The Relevance of Market Correlation for the Portfolio Selection - An Individual Investor Long Term Perspective

Anna Marta Chmielewska

doi:10.2478/erfin-2022-0006

Anna Marta Chmielewska SGH Warsaw School of Economics, Poland

DOI: https://doi.org/10.2478/erfin-2022-0006

Keywords: Passive Investment Strategies, Pension Savings, Long-Term Investment, Home-Currency Bias, Market Interdependence

Abstract

This paper applies BEKK-type model to explain the interdependence between markets that might be relevant to a Polish individual saving for retirement. The investor is assumed to look for cross-country and cross-asset diversification of the long-term investment yielding the optimal portfolio, with performance assessed using local currency returns. Monte Carlo simulation methodology was used to better capture the market dynamics, especially with respect to market interdependence assumptions.

The high level findings of the optimal portfolio composition reconfirm that even a local currency investor, looking at local currency returns, can benefit from broadening of the investment spectrum, at the same time however providing supportive arguments for a strong bias towards local currency government bonds. The results question relatively high proportion of equity component offered as default by majority savings providers or mutual funds. This encourages reflection on the society-wide consequences of following predefined structures, frequently supported by policy reforms, which may lead to excessive shift of business risks onto the households. These results prove robust when using various measures of market interdependence as well as when capturing the recent COVID related market turmoil.

References

Allen, D. E. and McAleer, M. (2018). Theoretical and Empirical Differences Between Diagonal and Full BEKK for Risk Management. Energies, 11(7):1627.

Allen, D. E., McAleer, M., Powell, R., and Singh, A. K. (2017). Volatility Spillover and Multivariate Volatility Impulse Response Analysis of GFC News Events. Applied Economics, 49(33):3246–3262.

Analizy Online (2020). Struktura oszczednosci gospodarstw domowych (czerwiec 2020) (translation: Quarterly Report on Savings Structure). derived From https://www.analizy.pl/raporty/26094/struktura-oszczednosci-gospodarstw-domowych-czerwiec-2020 (on 15.09.2020).

Arnott, R. D., Hsu, J., and Moore, P. (2005). Fundamental Indexation. Financial Analysts Journal, 61(2):83–99.

Aziz, N. S. A., Vrontos, S., and Hasim, H. M. (2019). Evaluation of Multivariate GARCH Models in an Optimal Asset Allocation Framework. The North American Journal of Economics and Finance, 47:568–596.

Bauwens, L., Laurent, S., and Rombouts, J. V. (2006). Multivariate GARCH Models: A Survey. Journal of Applied Econometrics, 21(1):79–109.

Beshears, J., Choi, J. J., Laibson, D., and Madrian, B. C. (2009). The Importance of Default Options for Retirement Saving Outcomes: Evidence From the United States. In Social Security Policy in a Changing Environment, pages 167–195. University of Chicago Press.

Caporin, M. and McAleer, M. (2012). Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models. Journal of Economic Surveys, 26(4):736–751.

Chang, C.-L. and McAleer, M. (2019). The Fiction of Full BEKK: Pricing Fossil Fuels and Carbon Emissions. Finance Research Letters, 28:11–19.

Chmielewska, A. et al. (2018). Volatility and Co-movements of the Equity Markets in Central Europe – Evidence From Poland and Hungary. Economic and Environmental Studies, 18(2 (46)):499–513.

Dowd, K. (2000). Adjusting for Risk: An Improved Sharpe Ratio. International Review of Economics & Finance, 9(3):209–222.

Driessen, J. and Laeven, L. (2007). International Portfolio Diversification Benefits: Cross-Country Evidence From a Local Perspective. Journal of Banking & Finance, 31(6):1693–1712.

Engle, R. F. and Kroner, K. F. (1995). Multivariate Simultaneous Generalized ARCH. Econometric Theory, 11(1):122–150.

Farinelli, S., Ferreira, M., Rossello, D., Thoeny, M., and Tibiletti, L. (2008). Beyond Sharpe Ratio: Optimal Asset Allocation Using Different Performance Ratios. Journal of Banking & Finance, 32(10):2057–2063.

Funke, M., Loermann, J., and Tsang, A. (2022). Volatility Transmission and Volatility Impulse Response Functions in the Main and the Satellite Renminbi Exchange Rate Markets. Review of International Economics, 30(2):606–628.

Gorgi, P., Koopman, S. J., and Schaumburg, J. (2021). Vector Autoregressions With Dynamic Factor Coefficients and Conditionally Heteroskedastic Errors. Tinbergen Institute Discussion Paper 2021-056/III. Available at SSRN: https://ssrn.com/abstract=3875604.

Gutierrez, G. and Philippon, T. (2016). Investment-less Growth: An Empirical Investigation. Technical Report w22897, National Bureau of Economic Research.

Jacobs, H., Muller, S., and Weber, M. (2014). How Should Individual Investors Diversify? An Empirical Evaluation of Alternative Asset Allocation Policies. Journal of Financial Markets, 19:62–85.

Malik, K., Sharma, S., and Kaur, M. (2021). Measuring Contagion During COVID-19 Through Volatility Spillovers of BRIC Countries Using Diagonal BEKK Approach. Journal of Economic Studies, 49(2):227–242.

Maller, R. A., Durand, R. B., and Jafarpour, H. (2010). Optimal Portfolio Choice Using the Maximum Sharpe Ratio. The Journal of Risk, 12(4):49–73.

McAleer, M. (2019). What They Did Not Tell You About Algebraic (Non-)existence, Mathematical (Ir-)regularity, and (Non-)asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model. Journal of Risk and Financial Management, 12(2):61.

Patra, S. and Panda, P. (2021). Spillovers and Financial Integration in Emerging Markets: Analysis of BRICS Economies Within a VAR-BEKK Framework. International Journal of Finance & Economics, 26(1):493–514.

Pojarliev, M. and Polasek, W. (2003). Portfolio Construction by Volatility Forecasts: Does the Covariance Structure Matter? Financial Markets and Portfolio Management, 17(1):103–116.

Rachev, S., Jasic, T., Stoyanov, S., and Fabozzi, F. J. (2007). Momentum Strategies Based on Reward–Risk Stock Selection Criteria. Journal of Banking & Finance, 31(8):2325–2346.

Sharpe, W. F. (1966). Mutual Fund Performance. The Journal of Business, 39(1):119–138.

Sheppard, K. (2013). MFE Toolbox. Derived from https://www.kevinsheppard.com/code/matlab/mfe-toolbox/.

Silvennoinen, A. and Terasvirta, T. (2009). Multivariate GARCH Models. In Handbook of Financial Time Series, pages 201–229. Springer, Berlin, Heidelberg.

Sushko, V. and Turner, G. (2018). The Implications of Passive Investing for Securities Markets. BIS Quarterly Review, March, March:113–131.

Tola, V., Lillo, F., Gallegati, M., and Mantegna, R. N. (2008). Cluster Analysis for Portfolio Optimization. Journal of Economic Dynamics and Control, 32(1):235–258.

Tsiaras, K. and Simos, T. (2020). FOREX and Equity Markets Spillover Effects Among USA, Brazil, Italy, Germany and Canada in the Aftermath of the Global Financial Crisis. Journal of Finance and Accounting Research, 2:68–96.

Virbickaite, A., Ausın, M. C., and Galeano, P. (2015). Bayesian Inference Methods for Univariate and Multivariate GARCH Models: A Survey. Journal of Economic Surveys, 29(1):76–96.

Walden, M. L. (2015). Active Versus Passive Investment Management of State Pension Plans: Implications for Personal Finance. Journal of Financial Counseling and Planning, 26(2):160–171.

Yousaf, I., Ali, S., and Wong, W.-K. (2020). Return and Volatility Transmission Between World-leading and Latin American Stock Markets: Portfolio Implications. Journal of Risk and Financial Management, 13(7):148.

Zielonka, P. (2004). Technical Analysis as the Representation of Typical Cognitive Biases. International Review of Financial Analysis, 13(2):217–225.