Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies

Montshioa, Keitumetse and Muteba Mwamba, John Weirstrass and Bonga-Bonga, Lumengo (2021): Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies.

Abstract

This study makes use of the Extreme Value Theory, based on the Generalised Pareto Distribution and the Generalised Extreme Value Distribution, to construct efficient portfolios during periods of turmoil. The portfolios are constructed by combining different assets constituted by their positions in emerging and developed stock markets, with the aim of identifying which assets combinations provide optimal portfolio allocations during turmoil periods. For the developed stock markets, the study uses the French CAC 40, the Canadian S&P/TSX, the United Kingdom FTSE 100, the Japanese NIKKEI 225 and the United States S&P500 indices and returns. Five emerging stock markets indices are used, namely, the Brazilian BOVESPA, the Chinese SHCOMP the Indian S&P BSE SENEX, Indonesian JSI and the Turkish BIST 100. The data sample spans from August 1997 to August 2019 and include major economic and financial crises. Our findings show that for the different portfolios constructed, the estimated shape, location, and scale parameters differ depending on the Extreme Value Theory distribution under investigation. Moreover, based on the Generalised Pareto Distribution and the Generalised Extreme Value Distribution for portfolio optimisation, the results of the study show that during extreme conditions investors are prone to allocate more weight to developed stock market assets than to emerging markets. This confirms that developed economies are safe havens, especially during extreme market conditions. Moreover, the GPD is superior as it provides maximum risk-reward ratios.

• Item Type: MPRA Paper
• Language: English
• Keywords: asset allocation, extreme value, developing economies, emerging markets
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation; G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

References

Afzal, M. & Ali, R. (2012). Impact of Global Financial Crisis on Stock Markets: Evidence from Pakistan and India. Journal of Business Management and Economics, 3(7): 275-282.

Arzac, E. & Bawa, V. (1977). Portfolio choice and equilibrium in capital markets with safety-first investors. Journal of Financial Economics, 4(3): 277–288.

Bailey, R.E. (2005). The Economics of Financial Markets. 2nd edition. Cambridge University Press.

Bhurjee. A.K., Kumar, P. & Panda, G. (2015). Optimal Range of Sharpe Ratio of a Portfolio Model with Interval Parameters. Journal of Information and Optimisation Sciences, pp. 367-387.

Bollerslev. T. (1986) Generalised Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31: 307-327.

Briec, W., Kerstens, K. & Jokung, O. (2007). Mean-variance-skewness Portfolio Performance gauging: A general shortage function and dual approach. Management Science, 53 (1): 135–149.

Calice, G., Chen, J. & Williams, J. (2013). Liquidity Spillovers in Sovereign Bond and CDS markets: An analysis of the Eurozone sovereign debt crisis. Journal of Economic Behaviour and Organisation, 8: 122-145.

Chiang, T. & Zhang, Y. (2018). An empirical investigation of risk-return relations in Chinese equity markets: Evidence from aggregate and sectoral data. International Journal of Financial Studies, 6(2): 35.

Cohen, B.H. and Remolona, E.M., 2008. Information flows during the Asian crisis: Evidence from closed-end funds. Journal of International Money and Finance, 27(4), pp.636-653.

Coles, S. (2001). An Introduction to Statistical Modelling of Extreme Values. Springer Series in Statistics. London: Springer.

Corsetti, G., Pesenti, P. and Roubini, N., 1999. Paper tigers?: A model of the Asian crisis. European Economic Review, 43(7), pp.1211-1236.

Ćvitanic. J., Polimenis, V. & Zapatero, F. (2008). Optimal Portfolio Allocation with Higher Moments. Annals of Finance, 4(1): 1-28.

Danielsson, J. & De Vries, C. (1997). Tail index and quantile estimation with very high frequency data. Journal of Empirical Finance, 4(2-3): 241–257.

DiTraglia, F.J. & Gerlach, J.R. (2012). Portfolio Selection: An Extreme Value Approach. Journal of Banking and Finance, 37(2): 305-323.

Embrechts, P., Klüppelberg, C. & Mikosch, T. (1997). Modelling Extremal Events for Insurance and Finance. Berlin: Springer-Verlag.

Engle, R.F. (1982). Auto Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50-989.

Erb, C.B., Harvey, C.R., & Viskanta, T.E. (1995). Inflation and World Equity Selection. Financial Analysts Journal, 6: 28-42.

Espaso, A., Pellegrini, S. & Ruiz, E. (2010). Conditionally Heteroscedastic unobserved component models and their reduced form. Economic Letters, 107(2): 88-90.

Falk, M. (1995). On testing the extreme value index via the POT-method. The Annals of Statistics, 23(6): 2013-2035.

Fama, E.F. (1965). The Behaviour of Stock Market Prices. Journal of Business, 38: 34-105.

Gilli, M. (2006). An application of extreme value theory for measuring financial risk. Computational Economics, 27(2-3): 207-228.

Guinigundo, D. and Paulson Jr, H.M., 2010. The impact of the global financial crisis on the Philippine financial system: an assessment. BIS Papers, 54, pp.317-342.

Harvey, C.R. (1995). Predictable Risk and Return in Emerging Markets. Review of Financial Studies, 8: 773-816.

Harvey, C.R., Liechty, J.C. & Liechty, M.W. (2010). Portfolio Selection with Higher Moments. Quantitative Finance, 10: 469-485.

Haugh, M. (2016). Mean-Variance Optimisation and the CAPM. Foundations of Financial Engineering Course, Columbia University.

Hubbard, R.G. (1991). Introduction to Financial Markets and Financial Crises. 1-10: University of Chicago Press.

Hyung, N. & De Vries, C. (2007). Portfolio selection with heavy tails. Journal of Empirical Finance, 14(3): 383–400.

Ibragimov, M., Ibragimov, R. & Kattuman, P. (2013). Emerging Markets and Heavy tails. Journal of Banking and Finance, 7: 2546-2559.

Jansen, D. & De Vries, C. (1991). On the frequency of large stock returns: Putting booms and busts into perspective. The Review of Economics and Statistics, 73(1): 18–24.

Jorion, P. (1996). Measuring the risk in value at risk, Financial Analysts Journal, 52(6): 47-56.

Jorion, P. (2007). Value at Risk: The new benchmark for managing financial risk, 3rd edition. New York: McGraw-Hill.

Junior, L.S. & Franca, I.D.P. (2012). Correlation of Financial Markets in Times of Crisis. Physica: A Statistical Mechanics and its Applications. 391(1-2): 187-208.

Kabundi, A. & Mwamba, J.M. (2011). Extreme Value at Risk: A Scenario for Risk Management. South African Journal of Economics, 79(2), pp.173-183.

Kemp, M. (2011). Extreme Events: Robust Portfolio Construction in the Presence of Fat Tails. John Wiley & Sons.

Khoon, G.S. and Lim (Mah-Hui.), 2010. The impact of the global financial crisis: the case of Malaysia. Third World network (TWN).

Kim, J. (2015). Heavy Tails in Foreign Exchange Markets: Evidence from Asian countries. Journal of Finance and Economics, 3(1): 1-14.

Kiragu, K.A. & Mung’atu, J.K. (2016). Extreme values modelling of Nairobi securities exchange index. American Journal of Theoretical and Applied Statistics, 5(4), pp.234-241.

Koedijk, K.G., Schafgans, M.M. & De Vries, C.G. (1990). The tail index of exchange rate returns. Journal of International Economics, 29(1-2): 93-108.

Lagoarde-Segot, T. & Lucey, B.M. (2007). International Portfolio Diversification: Is there a role for Middle East and North America? Journal of Multinational Financial Management, 17(5): 401-416.

Lhabitant, F.S. (2001). Assessing market risk for hedge funds and hedge fund portfolios. The Journal of Risk Finance, 2(4): 16-32.

Magnou, G. (2017). An Application of Extreme Value Theory for Measuring Financial Risk in the Uruguayan Pension Fund. Compendium: Cuadernos de Economía y Administración, 4(7).

Mainik, G., Mitov, G. & Rüschendorf, L. (2015). Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz. Journal of Empirical Finance, 32, pp.115-134.

Malevergne, Y., Pisarenko, V. & Sornette, D. (2006). On the power of generalized extreme value (GEV) and generalized Pareto distribution (GPD) estimators for empirical distributions of stock returns. Applied Financial Economics, 16(3), pp.271-289.

Mandelbrot, B. (1963). The Variation of Certain Speculative Prices. Journal of Business, 36: 394-419.

Mao, J.C.T. (1970). Capital Budgeting, E-V vs E-S. Journal of Financial and Quantitative Analysis, 4(5): 657-675.

Markowitz, H.(1952). Portfolio Selection. Journal of Finance, 7(1): 77-91.

Markowitz, H. (1959). Portfolio Selection Efficient Diversification of Investment. New York: Wiley.

McNeil, A. & Frey, R. (2000). Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach. Journal of Empirical Finance, 7(3- 4): 271–300.

Mwamba, J.M. (2012). On the optimality of hedge fund investment strategies: A Bayesian Skew-t Distribution Model. African Journal of Business Management, 6: 10015-10024.

Mwamba, J.M., Hammoudeh, S. & Gupta, R. (2017). Financial tail risks in conventional and Islamic stock markets: a comparative analysis. Pacific-Basin Finance Journal, 42: 60-82.

Naqvi, B., Mirza, N., Naqvi, W.A. & Rizvi, S.K.A. (2017). Portfolio optimisation with higher moments of risk at the Pakistan Stock Exchange. Economic Research-Ekonomska istraživanja, 30(1): 1594-1610.

Nagahara, Y. (1996). Non-Gaussian Distribution for Stock Returns and Related Stochastic Differential Equation. Financial Engineering and Japanese Markets. 3:121-149.

Nelson, D.B. (1992). Filtering and Forecasting with Misspecified ARCH Models I: Getting the Right Variance with the Wrong Model. Journal of Econometrics, 52: 61-90.

Peterson, H.G. & Wiegelmann, A.M. (2014). Financial Markets and Global Debt Crisis: Toward a New Architecture for a more Reliable Financial Sector. Norteamérica, 9(1): 79-107.

Pownall, R.A.J. & Koedijk, K.G. (1999). Capturing Downside Risk in Financial Markets: The Case of the Asian Crisis. Journal of International Money and Finance, 18: 853-870.

Riley Jr, W.B. and Chow, K.V., 1992. Asset allocation and individual risk aversion. Financial Analysts Journal, 48(6), pp.32-37.

Roy, A. D. (1952). Safety First and Holding of Assets. Econometrica, 20(3): 431-449.

Samarakoon, L.P. (2017). Contagion of the eurozone debt crisis. Journal of International Financial Markets, Institutions and Money, vol. 49, pp. 115-128.

Saranya, K. & Prasanna, P.K. (2014). Portfolio Selection and Optimization with Higher Moments: Evidence from the Indian Stock Market. Asia-Pacific Financial Markets, 21(2): 133-149.

Sharpe, W. F. (1966). Mutual Fund Performance. Journal of Business, 39(1): 199-138.

Sortino, F. & Van der Meer, R. (1991). Downside Risk: Capturing what’s at Stake in Investment Solutions. Journal of Portfolio Management, 17(4): 27-31 DOI:10.3905/jpm.1991.409343.

Susmel, R. (2001). Extreme Observations and Diversification in Latin American Emerging Equity Markets. Journal of International Money and Finance, 20 (7): 971-986.

Tessler, L. G. (1955). Safety-First and Hedging. Review of Economic Studies, 23(1) 60: 1-16.

Tronzano, M., 2020. Safe-Haven Assets, Financial Crises, and Macroeconomic Variables: Evidence from the Last Two Decades (2000–2018). Journal of Risk and Financial Management, 13(3), p.40.

Uotila, J., Maula, M., Keil, T. and Zahra, S.A., 2009. Exploration, exploitation, and financial performance: analysis of S&P 500 corporations. Strategic Management Journal, 30(2), pp.221-231.

Vila, A., 2000, March. Asset price crises and banking crises: some empirical evidence. In BIS conference papers (Vol. 8, No. March, pp. 232-252).

Violi, R. and Camerini, E., 2016. Emerging market portfolio strategies, investment performance, transaction cost and liquidity risk. Bank of Italy Occasional Paper.

Wang, P., Sullivan, R.N. & Ge, Y. (2011). Risk-Based Dynamic Asset Allocation with Extreme Tails and Correlations. Journal of Portfolio Management, 38(4):26