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Multi-Factor Sector Based Investment Strategy (MFSS)

STAT 682 Quantitative Financial Analytics STATISTICS. Multi-Factor Sector Based Investment Strategy (MFSS). Team Ichiban: Wei Fu, Dingyi Li, Fei Ni, Taliya Perera, Benjamin Tang 28 th November 2011. STAT 682 Quantitative Financial Analytics STATISTICS. Scope:

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Multi-Factor Sector Based Investment Strategy (MFSS)

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  1. STAT 682 Quantitative Financial Analytics STATISTICS Multi-Factor Sector Based Investment Strategy (MFSS) Team Ichiban: Wei Fu, Dingyi Li, Fei Ni, Taliya Perera, Benjamin Tang 28th November 2011

  2. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Benchmarks & Back-testing the Fund’s Strategy Returns and Results Conclusion

  3. STAT 682 Quantitative Financial Analytics STATISTICS Fund Investment Strategy The Original: O’Shaugnessey Multi-factor Strategy • Price-to-Earnings (PE) ratio between 0 and 20, then selecting Best One-Year Performers (Top 50). • Price-to-Book (PB) ratio less than 1, then selecting One-Year Performers (Top 50). • Price-to-Sales (PSR) ratio less than 1, then selecting One-Year Performers (Top 50).

  4. STAT 682 Quantitative Financial Analytics STATISTICS Fund Investment Strategy Multi-Factor Sector Based Strategy • Why did we add Sector Analysis to O’Shaugnessy’s method? Correlation trades, Proxy trades, Complementary growth, Difference of inter-sector indicator norms. Growth is under-represented in his model; relative to momentum and value. • How did we add Sector component into the strategy? The top 50 stocks in each of the multifactor model are identified. Sector proportion (Ps) of the top 50 stocks are compared against the (Pu) of the entire universe. Sectors are then ranked by highest “Ps - Pu”.

  5. STAT 682 Quantitative Financial Analytics STATISTICS Fund Investment Strategy 3 Different MFSS Approaches • Top 10 stocks using the original approach, plus the top 5 stocks from the highest ranked sector. (Total of 15 stocks). • Top 15 stocks using the original approach, with stocks in the highest ranked sectors (if any) given double weight. • Top 3 stocks each from the 5 highest ranked sectors.

  6. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Benchmarks & Back-testing the Fund’s Strategy Returns and Results Conclusion

  7. STAT 682 Quantitative Financial Analytics STATISTICS Data Management Process • Wharton Research Data Services (WRDS) - Compustat Fundamentals Annual - CRSP Monthly Stock File • Annual Returns of Portfolios - Dividends included - Adjusted for AJEX (Splits and Such) - Accounted for data lags (April 1st Rebalancing) • Other Adjustments/Assumptions - March Month-End price close used. (CAPM assumption of sorts) - Brokerage (1% hit p.a. in 1970s – 80s, $450 p.a. thereafter.) - Tax deferred investment account. - Delisting and Acquisitions

  8. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Benchmarks & Back-testing the Fund’s Strategy Returns and Results Conclusion

  9. STAT 682 Quantitative Financial Analytics STATISTICS Portfolio Selection Mechanism: • General Procedure - Recreate O’Shaugnessey’s ranking (by previous returns) for each of the three segments in his portfolio. - Calculate the Ps – Pu for each of the three segments. - Apply it to generate the portfolios for the fund’s strategy.

  10. STAT 682 Quantitative Financial Analytics STATISTICS Sample Portfolios (1975):

  11. STAT 682 Quantitative Financial Analytics STATISTICS Sample Portfolios (1985):

  12. STAT 682 Quantitative Financial Analytics STATISTICS Sample Portfolios (1995):

  13. STAT 682 Quantitative Financial Analytics STATISTICS Sample Portfolios (2005):

  14. STAT 682 Quantitative Financial Analytics STATISTICS Sample Portfolios (2009):

  15. STAT 682 Quantitative Financial Analytics STATISTICS Sector Weights:

  16. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Benchmarks & Back-testing the Fund’s Strategy Returns and Results Conclusion

  17. STAT 682 Quantitative Financial Analytics STATISTICS Creating Benchmarks Compared against: - O’Shaugnessey’s Reduced Portfolio Returns - NYSE/S&P Returns - Against the other Sector-based Strategies

  18. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Benchmarks & Back-testing the Fund’s Strategy Returns and Results Conclusion

  19. STAT 682 Quantitative Financial Analytics STATISTICS Returns and Results (Seed Capital = $10k)

  20. STAT 682 Quantitative Financial Analytics STATISTICS Returns and Results (Seed Capital = $10k)

  21. STAT 682 Quantitative Financial Analytics STATISTICS Returns: Summary Statistics

  22. STAT 682 Quantitative Financial Analytics STATISTICS Annual Returns:

  23. STAT 682 Quantitative Financial Analytics STATISTICS 5 Year Rolling Returns:

  24. STAT 682 Quantitative Financial Analytics STATISTICS 10 Year Rolling Returns:

  25. STAT 682 Quantitative Financial Analytics STATISTICS Returns: “Beating Ratios”

  26. STAT 682 Quantitative Financial Analytics STATISTICS Scope: Fund Investment Strategy Dataset Management Process Portfolio Selection Mechanism Creating Benchmarks Back-testing the Fund’s Strategy Conclusion

  27. STAT 682 Quantitative Financial Analytics STATISTICS • Conclusion: • Advantages of the MFSS Investment Strategies • Downside Risks • Schumpeterian Theory of Growth • Back-testing as Optimization of Hindsight • Leverage as a matter of Preference

  28. STAT 682 Quantitative Financial Analytics STATISTICS Questions?

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