Quantitative Asset Management Quantitative Asset Management Most math








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Quantitative Asset Management
Quantitative Asset Management Most math departments now offer finance courses 2007 2010: 61% decline in AUM Reflects loss of clients + poor performance Different varieties: hedge funds, 130/30, long only They differ in trading frequency/portfolio turnover Quantitative hedge fund 1 in 4 has closed since 2007 Negative impact of Bear Stearns, Lehman (prime brokers for many funds) 2 2022 -01 -11
Recent Criticisms of Quantitative Management The quant space is too crowd By and large the same story: value, momentum, small tilt Reliance of historical data and similar statistical methods Returns highly correlated any value added has been competed away 3 2022 -01 -11
LSV’s Response May 2010 article Research questions: Is there more crowding among quantitative managers compared to discretionary managers? How does the information ratio (industry version) between the two groups compare over time? Does the style (value/momentum. . etc. ) differ significantly between the two groups? 4 2022 -01 -11
Data Database: e. Vestment Alliance, launched in 2000 Monthly data, widely used by consultants in manager 5 searches Self-reported data, back-filled bias Long-only institutional managers, large cap, EAFE (i. e. , LSV’s universe) Managers self identify as either fundamental or quantitative Style is self reported, but consultants will typically perform a holdings-based or returns-based analysis to confirm 2022 -01 -11
Summary of Findings Sample period: 1995 -2009 Quantitative AUM US large cap has been stable at ~ 16% Number of quantitative firms Percentage of total stable at ~29% Average pairwise correlation of value added Low and comparable to fundamental managers Dispersion of in performance exists among quantitative managers 6 2022 -01 -11
Summary of Findings Quantitative managers have bigger exposure to momentum Place a larger weight on momentum in ranking stocks Poor recent relative performance can be explained by this difference to a large extent From Ken French’s data library: 7 Mkt-Rf SMB HML Mom 2006 11. 40 0. 50 14. 34 -7. 83 2007 2. 63 -8. 21 -12. 48 21. 38 2008 -39. 96 4. 18 1. 01 13. 39 2009 31. 58 7. 90 -5. 15 -83. 36 2010 17. 96 14. 02 -3. 59 5. 85 2022 -01 -11
Annual Factors (%) 1927 -2010 8 Mkt-RF SMB HML RF Mom Arithmetic mean 8. 04 3. 76 4. 87 3. 67 9. 73 Geometric mean 5. 85 2. 83 3. 92 3. 62 7. 69 S. D. 20. 95 14. 27 13. 97 3. 11 15. 95 2022 -01 -11