w Þk þl Z ði ;w Þk þl T i k þl;ð22ÞwhereX ði ;j ;w Þk þl¼X 1u ¼Au Àg ði ;j ;w Þk þl S ði ;w Þk þl p k ði ;j ;w Þk þl Z ði ;w Þk þl T i k þl þL ði ;w Þk þl h i;gði ;j ;w Þk þl¼E D ði ;j ;w Þk þlk þl þ1j ¼1E D ði ;j ;w Þk þl;andX m k þl þ1j ¼1g ði ;j ;w Þk¼1:Therefore,the total shortage cost of the multi-product multi-echelon inventory system per year is deﬁned as follows:TC Shortage ¼C Shortage C þC Shortage SþC Shortage D :ð23ÞIn conclusion,we develop the multi-product multi-echelon inventory control model as follows:minTC ¼TC Order þTC Hold þTC Trans þTC Shortage ;ð24Þs :t :E D ðg ;h ÞkL ðg ;h Þk þE D ðg ;h Þk Z ðg ;h Þk T h k 2ÀS ðg ;h Þk <0;ð25ÞE D ðf ;g Þk Àl L ðf ;g Þk Àl þE D ðf ;g Þk Àl Z ðf ;g Þk Àl T g k Àl 2ÀS ðf ;g Þk Àl <0;l ¼1;2;...;k À2;f ¼1;2;...;m k Àl À1;g ¼1;2;...;m k Àl ;ð26ÞE D ði ;w Þk þl L ði ;w Þk þl þE D ði ;w Þk þl Z ði ;w Þk þl T i k þl2ÀS ði ;w Þk þl <0;l ¼1;2;...;N Àk ;i ¼1;2;...;m k þl ;w ¼1;2;...;W ;ð27Þmin Z g ¼1;h ðÞk ;Z g ¼2;h ðÞk ;...;Z g ¼m k À1;h ðÞk h i¼1;ð28Þmin Z ðf ¼1;g Þk Àl ;Z ðf ¼2;g Þk Àl ;...;Z ðf ¼m k Àl À1;g Þk Àl h i¼1;l ¼1;2;3;...;k À2;ð29Þmin Z ði ;w ¼1Þk þl ;Z ði ;w ¼2Þk þl ;...;Z ði ;w ¼W Þk þl h i ¼1;l ¼1;2;3;...;N Àk :ð30Þ(28)–(30)can ensure that at least one product’s order cycle is the basic order cycle.The decision variables in the model are allintegers greater than or equal to zero.3.Simulation and analysis 3.1.Simulation model based on GAThe objective function of this optimization model is minimization,and the objective function of GA is maximization,so the objective function of this optimization model cannot be taken as the ﬁtness function of GA.We must convert the objec-tive function to the ﬁtness function of GA as follows:F ðX Þ¼TC max ÀTC ;TC <TC max ;0;TC P TC max ;&ð31Þwhere F (X )is the individual ﬁtness.TC max is a relatively large number,and in this simulation model,we may put TC max as the largest objective function value during evolution.The multi-product multi-echelon inventory control model can be reduced to a nonlinear programming problem as follows:6W.-Q.Zhou et al./Applied Mathematical Modelling xxx (2012)xxx–xxxmin f ðX Þ;ð32Þs :t :g i ðX Þ60ði ¼1;2;3;...;m Þ:In this paper,penalty function is used as constraint.So,we construct the penalty function as follows:/ðX ;c kÞ¼X m i ¼1c k i min g i ðX Þ;0ðÞ2;ð33Þwhere k is iteration times of GA.c k i is penalty factor,which is a monotone increasing sequence and positive value.Andc k þ1i ¼e i Ác ki .The experience in computation shows that if c k i ¼1and e i =5À10,we can achieve satisfactory results.So,we change (31)to the function as follows:F ðX Þ¼TC max ÀTC À/ðX ;c k Þ;TC <TC max ;0;TC P TC max :(ð34ÞMoreover,we use the ﬂoating point number coding (the chromosome’s length equals the number of decision variables),the roulette wheels selection mechanism as the selection operator,the arithmetic cross technique as the crossover operator,the Gauss mutation operator as the mutation operator,and algebra (its values range from 100to 500)as the termination criteria.3.2.SimulationAs an illustration,we develop a multi-product multi-echelon inventory control model which has four suppliers (the four suppliers are divided into two levels and each level has two suppliers),one core enterprise and two distributors,and has two products (Fig.2).The average demand of the customers to order product 1and product 2from the distributor 1of layer 4per day is 6units and 3units.The average demand of the customers to order product 1and product 2from the distributor 2of layer 4per day is 4units and 7units.The values of other parameters are shown in Tables 1–3.Table 2The values of the parameters of the supply network.Parameters A 12A ð1;1Þ2A ð2;1Þ2A 22A ð1;2Þ2A ð2;2Þ2L ð1;1Þ2L ð2;1Þ2L ð1;2Þ2Values $70$200$180$60$250$250666Parameters L ð2;2Þ2H ð1;1Þ2H ð2;1Þ2H ð1;2Þ2H ð2;2Þ2f ð1;1Þ2f ð2;1Þ2f ð1;2Þ2f ð2;2Þ2Values 6$3$6$3$15$200$140$250$150Parameters t ð1;1Þ2t ð2;1Þ2t ð1;2Þ2t ð2;2Þ2g ð1;1Þ2g ð2;1Þ2g ð1;2Þ2g ð2;2Þ21ð1;1Þ2Values $4$6$5$811111Parameters 1ð2;1Þ21ð1;2Þ21ð2;2Þ2B ð1;1Þ2B ð2;1Þ2B ð1;2Þ2B ð2;2Þ2Values0.510.5$150$120$160$140Table 1The values of the parameters of the core enterprise.Parameters A 13A ð1;1Þ3A ð2;1Þ3L ð1;1Þ3L ð2;1Þ3H ð1;1Þ3H ð2;1Þ3f ð1;1Þ3f ð2;1Þ3Values $100$240$32055$5$40$300$350Parameters t ð1;1Þ3t ð2;1Þ3g ð1;1;1Þ3g ð1;2;1Þ3g ð1;1;2Þ3g ð1;2;2Þ31ð1;1;1Þ31ð2;1;1Þ31ð1;1;2Þ3Values $15$100.60.40.30.70.510Parameters 1ð2;1;2Þ3b ð1;1;1Þ3b ð1;1;2Þ3b ð2;1;1Þ3b ð2;1;2Þ3B ð1;2;1Þ3B ð1;1;2Þ3B ð1;2;2Þ3B ð1;1;1Þ3Values110.50.5$150$120$180$200W.-Q.Zhouet al./Applied Mathematical Modelling xxx (2012)xxx–xxx 7。

CIIA考试历年真题2011-2012 答案PDF版

关注证书君，让你复习时感到贴心；关注证书君，让你考试时感到顺心；关注证书君，让你出分时感到开心：/601118526/考试二固定收益估值和分析衍生产品估值和分析投资组合管理答案最终考试2011年3月问题1：固定收益估值和分析 (43 分)下面给出的只是参考答案，不代表是唯一的计算方法和解释。

考生给出的计算和解释只要是合理的就可以（不同的计算方法对应的计算结果可能会不同）。

a) a1)永久债券的价格P 等于其固定票息（C ）除其收益率（R ）：42.77%25.4%50.36R C P =+==(4 分) a2)永久债券的麦考利久期 D 定义如下：年9.131%25.4%50.3111=++=+=Yield D修正久期 D mod 是： 9.12%25.4%50.319.13Yield 1D D mod =++=+=(4 分)其他解法：:麦考利久期： y y1D +=修正久期 9.120775.01y 1y 1D D mod ===+=(4 分) a3)永久债券的价格 P 近似为 (y 是收益率):()99.9%1%25.4%50.319.1342.77y y 1D P P =-⋅++⋅-=∆⋅+⋅-=∆结果新的价格是 77.42 + 9.99 = 87.41 (4 分) a4)只有当收益率曲线发生微小的平行移动时，债券价格的线性近似才适用。

利差收紧100bps 并不小，也就是说这里的线性近似不适用，利差收紧后债券的准确价格是88.89，而不是上面近似的 87.41，89.88%1%75.76y CF P =-==(5 分)b1)如果赎回债券，可依照下列步骤计算经济损失（单位：百万欧元）：- 100%的价格赎回导致支付 1,000（百万欧元）；-其他条件相同的情况下，如果没有赎回，则债券价格77.42，因此负债为774.2（百万欧元）=> 经济损失 = (1 – 0.7742) （十亿欧元） = 225.8 （百万欧元） (4 分)[注:如果基于下列原因,得出“没有损失”这个答案也可算是正确的。

0032 ND Rev 0 - 06 December 2010 - Guidelines for Moorings系泊指南

© 2010 Noble Denton Group Limited, who will allow:
the document to be freely reproduced, the smallest extract to be a complete page including headers and footers, but smaller extracts may be reproduced in technical reports and papers, provided their origin is clearly referenced.
15 16 20 22 24 24 24 25 26
Minimum Horizontal Anchor Clearances from Pipelines or Cables
27
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GUIDELINES FOR MOORINGS
PREFACE
This document has been drawn with care to address what are likely to be the main concerns based on the experience of the GL Noble Denton organisation. This should not, however, be taken to mean that this document deals comprehensively with all of the concerns which will need to be addressed or even, where a particular matter is addressed, that this document sets out the definitive view of the organisation for all situations. In using this document, it should be treated as giving guidelines for sound and prudent practice on which our advice should be based, but guidelines should be reviewed in each particular case by the responsible person in each project to ensure that the particular circumstances of that project are addressed in a way which is adequate and appropriate to ensure that the overall advice given is sound and comprehensive. Whilst great care and reasonable precaution has been taken in the preparation of this document to ensure that the content is correct and error free, no responsibility or liability can be accepted by GL Noble Denton for any damage or loss incurred resulting from the use of the information contained herein.

国际注册分析师(CIIA)2012年3月试卷 II真题及答案

考试 II:固定收益证券估值和分析衍生产品估值和分析投资组合管理问题最终考试2012年3月问题1：固定收益估值和分析(46 分)作为一家欧洲资产管理公司的固定收益组合的经理，你目前持有的债券组合如下：债券息票 (每年) 到期时间价格利差 vs. Gov. 评级A 1% 1 年99.507% 40 bps AAB 2% 2 年99.321% 60 bps AAC 3% 3 年101.434% 90 bps AA说明：债券所有的息票每年支付一次。

a)首先你必须进行一些基本的计算。

a1)为AA级的发行人计算1年、2年和3 年的即期利率（也称为“纯贴现”或“零”利率）。

(9 分) a2)计算每只债券和债券组合（此组合由债券A、B和C组成，而且每只债券的权重相同）的久期。

在计算久期时使用不同期限的即期利率。

【注：如果你没计算出问题a1)中的即期利率，可以使用到期收益率计算久期，到期收益率可以近似为“息票/价格”】。

(10 分)a3)计算一年后1年期和2年期的远期利率（基于现在的即期利率）。

(5 分) a4)假定“纯预期假说”成立，确定一年后投资债券C的持有期回报。

【注：首先基于一年后的远期利率计算债券C的价格，把结果与初始投资和息票进行比较。

如果没有解出问题a3)，则假设1年后2年期的远期利率是3%】。

(5 分) a5)如果债券C一年的持有期收益率是2.79%，确定债券C价格变化的百分比。

(4 分)b) 假设不同评级的债券利差（相对于政府债券）如下表所示，这里利差是期限和评级的函数:评级 1 年 2 年 3 年AAA 20 bps 30 bps 50 bpsAA 40 bps 60 bps 90 bpsA 80 bps 90 bps 125 bpsBBB 120 bps 170 bps 250 bps如果一年后债券C以2.65%的到期收益率交易，2年期的AA 级债券以2.35%的到期收益率交易。

债券C的近似评级是什么? 假设利差表没有变化。

CIIA历年真题2013年03paper1

试卷I：经济学公司财务财务会计和财务报表分析股票估值和分析问题最终考试2013年3月问题1：经济学(37分)日本经济被认为处在通缩状态。

2011年底消费者价格指数实际上和20年前处在同一水平。

和10年前相比，它下降了。

上世纪九十年代，日本政府采取了扩张性的财政政策，但不足以推动日本经济。

这些支出除了使政府财政状况更加恶化外，没有产生其它作用。

在2011年末，长期国债存量规模达到755万亿日元，为名义GDP的1.6倍（2010年日本名义GDP为479万亿日元）。

2011年3月份发生在日本东部的一场大地震又导致了更多的财政措施来重建基础设施。

a)请回答以下两个问题。

a1)首先，解释什么是凯恩斯消费方程的45度线模型。

请把GDP（总供给）设置为横轴，并假设需求仅仅由消费和外生性投资组成。

(6分)a2)然后，图解并说明何为通缩状态。

在你的解释中，把通缩状态和一个既无过剩需求也无过剩供给的状态做比较。

【提示：通过探讨通缩状态对需求的两大部分的影响来答题。

】(4分)b)通过解答以下三个问题，解释政府为地震重建而采取的财政措施的影响。

b1)请用45度线模型来图解并说明这种影响。

请和通缩状态比较。

(4分)b2)请用IS-LM模型来图解并说明这种影响。

在你的解释中，请评论它和45度线模型的区别。

(4分)b3)上世纪九十年代的日本扩张性财政政策最终没有产生经济效应。

请解释一般情况下何种社会经济状况会减弱财政政策的效果。

请指出两种情况来。

(4分)c)考虑日本政府的财政问题。

在你的回答中假定政府债务全部由长期国债构成。

c1)解释政府的基本平衡是什么，以及为重建基础设施而采取的财政措施对该基本平衡的影响。

(3分)c2)如果基本平衡是平衡的（即，差额为零），请解释政府债券余额在0年底和1年底的关系。

【提示：如果你未能解出问题c1），则假定政府财政收支余额为0，且仅有短期政府债务。

】(3分)______________________________________________________________________________________c3)请描述像日本这样一个长期国债余额高于名义GDP并且长期国债利率高于名义GDP增长率的国家的长期国债余额和名义GDP的未来的关系。

丰田召回事件的背后

ENTERPRISE MANAGEMENT 2, 2010丰田召回事件的背后卷首语顾问袁宝华陈锦华王忠禹张彦宁李德成赵维臣范敬宜朱焘编委会主任邵宁编委会副主任尹援平主编邵宁社长尹援平副社长孙庆生贺卫华编辑部主任孙庆生（兼）责任编辑郭学军张平王仕斌美术编辑王硕赵瑞梅广告部主任朱军编辑者企业管理杂志编委会出版者企业管理杂志社印刷者北京新华印刷厂总发行处北京邮政局报刊发行局订购处全国各地邮局国外总发行中国国际图书贸易总公司（北京399信箱）广告经营许可证京海工商广字第0107号刊号 ISSN 1003-2320CN11-1099/F国内代号 2-650国外代号 M651国内定价 16.00元地址北京市海淀区紫竹院南路17号邮编 100048电话 (010)68414646 68701338（编辑部）(010)68467871（发行）(010)68701919 68701247（广告）E-mail qyglzz@中企联合网址本期广告索引柳工集团/封底深圳华天谋企业管理顾问有限公司/封二江苏梅兰服饰有限公司/封三“三天一层楼”公益行/前插山东高速集团有限公司/前插3A 企管·工厂顾问/前插南京奥维斯雕塑艺术有限公司/P27注册供应链管理师培训认证/P39注册资产管理师培训认证/P39注册纳税筹划师/P65中国注册金融分析师培养计划/P65内蒙古金岗重工有限公司/P106主桅设计/P108全国经济类核心期刊国务院国有资产监督管理委员会主管中国企业联合会主办ENTERPRISE MANAGEMENT 3, 20101近来，丰田在自己引以为傲的“丰田品质”上出了安全问题，发生了大规模的召回事件，教训深刻。

究其根源，笔者以为有以下几点：第一，终生雇佣体制的瓦解。

在日本企业的产品成本中，劳动力成本所占比重非常大，为了降低成本，包括丰田在内的很多日本企业开始修正传统的终生雇佣制，尽可能减少终生雇佣员工的数量，采用大量的合同工、派遣工。

合肥工业大学自学考试本科毕业设计(论文)模板

高等教育自学考试本科毕业设计（论文）题目：（三号楷体加粗）姓名：（三号楷体加粗）专业：（三号楷体加粗）指导教师：（三号楷体加粗）年月日合肥工业大学自学考试本科毕业设计（论文）诚信声明本人郑重声明：所呈交的毕业设计（论文），题目《×××××××》是本人在指导教师的指导下，独立进行研究工作所取得的成果。

对本文的研究做出重要贡献的个人和集体，均已在文中以明确方式注明。

除此之外，本论文不包含任何其他个人或集体已经发表或撰写过的作品成果。

本人完全意识到本声明的法律结果。

毕业设计（论文）作者签名：日期：年月日目录（三号黑体加粗居中段前0行段后0行）中文摘要和关键词（小四宋体分散对齐段前0行段后0行） (1)一、我国中小企业利用融资租赁的现实障碍 (1)融资租赁在中小企业融资中的优势 (1)融资租赁在中小企业融资中存在的现实问题 (2)二、融资租赁的国际经验借鉴 (3)国外对融资租赁业的宏观管理 (4)国外融资租赁业的微观环境 (4)三、对我国中小企业利用融资租赁中所存在问题的深入分析 (5)融资租赁的基本架构 (5)制约我国融资租赁业发展的因素 (5)四、结语 (12)参考文献 (13)致谢 (13)（小二华文中宋居中段前0行段后0行单倍行距）张三（五号宋体居中段前0行段后0行单倍行距）经济学（五号宋体居中段前0行段后0行单倍行距）【摘要】（小四宋体加粗）本文用比较的手法提出融资租赁是中小企业融资的有效工具，并通过中小企业利用融资租赁的情况统计数据提出我国当前中小企业在利用融资租赁中存在的问题，然后深入分析影响该问题的宏观环境和微观因素，最后提出通过国家政策调整融资租赁业发展的宏观环境，通过市场主体的自我完善改变微观因素的对策。

（正文宋体五号段前0行段后0行单倍行距首行缩进2字符）【关键词】（小四宋体加粗）中小企业；融资租赁；供求模型（正文宋体五号段前0行段后0行单倍行距首行缩进2字符）（小二华文中宋居中段前0行段后0行单倍行距）对于中小企业的划分，世界上没有一个统一的标准，在中国，据国家发改委和财政部制定的企业划分标准，出口额的68%、税收的48%[1]。

商品说明书智能足球机器人控制器

International Conference on Education Technology and Information System (ICETIS 2013) Investigation and Project Analysis of College Student's EntrepreneurialWish in the Pattern of Limited PartnershipShi-hua LI1, 3, a, Zhi-yuan Hu2, b and Zhang Wei3, c1School of management and engineering, Nanjing University, Nanjing 210093, China2School of Marxism, Hohai University, Nanjing 210098, China3Postdoctoral Workstation, Govtor Capital, Nanjing 210009 Chinaa******************,b*****************,c*******************Keywords: College student; Limited Partnership; Entrepreneurial Wish; Employment; Start-ups Abstract. According to the problem that the intelligence is not high of the soccer robot, using the mechanical theory as a guide, making some mechanical analyses and calculations on the pressure and transmutation states of chip kick mechanics, and conducting optimal design too, then making the structure of chip kick mechanics more and more rationalization. Experiments show that the new soccer robot controller features a quick response and high servo rigidity, and provide a kind of method for improving and perfecting the soccer robot control system, at the same time, filling the needs of producing.IntroductionEntrepreneurship is a process or an activity to create and establish a business [1].Entrepreneurship is a way of thinking, reasoning and behavior, and this way of behavior is driven by opportunities, methods and equilibrium with the leadership[2]. Since enlarging enrollment of high education in china in 1999, the graduates are increasing year after year, pressure on employment of college students are growing. Diversified employment channels become an inevitable trend of college students; meanwhile business Partnership has been also becoming a way to ease the employment pressure. In this context, it is very much necessary to study the pattern of college students' business partnership, especially limited partnership, in such a way we can not only understand the status of entrepreneurial wish in the pattern of limited partnership, but also find out rational way to alleviate the current problems of student's employment pressure. It is not a simple linear relationship between entrepreneurship and employment, but new venture will bring a direct impact on employment in the short term in the initial periods [3]. Finally, solve the problems existing in college students' entrepreneurial wish-category of motivations which constitutes the basis of the behavior of human beings[4]. This subject adopts targeted interview survey, and the approach of data collection combines self-administered questionnaires with visit method. Taking Huangshan University (a typical China's Midwest University) as a survey site for an example, a representative reaction of students' entrepreneurial wish in partnership will be presented. Because of the limitation of conditions, the sample elements use a random sampling method, the total sample of 100 questionnaires.1 Results of investigationThe survey collected a total of 100 questionnaires, conducted a survey of 100 college students in Huangshan University, freshman 30, sophomore 30, junior 40. There are 40 boys and 60 girls respectively. For a large number of senior students left school for practice or finding jobs, so they are not the objects in our survey. The survey shows that: the entrepreneurial willingness of boys is more Intensive than girls', 85% and 57% respectively; high grade than low-grade student, 76% and 54% respectively; Industrial choice of future entrepreneurial wish in limited partnership includes the food service industry 43%, computer 8%, advertising 11% , finance 16% , garment industry 9%, other 13%.1.1 Understanding of starting a business in partnershipThe survey shows that about 84% of the students believe that the starting-business is to create a career, which is consistent with the fact, and indicates that my college students have a macro understanding, open thinking conducive to the development of the cause? However, science and engineering students are more inclined to develop cutting-edge sci-and-tech projects. About 73% of the students have idea of starting a business, 19% of the students do not have, and 8% do not care about. However, although the majority of students want to start a business in partnership, but only 35% of the students began to prepare, 65% of the students did not prepare. The survey also found that, in the selection of entrepreneurial mode, 64% of the students tend to choose the pattern of partnership as Figure 1 shows.11%12%64%13%0%20%40%60%80%Co. Ltd individualproprietorship partnership otherFigure 1 The choice of different entrepreneurial model1.2 The preparatory work of starting a business in partnershipSingh (2001) believes that entrepreneurship is the process to create a new enterprise [3]. This course needs an adequate preparation. The college students who have done preparation for starting a business in partnership accounts for about 35%, in which about 14% of the students advocates practicing into an enterprise, 18% tends to take part in entrepreneurship training, 7% participate in the Business Plan Competition, 53% advocates learning business knowledge from entrepreneurial books, 38% are ready to go to the internship, 4% tends to seek help entrepreneurial entrepreneurs. On how to obtain the knowledge and skills of entrepreneurship, 13% of the students hope to learn from teachers' lecture, and 47% want to participate in activities and training, 36% of students want to get through their own hands, about 4% of the students hope to obtain the knowledge and skills of the business partnership by other means (See Fig. 2).13%4%36%47%0%10%20%30%40%50%the professor's lecture courseactivitiies andtraining personal pratice other wayFigure 2 The obtaining way of entrepreneurial knowledge and skillsAfter making forecast of the prospects of college students' business in the pattern of partnership, only 8% express their confidences, 13% on the entrepreneurial prospects feel confused, 28% of the students have a certain pressure, 47% of the students think that starting-business in partnership like a gambling, and 19 % of students choose other ways.1.3 The preparatory work of starting a business in partnershipFor undergraduates, there are a lot of obstacles during the course of starting business in the pattern of partnership. This investigation mainly involves such indexes as lack of money, inexperience, further studies, family's opposition, larger pressures and others. The survey showed that: 47% of the students believe that the biggest entrepreneurial obstacle is the lack of funds, and have no better direction; 23% of students believe they lack experience and social relations; 13% of students consider that they need further studies, 6% are getting the objections of the family, 17% think that, when facing ventures, the heart affordability is not enough, as Fig.3 shows.17%4%23%6%13%0%5%10%15%20%25%lack ofexperience further studies family's oppsition excessive pressure othersFigure 3 The obtaining way of entrepreneurial knowledge and skills1.4 The choice of a partnerWith reference to starting venture, it is essential to choose a partner, which sometimes also determines the success and failure of the investment even if you have a good project. The survey shows that, in the choice of partners, 4% of the students hope to choose peers (people of her own age), 42% of the students want to start a business with people with the same experience, 16% want to cooperate with partners with highly education, 31% want to work with people with a certain economic base, 7% of the students want to start business with friends and relatives ( in Figure 4).4%42%16%31%7%0%10%20%30%40%50%peers people withexperience one with high diploma one with economic base releativesFigure 4 The college students' conditions of the choice of a partner2Existing problems in college student's entrepreneurial wish in partnership 2.1The lack of enough preparatory workCollege students have entrepreneurial intention, but the indexes of entrepreneurial practice are too low. There are still a great number of questions on starting an undertaking: the preparatory work of venture is not enough; there is no clear entrepreneurial direction. The partnership entrepreneurship is a more complex entrepreneurial model; especially early it is difficult for inexperienced college students in start-up stage. There is no enough money and experience, even if the start-up is opened, the start-up will be closed for a not long time.2.2 The lack of rationality in the choice of a partnerSingh (2001) believes that entrepreneurship is the process to create a new enterprise [5]. In the legal sense the selection of partner of a partnership venture tend to choose investors with mutual trust together, but for this particular group of college students, the element of capital and experience may be more important. The college students who have not yet leave the campus, have no experience, no money, no interpersonal relationships, so entrepreneurship is difficult, especially more difficult after the venture. For this reason, there is contradiction in selecting partner.Additionally, this investigation shows that college student in Hungshan University have entrepreneurial awareness, but their mental capacity are too strong enough to endure failure of entrepreneurship.3Conclusion and strategic recommendations of starting undertaking in partnershipEntrepreneurship is a systematic project; it requires entrepreneurs to accumulate a series of certain knowledge in such aspects as corporate positioning, strategic planning, property relations, marketing, production organization, team building, financial system, such as accumulation. Believe that a lot of people, on behalf of certain entrepreneurial success concept with a good idea and creative entrepreneurial preparation of the problems you might encounter inadequate preparation orsimply do not think about countermeasures designed exit mechanism. It is not enough to only have entrepreneurial wish, and it is necessary for college students to make full preparation and design a much better exit mechanism. As per this investigation and employment problem of college students in China, suggestions are as follows:3.1Enhangce policy supportFor college students having entrepreneurial wishes, the majority of students must have a good business philosophy; relevant departments of the government should create a good entrepreneurial environment, and enact certain entrepreneurship policy to educate and support undergraduates' entrepreneurial intention. College students start their own undertaking so as to not solve their own career development but also bring more employment opportunity, which is essential for the promotion of economic and social development and maintaining social stability.The government and university create a good business environment. For example, in the respect of building college students' business incubator, effective leadership and coordination mechanism should be established in order to solve the problem of "underemployment" on the basis of the implementation of "Guidance Planning of College Student's Entrepreneurship". Colleges and universities should establish specialized institutions of entrepreneurship education and training faculty, and identified entrepreneurship education as elective courses. Additionally, Universities can make full use of campus resources, and promote the launching of the Campus' Business Plan Competition.3.2Establish clear process of starting an undertakingFirstly, there lives a clear positioning: that is who I am, what I can do, what I have to do; Secondly, according the requirement for a standard Business Plan, a business plan for this entrepreneurial project should be written, and the item concerns "people, money and content", "production, supply, and marketing". Thirdly, you can invite people-who are more familiar with the industry-to find prick on your plan and give the feasibility analysis. Fourthly, management teams should be built, partners should be selected, and at the same time the principles of cooperation should be determined. Finally, an operating plan and implementation plan should be formulated.3.3Act from the realityAs a partnership venture for college students Huangshan University as a typical mid-west university, those college students who would like to venture must combine their own theory learned from campus with practice in the society. That is to do everything from the reality. Starting undertaking isn't just a matter of entrepreneurial wishes. It is with actual action that the success possibility of starting an undertaking in limited partnership would be increased. AcknowledgementsThis work was financially supported by: Govtor Capital(JSGOVTOR2012); "Doctor clustering scheme of enterprises in Jiangsu Province-the category of Enterprise postdoctoral"; and the scientific research innovation project in Jiangsu province (CXZZ12-0222).References[1] Yan-fu Jiang, Global Entrepreneurship Monitor 2002 Report, Beijing: Tsinghua University Press, 2003.[2] Man-hong Liu, Venture capital: innovation and financial, Beijing,China Renmin University Press, 2005.[3] Fritsch M. Effects of new business formation on regional development over time [J]. Regional Studies, 2004, 38: 961-975.[4] Weiner, B. An attributional theory of achievement motivation and emotion. Psychological Review, 1985, 548-573.[5] Singh, R. 2001. A comment on developing the field of entrepreneurship through the study of opportunity recognition and exploitation. Academy of Management Review, 26(1): 10-12.。

CICCR 0.3.0 用户指南说明书

Package‘ciccr’October20,2023Type PackageTitle Causal Inference in Case-Control and Case-Population StudiesVersion0.3.0Description Estimation and inference methods for causal relative and attributable risk in case-control and case-population studiesunder the monotone treatment response and monotone treatment selection assumptions.For more details,see the paper by Jun and Lee(2023),``Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions,''<arXiv:2004.08318[econ.EM]>,accepted for publication in Journal of Business&Economic Statistics.License GPL-3Encoding UTF-8LazyData trueRoxygenNote7.2.3Imports stats,glmnetSuggests knitr,rmarkdown,testthat,MASS,splines,MatrixVignetteBuilder knitrDepends R(>=2.10)URL https:///sokbae/ciccr/BugReports https:///sokbae/ciccr/issuesNeedsCompilation noAuthor Sung Jae Jun[aut],Sokbae Lee[aut,cre]Maintainer Sokbae Lee<*******************>Repository CRANDate/Publication2023-10-2021:30:02UTC12AAA_DML R topics documented:AAA_DML (2)ACS (3)ACS_CC (4)ACS_CP (4)avg_AR_logit (5)avg_RR_logit (6)cicc_AR (7)cicc_plot (9)cicc_RR (10)DZ_CC (11)FG (12)FG_CC (13)FG_CP (14)trim_pr (15)Index16 AAA_DML Average Adjusted AssociationDescriptionAverages the log odds ratio using prospective or retrospective high-dimensional logistic regressionUsageAAA_DML(y,t,x,type="pro",k=10)Argumentsy n-dimensional vector of binary outcomest n-dimensional vector of binary treatmentsx n by d matrix of covariatestype’pro’if the average is based on prospective regression;’retro’if it is based on prospective regression(default=’pro’)k number of folds in k-fold partition(default=10)ValueAn S3object of type"ciccr".The object has the following elements.est a scalar estimatese standard errorACS3 ReferencesJun,S.J.and Lee,S.(2020).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.Examples#use the ACS dataset included in the packagey=ciccr::ACS$topincomet=ciccr::ACS$baplusage=ciccr::ACS$agex=splines::bs(age,df=6)#b-splines for ageresults=AAA_DML(y,t,x, pro ,k=2)ACS ACSDescriptionSample extracted from American Community Survey(ACS)2018,restricted to white males residing in California with at least a bachelor’s degree.The sample is composed of17,816individuals whose age is restricted to be between25and70.UsageACSFormatA data frame with17,816rows and4variables:age age,in yearsind industry code,in four digitsbaplus1if a respondent has a master’s degree,a professional degree,or a doctoral degree;0 otherwisetopincome1if income is top-coded;0otherwiseSourcehttps:///usa/4ACS_CP ACS_CC ACS_CCDescriptionA case-control sample extracted from American Community Survey(ACS)2018,restricted to whitemales residing in California with at least a bachelor’s degree.The original ACS dataset is not from case-control sampling,but this case-control sample is obtained by the following procedure.The case sample is composed of921individuals whose income is top-coded.The control sample of equal size is randomly drawn without replacement from the pool of individuals whose income is not top-coded.Age is restricted to be between25and70.UsageACS_CCFormatA data frame with1842rows and4variables:age age,in yearsind industry code,in four digitsbaplus1if a respondent has a master’s degree,a professional degree,or a doctoral degree;0 otherwisetopincome1if income is top-coded;0otherwiseSourcehttps:///usa/ACS_CP ACS_CPDescriptionA case-population sample extracted from American Community Survey(ACS)2018,restricted towhite males residing in California with at least a bachelor’s degree.The original ACS dataset is not from case-population sampling,but this case-population sample is obtained by the following procedure.The case sample is composed of921individuals whose income is top-coded.The control sample of equal size is randomly drawn without replacement from all observations and its top-coded status is coded missing.Age is restricted to be between25and70.UsageACS_CPFormatA data frame with1842rows and4variables:age age,in yearsind industry code,in four digitsbaplus1if a respondent has a master’s degree,a professional degree,or a doctoral degree;0 otherwisetopincome1if an observation belongs to the case sample;NA otherwiseSourcehttps:///usa/avg_AR_logit An Average of the Upper Bound on Causal Attributable RiskDescriptionAverages the upper bound on causal attributable risk using prospective and retrospective logistic regression models under the monotone treatment response(MTR)and monotone treatment selection (MTS)assumptions.Usageavg_AR_logit(y,t,x,sampling="cc",p_upper=1L,length=21L,interaction=TRUE,eps=1e-08)Argumentsy n-dimensional vector of binary outcomest n-dimensional vector of binary treatmentsx n by d matrix of covariatessampling’cc’for case-control sampling;’cp’for case-population sampling;’rs’for ran-dom sampling(default=’cc’)p_upper speciﬁed upper bound for the unknown true case probability(default=1)length speciﬁed length of a sequence from0to p_upper(default=21)interaction TRUE if there are interaction terms in the retrospective logistic model;FALSE if not(default=TRUE)eps a small constant that determines the trimming of the estimated probabilities.Speciﬁcally,the estimate probability is trimmed to be between eps and1-eps(default=1e-8).ValueAn S3object of type"ciccr".The object has the following elements.est(length)-dimensional vector of the average of the upper bound of causal at-tributable riskpseq(length)-dimensional vector of a grid from0to p_upperReferencesJun,S.J.and Lee,S.(2023).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.Manski,C.F.(1997).Monotone Treatment Response.Econometrica,65(6),1311-1334.Manski,C.F.and Pepper,J.V.(2000).Monotone Instrumental Variables:With an Application to the Returns to Schooling.Econometrica,68(4),997-1010.Examples#use the ACS_CC dataset included in the package.y=ciccr::ACS_CC$topincomet=ciccr::ACS_CC$baplusx=ciccr::ACS_CC$ageresults=avg_AR_logit(y,t,x,sampling= cc )avg_RR_logit An Average of the Log Odds RatioDescriptionAverages the log odds ratio using retrospective logistic regression.Usageavg_RR_logit(y,t,x,w="control")Argumentsy n-dimensional vector of binary outcomest n-dimensional vector of binary treatmentsx n by d matrix of covariatesw’case’if the average is conditional on the case sample;’control’if it is condi-tional on the control sample;’all’if it is based on the whole sample;default w=’control’ValueAn S3object of type"ciccr".The object has the following elements.est a scalar estimate of the weighted average of the log odds ratio using retrospective logistic regressionse standard errorReferencesJun,S.J.and Lee,S.(2023).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.Examples#use the ACS_CC dataset included in the packagey=ciccr::ACS_CC$topincomet=ciccr::ACS_CC$baplusx=ciccr::ACS_CC$age#use case to condition on the distribution of covariates given y=1results=avg_RR_logit(y,t,x, case )cicc_AR Causal Inference on Attributable RiskDescriptionProvides an upper bound on the average of attributable risk under the monotone treatment response (MTR)and monotone treatment selection(MTS)assumptions.Usagecicc_AR(y,t,x,sampling="cc",p_upper=1L,cov_prob=0.95,length=21L,interaction=TRUE,no_boot=0L,eps=1e-08)Argumentsy n-dimensional vector of binary outcomest n-dimensional vector of binary treatmentsx n by d matrix of covariatessampling’cc’for case-control sampling;’cp’for case-population sampling;’rs’for ran-dom sampling(default=’cc’)p_upper a speciﬁed upper bound for the unknown true case probability(default=1) cov_prob coverage probability of a conﬁdence interval(default=0.95)length speciﬁed length of a sequence from0to p_upper(default=21)interaction TRUE if there are interaction terms in the retrospective logistic model;FALSE if not(default=TRUE)no_boot number of bootstrap repetitions to compute the conﬁdence intervals(default= 0)eps a small constant that determines the trimming of the estimated probabilities.Speciﬁcally,the estimate probability is trimmed to be between eps and1-eps(default=1e-8).ValueAn S3object of type"ciccr".The object has the following elements:est(length)-dimensional vector of the upper bounds on the average of attributable riskci(length)-dimensional vector of the upper ends of pointwise one-sided conﬁdence intervalspseq(length)-dimensional vector of a grid from0to p_uppercov_prob the nominal coverage probabilityreturn_code status of existence of missing values in bootstrap replicationsReferencesJun,S.J.and Lee,S.(2020).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.Manski,C.F.(1997).Monotone Treatment Response.Econometrica,65(6),1311-1334.Manski,C.F.and Pepper,J.V.(2000).Monotone Instrumental Variables:With an Application to the Returns to Schooling.Econometrica,68(4),997-1010.cicc_plot9Examples#use the ACS_CC dataset included in the package.y=ciccr::ACS_CC$topincomet=ciccr::ACS_CC$baplusx=ciccr::ACS_CC$ageresults_AR=cicc_AR(y,t,x,sampling= cc ,no_boot=100)cicc_plot Plotting Upper Bounds on Relative and Attributable RiskDescriptionPlots upper bounds on relative and attributable riskUsagecicc_plot(results,parameter="RR",sampling="cc",save_plots=FALSE,file_name=Sys.Date(),plots_ctl=0.3)Argumentsresults estimation results from either cicc_RR or cicc_ARparameter’RR’for relative risk;’AR’for attributable risk(default=’RR’)sampling’cc’for case-control sampling;’cp’for case-population sampling(default=’cc’)save_plots TRUE if the plots are saved as pdfﬁles;FALSE if not(default=FALSE)file_name the pdfﬁle name to save the plots(default=Sys.Date())plots_ctl value to determine the topleft position of the legend in theﬁgure a large value makes the legend far away from the conﬁdence intervals(default=0.3)ValueA X-Y plot where the X axis shows the range of p from0to p_upper and the Y axis depicts bothpoint estimates and the upper end point of the one-sided conﬁdence intervals.ReferencesJun,S.J.and Lee,S.(2020).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.10cicc_RRExamples#use the ACS_CC dataset included in the package.y=ciccr::ACS_CC$topincomet=ciccr::ACS_CC$baplusx=ciccr::ACS_CC$ageresults=cicc_RR(y,t,x)cicc_plot(results)cicc_RR Causal Inference on Relative RiskDescriptionProvides upper bounds on the average of log relative risk under the monotone treatment response (MTR)and monotone treatment selection(MTS)assumptions.Usagecicc_RR(y,t,x,sampling="cc",cov_prob=0.95)Argumentsy n-dimensional vector of binary outcomest n-dimensional vector of binary treatmentsx n by d matrix of covariatessampling’cc’for case-control sampling;’cp’for case-population sampling;’rs’for ran-dom sampling(default=’cc’)cov_prob coverage probability of a uniform conﬁdence band(default=0.95)ValueAn S3object of type"ciccr".The object has the following elements:est estimates of the upper bounds on the average of log relative risk at p=0and p=1 se pointwise standard errors at p=0and p=1ci the upper end points of the uniform conﬁdence band at p=0and p=1pseq two end points:p=0and p=1ReferencesJun,S.J.and Lee,S.(2023).Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions.https:///abs/2004.08318.Manski,C.F.(1997).Monotone Treatment Response.Econometrica,65(6),1311-1334.Manski,C.F.and Pepper,J.V.(2000).Monotone Instrumental Variables:With an Application to the Returns to Schooling.Econometrica,68(4),997-1010.DZ_CC11 Examples#use the ACS_CC dataset included in the package.y=ciccr::ACS_CC$topincomet=ciccr::ACS_CC$baplusx=ciccr::ACS_CC$ageresults_RR=cicc_RR(y,t,x,sampling= cc ,cov_prob=0.95)DZ_CC DZ_CCDescriptionCase-control sample extracted from Delavande and Zafar(2019).The sample is composed of689 students who attended either"Very Selective University"(VSU)or"Selective University"(SU).UsageDZ_CCFormatA data frame with689rows and5variables:parent_ba indicator:at least one college-educated parentprivate_school indicator:attended private school before unversityparent_inc parents’monthly income(in1000s Rs)case_sample indicator:attended"Very Selective University"(VSU)control_sample indicator:attended the other simply"Selective University"(SU)Sourcehttps:///doi/suppl/10.1086/701808/suppl_file/2014399data.zipReferencesDelavande,A.and Zafar,B.(2019).University Choice:The Role of Expected Earnings,Non-Pecuniary Outcomes,and Financial Constraints.Journal of Political Economy127(5),2343-2393.12FG FG FGDescriptionDataset from Fang and Gong(2017,2020).The original dataset in Fang and Gong(2017)is updated in Fang and Gong(2020)after Matsumoto(2020)pointed out data and coding errors in the original work.We use the updated version of the dataset.The sample is composed of78,165physicians who billed at least20hours per week.UsageFGFormatA data frame with78,165rows and5variables:male indicator:physician is maleisMD indicator:physician has a MD degreeexperYear experience in yearsﬂag indicator:physician billed for more than100hours per weeksmallPractice indicator:number of group practice members less than6SourceFang,H.and Gong,Q.(2020)Data and Code for:Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.Nashville,TN:American Economic Association[pub-lisher].Ann Arbor,MI:Inter-university Consortium for Political and Social Research[distributor], 2020-11-23.doi:10.3886/E119192V1ReferencesFang,H.and Gong,Q.(2017).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked.American Economic Review,107(2),562-91.Matsumoto,B.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Comment.American Economic Review,110(12),3991-4003.Fang,H.and Gong,Q.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.American Economic Review,110(12):4004-10.FG_CC13 FG_CC FG_CCDescriptionCase-control sample extracted from Fang and Gong(2020).The case-control sample is extracted from Fang and Gong(2020)by the following procedure.The case sample is composed of2,261ﬂagged physicians(that is,those who billed for more than100hours per week).The control sample of equal size is randomly drawn without replacement from the pool of physicians who were never ﬂagged.The sample is composed of4,522physicians who billed at least20hours per week. UsageFG_CCFormatA data frame with4,522rows and5variables:male indicator:physician is maleisMD indicator:physician has a MD degreeexperYear experience in yearsﬂag indicator:physician billed for more than100hours per weeksmallPractice indicator:number of group practice members less than6SourceFang,H.and Gong,Q.(2020)Data and Code for:Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.Nashville,TN:American Economic Association[pub-lisher].Ann Arbor,MI:Inter-university Consortium for Political and Social Research[distributor], 2020-11-23.doi:10.3886/E119192V1ReferencesFang,H.and Gong,Q.(2017).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked.American Economic Review,107(2),562-91.Matsumoto,B.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Comment.American Economic Review,110(12),3991-4003.Fang,H.and Gong,Q.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.American Economic Review,110(12),4004-10.14FG_CP FG_CP FG_CPDescriptionCase-population sample extracted from Fang and Gong(2020).The case-population sample is extracted from Fang and Gong(2020)by the following procedure.The case sample is composed of 2,261ﬂagged physicians(that is,those who billed for more than100hours per week).The control sample of equal size is randomly drawn without replacement from all observations and itsﬂagged status is coded missing.The sample is composed of4,522physicians who billed at least20hours per week.UsageFG_CPFormatA data frame with4,522rows and5variables:male indicator:physician is maleisMD indicator:physician has a MD degreeexperYear experience in yearsﬂag1if an observation belongs to the case sample;NA otherwisesmallPractice indicator:number of group practice members less than6SourceFang,H.and Gong,Q.(2020)Data and Code for:Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.Nashville,TN:American Economic Association[pub-lisher].Ann Arbor,MI:Inter-university Consortium for Political and Social Research[distributor], 2020-11-23.doi:10.3886/E119192V1ReferencesFang,H.and Gong,Q.(2017).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked.American Economic Review,107(2),562-91.Matsumoto,B.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Comment.American Economic Review,110(12),3991-4003.Fang,H.and Gong,Q.(2020).Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked:Reply.American Economic Review,110(12):4004-10.trim_pr15 trim_pr Trimming the estimates to be strictly between0and1DescriptionTrimming the estimates to be strictly between0and1Usagetrim_pr(ps,eps=1e-08)Argumentsps n-dimensional vector of estimated probabilitieseps a small constant that determines the trimming of the estimated probabilities.Speciﬁcally,the estimate probability is trimmed to be between eps and1-eps(default=1e-8).Valueps_tr n-dimensional trimmed estimatesIndex∗datasetsACS,3ACS_CC,4ACS_CP,4DZ_CC,11FG,12FG_CC,13FG_CP,14AAA_DML,2ACS,3ACS_CC,4ACS_CP,4avg_AR_logit,5avg_RR_logit,6cicc_AR,7cicc_plot,9cicc_RR,10DZ_CC,11FG,12FG_CC,13FG_CP,14trim_pr,1516。

香港理工大学深圳研究院中国会计与金融研究中心诚聘（企业咨询）项目经理／助理经理

香港理工大学深圳研究院中国会计与金融研究中心诚聘（企业
咨询）项目经理／助理经理
佚名
【期刊名称】《中国会计与财务研究》
【年(卷),期】2001(000)004
【摘要】财经专业，硕士且有三年以上相关工作经验，或本科且有六年以上相关工作经验；英文六级以上。

具备良好的专业素质和实务经验，组织协调能力强，文字策划功底好；井具有强烈的社会责任感和工作热情。

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【总页数】2页(P178-179)
【正文语种】中文
【中图分类】F270
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【期刊名称】《汽车工艺与材料》
【年(卷),期】2006(000)008
【摘要】介绍了国家《汽车产品回收利用技术政策》的主要技术内容,分析了汽车生产企业实施该技术政策的责任与义务,指出了该技术政策与欧盟《关于报废汽车的技术指令》之间的差异,提出了需要跨汽车行业商讨的主要问题,为汽车生产企业理解和实施《汽车产品回收利用技术政策》提供了方向性的指导.
【总页数】4页(P32-35)
【作者】李名林;刘丽娟
【作者单位】泛亚汽车技术中心有限公司,上海,201201;如新华茂光电技术(上海)有限公司,上海,201201
【正文语种】中文
【中图分类】F4
【相关文献】
1.汽车产品回收利用技术政策 [J],
2.解读《汽车产品回收利用技术政策》 [J], 李名林;刘丽娟
3.解读《汽车产品回收利用技术政策》 [J], 吴勇
4.《汽车产品回收利用技术政策》研读 [J], 李名林
5.实施《汽车产品回收利用技术政策》后的汽车用纺织品开发方向 [J], 陈榕;廖启标;毛翊;顾钰良
因版权原因，仅展示原文概要，查看原文内容请购买。

IA财务考

IA财务考
佚名
【期刊名称】《新理财：公司理财》
【年(卷),期】2012()5
【摘要】＂模糊、战战兢兢、雷区＂,这是一位实务界CFO在谈到无形资产（IA,Intangible assets的简称）时,使用的关键词。

而另一位一家大型国企的CFO也指出,忽视它,就只能交＂学费＂,甚至会血本无归。

【总页数】4页(P50-53)
【关键词】考卷;财务;IA;无形资产;大型国企;CFO;关键词;实务
【正文语种】中文
【中图分类】F275
【相关文献】
1.合阳方言“[ia24]姑”考 [J], 王三敏
2.浅议IAS 34中期财务报表新准则的应用 [J], 常金莲
3.IA财务考——IA：CFO“有形”考卷 [J],
4.争议IA“财务纠结” [J],
5.四川方言[_c ia _c in]本字考 [J], 谭伦华
因版权原因，仅展示原文概要，查看原文内容请购买。

控制与信息融合——制造企业参考架构

控制与信息融合——制造企业参考架构
华镕
【期刊名称】《软件》
【年(卷),期】2009(000)012
【摘要】@@ 在工厂中,控制与信息都采用EtherNet/IPTM,这就导致了工业企业广泛地使用标准的以太网.这种部署使得制造网络与企业网络的融合成为可能.【总页数】4页(P47-50)
【作者】华镕
【作者单位】
【正文语种】中文
【相关文献】
1.小型无人机姿态航向参考系统信息融合算法 [J], 代君;任淑红;王晓璐
2.制造企业参考架构 [J], 华镕
3.制造企业参考架构中的软件 [J], 华镕
4.罗克韦尔自动化发布参考架构的重要扩展，帮助生产商设计全厂范围的EtherNet／IP架构 [J],
5.基于物联网六域模型的人体感知\r信息融合参考体系结构探究 [J], 何艾玲;沈杰;王耀梁;刘丽
因版权原因，仅展示原文概要，查看原文内容请购买。

金融全球化背景下的我国金融业人力资源管理

金融全球化背景下的我国金融业人力资源管理
张付香
【期刊名称】《征信》
【年(卷),期】2003(021)005
【摘要】加入WTO后,我国金融全球化的进程日益加快,我国金融业人力资源管理面临着严峻的挑战.为此,我国金融业应采取更新观念,转换工作方式;深化内部改革,建立科学合理的激励机制;加强人才培养和培训等措施,积极应对挑战.
【总页数】2页(P63-64)
【作者】张付香
【作者单位】中国人民银行郑州培训学院,河南,郑州,450002
【正文语种】中文
【中图分类】F830.33
【相关文献】
1.金融全球化下我国金融业面临的挑战及对策 [J], 袁艳辉;李伟;肖华蓉
2.金融全球化下我国金融业面临的风险及防范 [J], 茆仲义
3.经济全球化背景下我国金融业r混业经营的探讨 [J], 郑晓栩
4.全球化背景下的我国金融业发展 [J], 南晓莉
5.金融全球化下我国金融业面临的风险及防范措施 [J], 王娇;聂肖萼
因版权原因，仅展示原文概要，查看原文内容请购买。

中文PRM考试指南

成为行业观点的权威和风险管理行业的典范
■ 通过设置较高的风险认证标准，我们建立了操作准则和衡量标准，这些将决定国际风险管理师给他们的同事和雇主带来什么。
推动理论和实践相结合
■ 没有各领域专家之间的强势互动，光靠理论或只有实践是不能成功朝着最大潜能目标发展的。国际风险管理师认证包含从风险管理理论、金融理论、风险度量基础数学得出的课题和从行业实践产生的应用问题。我们将直接对金融和基础数学知识进行测验。这些知识是风险管理师所不可或缺的，因为它们是风险度量和管理的基础。
6
考试考方试式设计和制度
考试费和注册
中文PRM考试每月进行一科的考试，详细考试时间请访问PRMIA中国认证中心网址：。目前PRM中文考试可以在北京、上海、广州、台北等中心城市参加。
中文PRM考试，PRMIA采用ATA提供的服务实施电子考试。ATA是世界领先的考试服务专家，中国规模最大的专业化考试与测评服务公司；是最优秀的基于评价技术的在线学习方案供应商。
中文PRM考试指南
风险管理行业最高认证
2010年3月更新 PRMIA中国认证中心
目录
3
概述
4
考试设计
5
考试方式和制度
7
费用和注册
8
参加PRM考试
10 PRM课程大纲
13 备考PRM
18 常见问题
2
国际风险管理师考试指南
概述
PRM是为专业的风险管理者量身定做的高端认证考试，已得到众多世界顶尖大学和行业机构的共同认可，现已成为风险管理从业资质的国际标准。 PRM考试由众多行业领导者建立，反映了协会的使命目标，确立了风险管理行业的领先教育、审核和认证机制。PRM吸引了超过95个国家和地区的考生，比世界任何地方的其他风险认证课程都要多。 PRM资格认证的学习目标在于掌握以下几个方面的知识：