Challenges in Quantitative Equity Management

Which investment style make a good performance?
1. Indicates that the search to identify new and/or unique factors was the most frequently cited strategy; complementary to it was the intention to use new models. 2. Regression is the state of the art of today’s toolkit. To get better performance, we will have to enlarge the tool kit and add information and dynamic and static models. People are always changing things; maybe we will be changing things just a bit quicker. 3. A good trading algorithm collapsed to three to four years in the mid-1990s and has now collapsed to just two to three months (Urstadt 2007). Berman added that he expects to see the life cycle of a successful algorithm continue to drop.
Percentage of survey participants using numerical only, both numerical and rule-based, and only rule-based modeling approaches
Rule Based Only Numerical Only Numerical and Rule Based
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How do you capture more information?
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There is no simple formula, everything is unique. To understand the process, you need to know the philosophy and understand how it performs in specific markets-for example, in markets that are trending up, down, or sideways. You need to understand what drives the returns. We have seen many processes that are very simple but work and others that are complex and do not work. A quantitative process is a process that quantifies things. Experience has shown that a pure data-mining approach—at least at the level of mining time series of equity returns—is not feasible. In our multifactor quantitative model, there is a focus on fundamental factors. These account for 90 percent of the factors in our approach; technical factors account for the remaining 10 percent of the factors
2. .Some sources cited the fact that quantitative funds are based on a more complex process than fundamental funds and so are harder to explain and more difficult to sell to investors. The successful active fundamental manager is almost like a machine: He does not fall in love with a stock or a CFO and he admits mistakes. Quant products are unglamorous. There are no ‘story ’ stocks, so it makes it a hard sell for consultants to their clients. Quant do not hit the ball out of the park, but they deliver stable performance.
What is a quantitative investment management process?
Input system
Forecasting engine
Portfolio construction engine
Dose that fundamental overlay add value to the quantitative process?
Relative strength of selling points of a quantitative products as rated
Statistics-Based Stock Selection Lower Trading Costs Lower Management Fees Nondiscretionary No style drift Greater Diversification Rule-Based Process Transparent Process Better risk management Enhanced Investment Discipline Alpha Generation
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Diversification
Improve performance Ensure more stable returns Tighter risk control
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What is the selling point of market quantitative pquantitative process?
1. The most compelling finding was that quant managers outperformed fundamental managers with half risk. Quant managers as a group are better at quantifying the all-around risks and what is likely to go wrong. Quant has an advantage when there is an element of financial engineering. The investment process is the same, but quant adds value when it comes to picking components and coming up with products such as 130-30. This profitability comes from the fact that (1) a quant process can be scaled to different universes all run by the same team and (2) a quant process allows more strategies about when and how to trade.
Response to: The most effective equity portfolio management process combines quantitative tools and a fundamental overlay
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Factors behind a firm’s motivation to adopt(at least partially) a quantitatively driven equity investment management process
Reduce Management costs Improve cost-to-revenues ratio Stabilize costs,revenues,performance Add new products Investor Demand Scalabity Profile of Founders/In-House Culture
Challenges in Quantitative Equity Management
Wenlong Jiao Oct.2010
What is Quant future in the industry?
• Most quant were value investors. • Models will run the entirety of the investment management process? • All models make forecasts (based on trend following). • It is a fool buying under the assumption that a bigger fool will buy in the future. • Active management is still a zero-sum game.