QUESTIONS

1. What is the purpose of estimating model risk?
2. How is behavioral modeling used?
3. What are some of the reasons for the greater use of optimization techniques?
4. What are meant by a fundamental, quantitative, and hybrid investment processes?
5. 1. Why are adaptive modeling techniques used by quantitative equity managers?
   2. Describe several examples of adaptive modeling techniques and the challenge in using them.
6. What is meant by “performance decay”?
7. How has the execution process undergone important changes in recent years?

¹ In the quotes from sources in these studies, we omit the usual practice of identifying the reference and page number. The study where the quote is obtained will be clear.

² The results of this study are reported in Frank J. Fabozzi, Sergio M. Focardi, and Caroline L. Jonas, “Trends in Quantitative Asset Management in Europe,” Journal of Portfolio Management 31, no. 4 (2004): 125–132 (Special European Section).

³ This statement is not strictly true. With the availability of high-frequency data, there is a new strain of financial econometrics that considers volatility as an observable realized volatility.

⁴ For a discussion of the different families of financial models and modeling issues, see Sergio M. Focardi and Frank J. Fabozzi, The Mathematics of Financial Modeling and Investment Management (Hoboken, NJ: John Wiley & Sons, 2004).

⁵ François Longin,“Stock Market Crashes: Some Quantitative Results Based on Extreme Value Theory.” Derivatives Use, Trading and Regulation 7, no. 3 (2001): 197–205.

⁶ Asset management firms are subject to other risks, namely, the risk of not fulfilling a client mandate or operational risk. Although important, these risks were outside the scope of the survey.

⁷ The results of this study are reported in Frank J. Fabozzi, Sergio M. Focardi, and Caroline Jonas, “Trends in Quantitative Equity Management: Survey Results,” Quantitative Finance 7, no. 2 (2007): 115–122.

⁸ The home market of participating firms was a follows: 15 from North America (14 from the United States, 1 from Canada) and 23 from Europe (7 from United Kingdom, 5 from Germany, 4 from Switzerland, 3 from Benelux, 2 from France, and 2 from Italy).

⁹ Of the 38 participants in this survey, two responded only partially to the questionnaire. Therefore, for some questions, there are 36 (not 38) responses.

¹⁰ Emanuel Derman, “A Guide for the Perplexed Quant,” Quantitative Finance 1, no. 5 (2001): 476–480.

¹¹ Narasimhan Jegadeesh and Sheridan Titman, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” Journal of Finance 48, no. 1 (1993): 65–92.

¹² Narasimhan Jegadeesh and Sheridan Titman, “Cross-Sectional and Time-Series Determinants of Momentum Returns,” Review of Financial Studies 15, no. 1 (2002): 143–158.

¹³ George A. Karolyi and Bong-Chan Kho, “Momentum Strategies: Some Bootstrap Tests,” Journal of Empirical Finance 11 (2004): 509–536.

¹⁴ The term behavioral modeling is often used rather loosely. Full-fledged behavioral modeling exploits a knowledge of human psychology to identify situations where investors are prone to show behavior that leads to market inefficiencies. The tendency now is to call behavioral any model that exploits market inefficiency. However, implementing true behavioral modeling is a serious challenge; even firms with very large, powerful quant teams who participated in the survey reported that there is considerable work needed to translate departures from rationality into a set of rules for identifying stocks as well as entry and exit points for a quantitative stock selection process.

¹⁵ The results of this study are reported in Frank J. Fabozzi, Sergio M. Focardi, and Caroline Jonas, Challenges in Quantitative Equity Management (Charlottesville, VA: CFA Institute Research Foundation, 2008); and Frank J. Fabozzi, Sergio M. Focardi, and Caroline L. Jonas, “On the Challenges in Quantitative Equity Management.” Quantitative Finance 8, no. 7 (2008): 649–655.

¹⁶ Soosung Hwang and Alexandre Rubesam, “The Disappearance of Momentum” (November 7, 2008). Available at SSRN: http://ssrn.com/abstract=968176.

¹⁷ Ilya Figelman, “Stock Return Momentum and Reversal,” Journal of Portfolio Management 34, no. 1 (2007): 51–69.

¹⁸ Amir E. Khandani and Andrew W. Lo, “What Happened to the Quants in August 2007,” Journal of Investment Management 5, no. 4 (2007): 29–78.

¹⁹ Eugene F. Fama and Kenneth R. French, “Common Risk Factors and the Returns on Stocks and Bonds,” Journal of Financial Economics, 47, no. 2 (1993): 427–465.

²⁰ Khandani and Lo, “What Happened to the Quants in August 2007?”.

²¹ Casey, Quirk and Associates, “The Geeks Shall Inherit the Earth?” November 2005.

²² As reported in Michael Lewis, Moneyball: The Art of Winning an Unfair Game (New York: Norton, 2003).

²³ Heping Pan, Dider Sornette, and Kenneth Kortanek, “Intelligent Finance—An Emerging Direction.” Quantitative Finance 6, no. 4 (2006): 273–277.

²⁴ Robert C. Merton, “An Intertemporal Capital Asset Pricing Model,” Econometrica 41, no. 5 (1973): 867–887.

²⁵ For the theoretical underpinning of bounded rationality from a statistical point of view, see Thomas J. Sargent, Bounded Rationality in Macroeconomics (New York: Oxford University Press, 1994). For the theoretical underpinning of bounded rationality from a behavioral finance perspective, see Daniel Kahneman, “Maps of Bounded Rationality: Psychology for Behavioral Economics,” American Economic Review 93, no. 5 (2003): 1449–1475. For a survey of research on computational finance with boundedly rational agents, see Blake LeBaron, Agent-Based Computational Finance”, in Handbook of Computational Economics, edited by Leigh Tesfatsion and Kenneth L. Judd (Amsterdam: North-Holland, 2006).

²⁶ For a review of the issues and opportunities associated with high-frequency trading, see Frank J. Fabozzi, Sergio M. Focardi, and Caroline Jonas, “High-Frequency Trading: Methodologies and Market Impact,” Review of Futures Markets, 19 (2011): 7–38.

²⁷ Sergio M. Focardi and Frank J. Fabozzi, “A Percolation Approach to Modeling Credit Loss Distribution Under Contagion,” Journal of Risk 7, no. 1 (2004): 75–94.

²⁸ Andrew G. Haldane, “Rethinking the Financial Network,” Speech to the Financial Student Association in Amsterdam (April 28, 2009).