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Predictive Modeling: An Optimized and Dynamic Solution Framework for Systematic Value Investing

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  • R. J. Sak

Abstract

This paper defines systematic value investing as an empirical optimization problem. Predictive modeling is introduced as a systematic value investing methodology with dynamic and optimization features. A predictive modeling process is demonstrated using financial metrics from Gray & Carlisle and Buffett & Clark. A 31-year portfolio backtest (1985 - 2016) compares performance between predictive models and Gray & Carlisle's Quantitative Value strategy. A 26-year portfolio backtest (1990 - 2016) uses an expanded set of predictor variables to show financial performance improvements. This paper includes secondary novel contributions. Quantitative definitions are provided for Buffett & Clark's value investing metrics. The "Sak ratio" is proposed as an extension to the Benjamini-Hochberg procedure for the inferential identification of false positive observations.

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  • R. J. Sak, 2017. "Predictive Modeling: An Optimized and Dynamic Solution Framework for Systematic Value Investing," Papers 1709.03226, arXiv.org.
    • Handle: RePEc:arx:papers:1709.03226
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    References listed on IDEAS

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    1. Randolph B. Cohen & Christopher Polk & Tuomo Vuolteenaho, 2003. "The Value Spread," Journal of Finance, American Finance Association, vol. 58(2), pages 609-641, April.
    2. Piotroski, JD, 2000. "Value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 1-41.
    3. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
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