Risk Aversion and Value at Risk in Macroeconomic Assets Portfolio: An Approach of Econophysics

Document Type : Research Paper

Authors

1 Department of Economic, Faculty of Economic and Management, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

2 Master of Economics and Reasercher.

10.22103/jdc.2020.11447.1037

Abstract

Objective: Due to the importance of studing the behavior of asset markets, the risk aversion term and its operational calculation has attracted many researchers. The present study intends to examine this issue by considering a portfolio with three assets in the three  markets of stock, currency and gold. Therefore, by examining the fluctuations of previous years in the portfolio consisting of three macroeconomic assets , stocks, currency and gold, we can assess the risk aversion of investors in these markets and the causal relationship between these markets and take steps to construct long-term policy goals.
Method: To investigate the issue, using a mathematical equilibrium model and dynamic econometric methods, the monthly data of stock markets, currency and gold during the period 1995 to 2018 has been analyzed.
Results: Based on the research findings, the amount of risk aversion for the sample size shows that the average risk aversion index of investors in the stock market is higher than the other two markets and this index is the lowest in the gold market. Also, the value-at-risk index of return has a one-way causality and a significant relationship with the degree of risk aversion of investors in all three asset markets.
Conclusion: The results of this study of risk aversion and risk value in these markets can help policymakers to better understand the interactions of these markets, control them and eliminat the destabilizing conditions of these markets.
Specifically in the case of the Iranian stock market, it can be said that investors are relatively more risk averse to the both gold and foreign exchange markets in the conditions of economic recession and increasing political instability, in other words, stock market investors have less confidence in  the exchange and gold markets. The reason is the newness of the stock market compared to the global stock markets and also the longer existence of gold and foreign exchange markets than the emerging stock market in Iran.
Also since gold assets have an intrinsic value and the dollar market is supported by a large global economy, Therefore to strengthen the support of the Iranian stock market, it seems improving economic infrastructure,  promotion of the conditions of companies in the stock market, increasing government support for competitive condition and prohibition of direct intervention in the stock market are necessary. In addition, due to the complex nature of the stock market and the lack of sufficient public information , the need to inform and increase public awareness for a long-term presence in the stock market seems necessary.

Keywords


ابراهیمی، سیدبابک؛ باباخانی، مسعود؛ متقی دستنایی، سمیرا؛ جبارزاده، آرمین. (1390). اثر ریسک‌گریزی فرد در انتخاب پویای سبد مالی بهینه. پژوهشنامه اقتصادی، 11(40)، 271-241.
حسینیون، نیلوفرسادات؛ بهنامه، مهدی؛ ابراهیمی سالاری، تقی. (1395). بررسی انتقال تلاطم نرخ بازده بین بازار‌‌‌‌‌های سهام، طلا و ارز در ایران. پژوهش‌های اقتصادی ایران، 21(66)، 150-123.
سجادی، زینب؛ فتحی، سعید. (1392). تبیین فرایند چهارگامی محاسبه ارزش در معرض خطر به‌عنوان معیاری برای اندازهگیری ریسک و پیاده‌سازی آن در یک مدل بهینه‌سازی سرمایه‌گذاری. دانش مالی تحلیل اوراق بهادار، 6(4)، 13-1.
فلاحی، فیروز، حقیقت؛ جعفر، صنوبر، ناصر؛ جهانگیری، خلیل. (1393). بررسی همبستگی بین تلاطم بازار سهام، ارز و سکه در ایران با استفاده از مدل DCC-GARCH.  پژوهشنامه اقتصادی، 14(52)، 147-123.
محمودی، وحید؛ تهرانی، رضا؛ پیمانی، مسلم. (1386). بررسی مقایسه‌ای بین انواع روش‌های تخمین بتا جهت رفع مشکلات ناشی از معاملات ناهمزمان. تحقیقات مالی، 9(2)، 102-83.
References
Brown, D.P., Zhang, Z.M. (1997). Market orders and market efficiency. The Journal of Finance, 52(1), 277-308.‏
Ebrahimi, S. B., Babakkhani, M., Motaghi, S., Jabarzadeh, A. (2011). The effect of risk aversion on the dynamic selection of the optimum portfolio, Journal of Economic Research,11(40), 241-271 [In Persian].
Fallahi, F., Hghighat, J., Sanoubar, N., Jahangiri, K. (2014). Study of correlation between volatility of stock, exchange and gold coin markets in Iran with DCC-GARCH model. Economics Research, 14(52), 147-123 [In Persian].
Grossman, S. (1976). On the efficiency of competitive stock markets where trades have diverse information. The Journal of Finance, 31(2), 573-585.‏
Hull, J., Treepongkaruna, S., Colwell, D., Heaney, R., Pitt, D. (2013). Fundamentals of Futures and Options Markets. Pearson Higher Education AU.‏
Hosseinioun, N.S., Behname, M, Ebrahimi, S.T. (2016). Volatility transmission of the rate of returns in Iranian stock, gold and foreign currency markets. Iranian Journal of Economic Research, 21(66), 123-150 [In Persian].
Iqbal, J. (2017). Does gold hedge stock market, inflation and exchange rate risks? An econometric investigation. International Review of Economics & Finance, 48, 1-17.‏
Iori, G. (2002). A microsimulation of traders activity in the stock market: the role of heterogeneity, agents’ interactions and trade frictions. Journal of Economic Behavior & Organization, 49(2), 269-285.‏
Jain, A., Biswal, P.C. (2016). Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resources Policy, 49, 179-185.‏
Levy, M., Levy, H., Solomon, S. (1995). Microscopic simulation of the stock market: the effect of microscopic diversity. Journal de Physique I, 5(8), 1087-1107.‏
Mahmoodi, V.,Tehrani, R., Peymani, M. (2007). Comparing methods of beta estimation in cases of non-synchronize trading. Financial Research Journal, 9(2), 83-102 [In Persian].
Marsili, M., Maslov, S., Zhang, Y.C. (1998). Dynamical optimization theory of a diversified portfolio. Physica A: Statistical Mechanics and its Applications, 253(1-4), 403-418.‏
Mas-Colell, A., Whinston, M.D., Green, J.R. (1995). Microeconomic Theory (Vol. 1). New York: Oxford university press.
Menezes, C.F., Hanson, D.L. (1970). On the theory of risk aversion. International Economic Review, 11(3), 481-487.‏
Navale, G.S., Dudhwala, N., Jadhav, K., Gabda, P., Vihangam, B.K. (2016). Prediction of stock market using data mining and artificial intelligence. International Journal of Engineering Science, 134, 9-11.‏
Palmer, R.G., Arthur, W.B., Holland, J.H., LeBaron, B., Tayler, P. (1994). Artificial economic life: A simple model of a stockmarket. Physica D: Nonlinear Phenomena, 75(1-3), 264-274.‏
Sajadi, Z.,Fathi, S. (2014).Explain the four-step process of calculating risk value as a measure of risk and its implementation in an investment optimization model, Financial Knowledge of Securities Analysis, 31(66), 1-13 [In Persian].
Vargas, M.R., De Lima, B.S., Evsukoff, A.G. (2017). Deep learning for stock market prediction from financial news articles. In Computational Intelligence and Virtual Environments for Measurement Systems and Applications, IEEE International Conference, 60-65.
Von Neumann, J., Morgenstern, O. (1945). Theory of games and economic behavior. Bulletin of the American Mathematical Society, 51(7), 498-504.‏
Wen, X., Cheng, H. (2018). Which is the safe haven for emerging stock markets, gold or the US dollar? Emerging Markets Review, Online at: https://papers.ssrn.com, 1-61.