Shift in Factor Investing: An Empirical Study in India

Vol 10 , Issue 2 , July - December 2023 | Pages: 75-98 | Research Paper

Article has been added to the cart.View Cart (0)

https://doi.org/10.17492/jpi.mudra.v10i2.1022305

Published Online: December 10, 2023

Author Details ( * ) denotes Corresponding author

1. * Kumar Bijoy, Associate Director, Department of Distance and Continuing Education, University of Delhi, NEW DELHI, Delhi, India (associatedirector@col.du.ac.in)

2. Aman Kedia, senior consultant, Quantitative Advisory Services, Ernst & Young , London, London, United Kingdom (aman.kedia1111@gmail.com)

The study during back-testing on individual factors and the alpha model finds the significant existence of abnormal return opportunities in the Indian market. For developing alpha models, Sharpe ratio, advanced optimization techniques such as multiple regression and support vector machine have been used with Macroeconomic variables as explanatory variables. Alpha models have provided better results than individual factors regarding performance statistics. This study also considers survivorship, forward-looking, and confirmation biases to make results more applicable for investment decisions and addresses different anomalies like low volatility, size, etc. Lastly, we have observed factors’ behavior and opportunities during the normal market regime and tilt in factor investing from the long-short to more implementable side of the long-only portfolio from the 2008 global crisis to post-demonetization to the (Covid-19) pandemic era. Finally, using the factor picking model, investment strategies have been suggested. Hence, market players may benefit from such opportunity gaps.

Keywords

Portfolio Management; Back-testing; Factor Investing; Multiple Regression; Support Vector Machine (SVM); Survivorship Bias

Agarwal, U. (2016). Factor risk premia in the Indian market. Asia Index Pvt Ltd. Retrieved from: https://www.asiaindex.co.in/documents/research/Factor%20Risk%20Premia%20in%20the%20Indian%20Market.pdf
Agarwalla, S. K., Jacob, J. & Varma, J. R. (2017). Size, value, and momentum in Indian equities. VIKALPA: The Journal for Decision Makers, 42(4), 211–219.
Agarwalla, S. K., Jacob, J., & Varma, J. R. (2013). Four-factor model in Indian equities market. Retrieved from http://www.iima.ac.in-/~iffm/Indian-Fama-French-Momentum/four-factors India-90s-onwards-IIM-WP-Version.pdf
Amenc, N., Esakia, M., Goltz, F. & Luyten, B. (2019). Macroeconomic risks in equity factor investing. The Journal of Portfolio Management, 45(6), 39-60.
Andrew, A., Hodrick, R. J., Xing, Y. & Zhang, X. (2006). The cross-section of volatility and expected returns. The Journal of Finance, 61(1), 259–299.
Andrew, A., Hodrick, R. J., Xing, Y. & Zhang, X. (2009). High idiosyncratic volatility and low returns: International and further U.S. evidence. Journal of Financial Economics, 91(1), 1-23.
Bahl, B. (2006). Testing the Fama and french three-factor model and its variants for the Indian Stock Returns. Retrieved from http://dx.doi.org/10.2139/ssrn.950899
Baker, M. P., Bradley, B. & Taliaferro, R. (2013). The low risk anomaly: A decomposition into micro and macro effects financial analysts journal. Retrieved from http://dx.doi.org/10.2139/ssrn.2210003
Barberis, N. (2013). The psychology Pf tail events: Progress and challenges. American Economic Review, 103(3), 611-616.
Basu, S. (1983). The relationship between earnings yield, market value and return for NYSE common stocks: Further evidence. Journal of Financial Economics, 12(1), 129-156.
Bender, J., Briand, R., Melas, D., & Subramanian, R. A. (2013b). Foundations of factor investing. Retrieved from http://dx.doi.org/10.2139/ssrn.2543990
Bender, J., Briand, R., Melas, D., Subramanian, R. A., & Subramanian, M. (2013a). Deploying multi-factor index allocations in institutional portfolios. Research Insight, MSCI. Retrieved from https://www.msci.com/documents/1296102/1336482/Deploying_Multi_Factor_Index_Allocations_in_Institutional_Portfolios.pdf/857d431b-d289-47ac-a644-b2ed70cbfd59
Blitz, D. & Vidojevic, M. (2019). The characteristics of factor investing. The Journal of Portfolio Management Quantitative Special Issue, 45(3), 69-86.
Bollerslev, T., Todorov, V. & Xu, L. (2015). Tail risk premia and return predictability. Journal of Financial Economics, 118(1), 113-134.
Carhart, M. (1997). On persistence on mutual fund performance. The Journal of Finance, 52(1), 57–82.
Cerniglia, J. A., Fabozzi, F. J., Kolm, P. N. (2016). Best practices in research for quantitative equity strategies. Journal of Portfolio Management, Quantitative, 42(5), 135-143.
Chan, L. K. C., Jegadeesh, N. & Lakonishok, J. (1995). Momentum Strategies. NBER Working Paper No. w5375.
Clarke, R., de Silva, H., & Thorley, S. (2016). Fundamentals of efficient factor investing. Financial Analysts Journal, 72(6), 9–26.
Cooper, M. J., Gulen, H., & Schill, M. J. (2008). Asset growth and the cross-section of stock returns. The Journal of Finance, 63(4), 1609-1651.
DeMiguel, V., Martin-Utrera, A. & Uppal, R. (2019). What alleviates crowding in factor investing? Crowding and liquidity provision in factor investing. Retrieved from https://dx.doi.org/10.2139/ssrn.3392875
Fama, E. F. & French, K. (2016). Dissecting anomalies with a five-factor model. Review of Financial Studies, 29(1), 69–103.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417.
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, American Finance Association, 47(2), 427-465.
Frazzini, A. & Pedersen, H. L. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
Freyberger, J., Neuhierl, A. & Weber, M. (2017). Dissecting characteristics non-parametrically. National Bureau of Economic Research, Working Paper 23227. Retrieved from https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.nber.org%2Fpapers%2Fw23227.pdf;h=repec:nbr:nberwo:23227
Gelderen, E. V., Huij, J. & Kyosev, G. (2019). Factor investing from concept to implementation. The Journal of Portfolio Management Quantitative Special Issue, 45(3), 125-140.
Gönen, M. & Alpadın, E. (2011). Multiple kernel learning algorithms. Journal of Machine Learning Research, 1, 2211-2268.
Gupta, T. & Kelly, B. T. (2019). Factor momentum everywhere. Journal of Portfolio Management, Quantitative, Special Issue 2019, 45(3), 13-36.
Haugen, R. A. & Baker, N. L. (1996). Commonality in the determinants of expected stock returns. Journal of Financial Economics, Elsevier, 41(3), 401-439.
Jegadeesh, N. & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48, 65-91.
Jegadeesh, N. & Titman, S. (2001). Profitability of momentum strategies: An evaluation of alternative explanations. The Journal of Finance, 56(2), 699–720.
Kelly, B. & Jiang, H. (2014). Tail risk and asset prices. The Review of Financial Studies, 27(10), 2841-2871.
Kenneth, R. G., Schwert, W. & Stambaugh, R. F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19(1), 3-29.
Koedijk, K., Slager, A., & Stork, P. (2016). A trustee guide to factor investing. The Journal of Portfolio Management, 42(5), 28–38.
Kolm, P. N. & Ritter, G. (2021). Factor investing with Black–Litterman–Bayes: Incorporating factor views and priors in portfolio construction. The Journal of Portfolio Management Quantitative Special Issue, 47(2) 113-126.
Li, F., Chow, T.-M., Pickard, A. & Garg, Y. (2019). Transaction costs of factor-investing strategies. Financial Analysts Journal, 75(2), 62-78.
Litzenberger, R. H. & Ramaswamy, K. (1982). The effects of dividends on common stock prices tax effects or information effects? The Journal of Finance, 37(2), 429–443.
Loughran, T. & Wellman, J. W. (2011). New evidence on the relation between the enterprise multiple and average stock returns. The Journal of Financial and Quantitative Analysis, 46(6), 1629–1650.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Penman, S. H., Richardson, S. A. & Tuna, A. I. (2007). The book-to-price effect in stock returns: Accounting for leverage. Journal of Accounting Research, 45(2), 427–467.
Roy, A. D. (1952). Safety first and the holding of assets. Econometrica, 20(3), 431-449.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425–442.
Shefrin, H. (2005). Behavioral corporate finance. Journal of Applied Corporate Finance, 14(3), 113-126.
Shimizua, H. & Shiohama, T. (2020). Constructing inverse factor volatility portfolios: A risk-based asset allocation for factor investing. International Review of Financial Analysis. Retrieved from https://doi.org/10.1016/j.irfa.2019.101438
Soliman, M. T. (2008). The use of DuPont analysis by market participants. The Accounting Review, 83(3), 823–853.
Su, C. (2021). A comprehensive investigation into style momentum strategies in China. Financial Markets and Portfolio Management, 35, 101–144.
Sugitomo, S. & Minami, S. (2018). Fundamental factor models using machine learning. Journal of Mathematical Finance. Retrieved from https://dx.doi.org/10.2139/ssrn.3322187
Thaler, R. H., Sunstein, C. R. & Balz, J. P. (2014). Choice architecture. The behavioral foundations of public policy. Retrieved from https://dx.doi.org/10.2139/ssrn.2536504
Wen, Z., Shi, J., Li, Q., & Bingsheng. C. J. (2018). ThunderSVM: A fast SVM library on GPUs and CPUs. Journal of Machine Learning Research, 1, 1-5.
Wilmott, P. (2000). The use, misuse and abuse of mathematics in finance. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, 358(1765), 63-73.