State-dependent asset allocation using neural networks

Bradrania, Reza and Pirayesh Neghab, Davood (2021): State-dependent asset allocation using neural networks. Published in: European Journal of Finance , Vol. 28, No. 11 (12 August 2021): pp. 1130-1156.

Abstract

Changes in market conditions present challenges for investors as they cause performance to deviate from the ranges predicted by long-term averages of means and covariances. The aim of conditional asset allocation strategies is to overcome this issue by adjusting portfolio allocations to hedge changes in the investment opportunity set. This paper proposes a new approach to conditional asset allocation that is based on machine learning; it analyzes historical market states and asset returns and identifies the optimal portfolio choice in a new period when new observations become available. In this approach, we directly relate state variables to portfolio weights, rather than firstly modeling the return distribution and subsequently estimating the portfolio choice. The method captures nonlinearity among the state (predicting) variables and portfolio weights without assuming any particular distribution of returns and other data, without fitting a model with a fixed number of predicting variables to data and without estimating any parameters. The empirical results for a portfolio of stock and bond indices show the proposed approach generates a more efficient outcome compared to traditional methods and is robust in using different objective functions across different sample periods.

• Item Type: MPRA Paper
• Language: English
• Keywords: asset allocation; portfolio optimization; market state, machine learning; neural networks; performance ratio
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C55 - Large Data Sets: Modeling and Analysis; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G0 - General; G - Financial Economics > G1 - General Financial Markets; G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions; G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

References

Agarwal, Vikas, and Narayan Y. Naik. 2004. “Risks and Portfolio Decisions Involving Hedge Funds.” The Review of Financial Studies 17 (1), 63–98.

Ait-Sahalia, Yacine, and Michael W. Brandt. 2001. “Variable Selection for Portfolio Choice.” The Journal of Finance 56 (4), 1297–1351.

Alpaydin, Ethem. 2004. “Introduction to Machine Learning (Adaptive Computation and Machine Learning).” The MIT Press. Ang, Andrew, and Geert Bekaert. 2004. “How Regimes Affect Asset Allocation.” Financial Analysts Journal 60 (2), 86–99.

Barberis, Nicholas. 2000. “Investing for the Long Run When Returns Are Predictable.” The Journal of Finance 55 (1), 225–64.

Bazaraa, Mokhtar S., Hanif D. Sherali, and Chitharanjan M. Shetty. 2013. “Nonlinear Programming: Theory and Algorithms.” John Wiley & Sons.

Bekaert, Geert, and Robert J. Hodrick. 1992. “Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets.” The Journal of Finance 47 (2), 467–509.

Biglova, Almira, Sergio Ortobelli, Svetlozar T. Rachev, and Stoyan Stoyanov. 2004. “Different Approaches to Risk Estimation in Portfolio Theory.” The Journal of Portfolio Management 31 (1), 103–12.

Bollerslev, Tim. 1986. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics 31 (3), 307–27.

Bollerslev, Tim, Robert F. Engle, and Jeffrey M. Wooldridge. 1988. “A Capital Asset Pricing Model with Time-Varying Covariances.” Journal of Political Economy 96 (1), 116–31.

Brandt, Michael W., and Pedro Santa-Clara. 2006. “Dynamic Portfolio Selection by Augmenting the Asset Space.” Journal of Finance 61, 2187–218.

Brandt, Michael W., Pedro Santa-Clara, and Rossen Valkanov. 2009. “Parametric Portfolio Policies: Exploiting Characteristics in the Cross-section of Equity Returns.” Review of Financial Studies 22 (9), 3411–3447.

Breiman, Leo. 2001. “Random Forests.” Machine Learning 45, 5–32.

Brennan, Michael J., Eduardo S. Schwartz, and Ronald Lagnado. 1997. “Strategic Asset Allocation.” Journal of Economic Dynamics and Control 21, 1377–1403.

Brennan, Michael J., Eduardo S. Schwartz, and Ronald Lagnado. 1999. “The Use of Treasury Bill Futures in Strategic Asset Allocation Programs.” Worldwide Asset and Liability Modeling, Cambridge University Press 205–228.

Campbell, John Y. 1987. “Stock Returns and the Term Structure.” Journal of Financial Economics 18 (2), 373–99.

Campbell, John Y. and Luis M. Viceira. 1999. “Consumption and Portfolio Decisions When Expected Returns Are Time Varying.” Quarterly Journal of Economics 114, 433–495.

Campbell, John Y., and Luis M. Viceira. 2001. “Who Should Buy Long-Term Bonds?” American Economic Review 91, 99–127.

Campbell, John Y., and Luis M. Viceira. 2002. “Strategic Asset Allocation: Portfolio Choice for Long-Term Investors.” Oxford University Press, New York, NY.

Campbell, Rachel, Ronald Huisman, and Kees Koedijk. 2001. “Optimal Portfolio Selection in a Value-at-Risk Framework.” Journal of Banking & Finance 25 (9), 1789–1804.

Campbell, John Y., Yeung L. Chan, and Luis M. Viceira. 2003. “A Multivariate Model of Strategic Asset Allocation.” Journal of Financial Economics 67, 41–80.

Chan, Louis K.C., Jason Karceski, and Josef Lakonishok. 1999. “On Portfolio Optimization: Forecasting Covariances and Choosing the Risk Model.” The Review of Financial Studies 12 (5), 937–74.

Chen, Hsin-Hung, Hsien-Tang Tsai, and Dennis K.J. Lin. 2011. “Optimal Mean-Variance Portfolio Selection Using Cauchy–Schwarz Maximization.” Applied Economics 43 (21), 2795–2801.

Chen, Shiu-Sheng. 2009. “Predicting the Bear Stock Market: Macroeconomic Variables as Leading Indicators.” Journal of Banking & Finance 33 (2), 211–23.

Cornuejols, Gerard, and Reha Tütüncü. 2006. “Optimization Methods in Finance.” Vol. 5. Cambridge University Press.

Costa, Giorgio, and Roy H. Kwon. 2019. “Risk Parity Portfolio Optimization under a Markov Regime-Switching Framework.” Quantitative Finance 19 (3), 453–71.

Dahlquist, Magnus, and Campbell R. Harvey. 2001. “Global Tactical Asset Allocation.” The Journal of Global Capital Markets 1–9.

Diebold, Francis X., Joon-Haeng Lee, and Gretchen C. Weinbach. 1994. “Regime Switching with Time-Varying Transition Probabilities.” Business Cycles: Durations, Dynamics, and Forecasting 1, 144–65.

Dimopoulos, Yannis, Paul Bourret, and Sovan Lek. 1995. “Use of Some Sensitivity Criteria for Choosing Networks with Good Generalization Ability.” Neural Processing Letters 2, 1–4.

Dimopoulos, Ioannis, J. Chronopoulos, A. Chronopoulou Sereli, and Sovan Lek. 1999. “Neural Network Models to Study Relationships between Lead Concentration in Grasses and Permanent Urban Descriptors in Athens City (Greece).” Ecological Modelling 120, 157–165.

Engle, Robert F. 1982. “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation.” Econometrica: Journal of the Econometric Society 987–1007.

Ernst, Cornelia, Martin Grossmann, Stephan Hocht, Stefan Minden, Matthias Scherer, and Rudi Zagst. 2009. “Portfolio Selection under Changing Market Conditions.” International Journal of Financial Services Technology Management 4 (1), 48–63.

Fama, Eugene F., and Kenneth R. French. 1988. “Dividend Yields and Expected Stock Returns.” Journal of Financial Economics 22 (1), 3–25.

———. 1989. “Business Conditions and Expected Returns on Stocks and Bonds.” Journal of Financial Economics 25 (1), 23–49.

Fama, Eugene F., and G. William Schwert. 1977. “Asset Returns and Inflation.” Journal of Financial Economics 5 (2), 115–46.

Farinelli, Simone, Manuel Ferreira, Damiano Rossello, Markus Thoeny, and Luisa Tibiletti. 2008. “Beyond Sharpe Ratio: Optimal Asset Allocation Using Different Performance Ratios.” Journal of Banking & Finance 32 (10), 2057–63.

Farinelli, Simone, Manuel Ferreira, Damiano Rossello, Markus Thoeny, and Luisa Tibiletti. 2009. “Optimal Asset Allocation Aid System: from “One-size” vs. “Tailor-made” Performance Ratio.” European Journal of Operation Research 192, 209–215.

Ferson, Wayne E., and Campbell R. Harvey. 1991. “The Variation of Economic Risk Premiums.” Journal of Political Economy 99 (2), 385–415.

French, Kenneth R., G. William Schwert, and Robert F. Stambaugh. 1987. “Expected Stock Returns and Volatility.” Journal of Financial Economics 19 (1), 3–29.

Garson, G. David. 1991. “Interpreting Neural-Network Connection Weights.” Artificial Intelligence Expert 6, 47–51.

Guidolin, Masimo, and Allan Timmermann. 2007. “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control 31 (11), 3503–3544.

Hannah, Lauren, Warren Powell, and David M. Blei. 2010. “Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable.” Advances in Neural Information Processing Systems 820–28.

Harvey, Campbell R. 2001. “The Specification of Conditional Expectations.” Journal of Empirical Finance 8 (5), 573–637.

Kaastra, Iebeling, and Milton Boyd. 1996. “Designing a Neural Network for Forecasting Financial and Economic Time Series.” Neurocomputing 10 (3), 215–36.

Kanas, Angelos. 2008. “A Multivariate Regime Switching Approach to the Relation between the Stock Market, the Interest Rate and Output.” International Journal of Theoretical and Applied Finance 11 (07), 657–71.

Kat, Harry M., and Chris Brooks. 2002. “The Statistical Properties of Hedge Fund Index Returns and Their Implications for Investors.” Journal of Alternative Investments 5, 26–44.

Keim, Donald B., and Robert F. Stambaugh. 1986. “Predicting Returns in the Stock and Bond Markets.” Journal of Financial Economics 17 (2), 357–90.

Konno, Hiroshi, and Hiroaki Yamazaki. 1991. “Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market.” Management Science 37 (5), 519–31.

Kotz, Samuel, N. Balakrishnan, and Norman L. Johnson. 2000. “Continuous Multivariate Distributions: Volume 1: Models and Applications.” 2nd Ed. New York: John Wiley & Sons, Inc.

Kritzman, Mark, Sebastien Page, and David Turkington. 2012. “Regime Shifts: Implications for Dynamic Strategies.” Financial Analyst Journal 68 (3), 22–39.

Kroll, Yoram, Haim Levy, and Harry M. Markowitz. 1984. “Mean-Variance versus Direct Utility Maximization.” The Journal of Finance 39 (1), 47–61.

Laborda, Ricardo, and Jose Olmo. 2017. “Optimal Asset Allocation for Strategic Investors.” International Journal of Forecasting 33 (4), 970-987.

Lek, Sovan, Alain Belaud, Philippe Baran, Ioannis Dimopoulos, and Marc Delacoste. 1996a. “Role of Some Environmental Variables in Trout Abundance Models Using Neural Networks.” Aquatic Living Resources 9, 23–29.

Lek, Sovan, Marc Delacoste, Philippe Baran, Ioannis Dimopoulos, Jacques Lauga, and Stephane Aulagnier. 1996b. “Application of Neural Networks to Modeling Nonlinear Relationships in Ecology.” Ecological Modelling 90, 39–52.

Leland, Hayne E. 1999. “Beyond Mean-Variance: Performance Measurement in a Nonsymmetrical World.” Financial Analysts Journal 27–36.

Malandri, Lorenzo, Frank Z. Xing, Carlotta Orsenigo, Carlo Vercellis, and Erik Cambria. 2018. “Public Mood–Driven Asset Allocation: the Importance of Financial Sentiment in Portfolio Management.” Cognitive Computation 10(6), 1167–1176.

Malkiel, Burton G., and Atanu Saha. 2005. “Hedge Funds: Risk and Return.” Financial Analysts Journal 80–88.

Markowitz, Harry. 1952. “Portfolio Selection.” The Journal of Finance 7 (1), 77–91.

Martin, R. Douglas, Svetlozar Zari Rachev, and Frederic Siboulet. 2003. “Phi-Alpha Optimal Portfolios and Extreme Risk Management.” The Best of Wilmott 1: Incorporating the Quantitative Finance Review 1, 223.

Merton, Robert C. 1980. “On Estimating the Expected Return on the Market: An Exploratory Investigation.” Journal of Financial Economics 8 (4), 323–61.

Nystrup, Peter, Henrik Madsen, and Erik Lindström. 2018. “Dynamic Portfolio Optimization across Hidden Market Regimes.” Quantitative Finance 18 (1), 83–95.

Olden, Julian D., and Donald A. Jackson. 2002. “Illuminating the “Black Box”: Understanding Variable Contributions in Artificial Neural Networks.” Ecological Modelling 154, 135–150.

Olden Julian D., Michael K. Joy, and Russel G. Death. 2004. “An Accurate Comparison of Methods for Quantifying Variable Importance in Artificial Neural Networks Using Simulated Data.” Ecological Modelling 178 (3-4), 389–397.

Oroojlooyjadid, Afshin, Lawrence V. Snyder, and Martin Takac. 2020. “Applying Deep Learning to the Newsvendor Problem.” IISE Transactions 52 (4), 444–463.

Ortobelli, Sergio, Sebastiano Vitali, Marco Cassader, and Tomas Tichy. 2018. “Portfolio Selection Strategy for Fixed Income Markets with Immunization on Average.” Annals of Operations Research 260 (1), 395–415.

Pyo, Sujin, and Lee Jaewook. 2018. “Exploiting The Low-Risk Anomaly Using Machine Learning to Enhance the Black–Litterman Framework: Evidence from South Korea.” Pacific-Basin Finance Journal 51, 1–12.

Rockafellar, R. Tyrrell, and Stanislav Uryasev. 2002. “Conditional Value-at-Risk for General Loss Distributions.” Journal of Banking and Finance 26, 1443–1471.

Rojas, Raúl. 2013. “Neural Networks: A Systematic Introduction.” Springer Science & Business Media.

Scardi, Michele, and Lawrence W. Harding Jr. 1999. “Developing an Empirical Model of Phytoplankton Primary Production: A Neural Network Case Study.” Ecological Modelling 120 (2–3), 213–223.

Schwert, G. William. 1989. “Why Does Stock Market Volatility Change over Time?” The Journal of Finance 44 (5), 1115–53.

Shalit, Haim, and Shlomo Yitzhaki. 1984. “Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets.” The Journal of Finance 39 (5), 1449–68.

Sharpe, William F. 1966. “Mutual Fund Performance.” The Journal of Business 39 (1), 119–38.

Sheikh Abdullah Z., and Jianxiong Sun. 2012. “Regime change: Implications of Macroeconomic Shifts on Asset Class and Portfolio Performance.” The Journal of Investing 21 (3), 36–54.

Vapnik, Vladimir. 1992. “Principles of Risk Minimization for Learning Theory.” In Moody, J. E., Hanson, S. J. & Lippmann, R. P. (eds.), Advances in Neural Information Processing Systems 4, 831–838. Morgan Kaufman, San Mateo, CA.

Villarrubia, Gabriel, Juan F. De Paz, Oablo Chamoso, and Fernando De la Prieta. 2018. “Artificial Neural Networks Used in Optimization Problems.” Neurocomputing 272, 10–6.

Whitelaw, Robert F. 1994. “Time Variations and Covariations in the Expectation and Volatility of Stock Market Returns.” The Journal of Finance 49 (2), 515–41.

Xing, Frank Z., Erik Cambria, and Roy E. Welsch. 2018. “Intelligent Asset Allocation via Market Sentiment Views.” IEEE Computational Intelligence Magazine 13 (4), 25–34.

Yao, Jingtao, Nicholas Teng, Hean-Lee Poh, and Chew Lim Tan. 1998. “Forecasting and Analysis of Marketing Data Using Neural Networks.” Journal of Information Science and Engineering 14, 843-862.

Young, Martin R. 1998. “A Minimax Portfolio Selection Rule with Linear Programming Solution.” Management Science 44 (5), 673–83