Regime shifts and volatility in BRIICKS stock markets: an asset allocation perspective

Abstract

Purpose -The purpose of this paper is to examine the regime shifts and stock market volatility in the stock market returns of seven emerging economies popularly called as "BRIICKS" which stands for Brazil, Russia, India, Indonesia, China, South Korea and South Africa, over the period from February 1996 to January 2012 by applying Markov regime switching (MS) in mean-variance model. Design/methodology/approach -The authors apply MS model developed by Hamilton (1989) using its mean-variance switching framework on the monthly returns data of BRIICKS stock markets. Further, the estimated probabilities along with variances have been used to calculate the time-varying volatility. The authors also examine market synchronization and portfolio diversification possibilities in sample markets by calculating the Logit transformation based crossmarket correlations and Sharpe ratios.Findings -The applied model finds two regimes in each of these markets. The estimated results also helped in formulating the asset allocation strategies based on market synchronization and Sharpe ratio. The results suggest that BRIICKS is not a homogeneous asset class and each market should be independently evaluated in terms of its regime-switching behavior, volatility persistence and level of synchronization with other emerging markets. The study finally concludes that Russia, India and China as the best assets to invest within this emerging market basket which can be pooled with a mature market portfolio to achieve further benefits of risk diversification.Research limitations/implications -The study does not provide macroeconomic and financial explanations of the observed differences in dynamics among sample emerging stock markets. The study does not examine these markets under multivariate framework. Practical implications -The results highlight the role of regime shifts and stock market volatility in the asset allocation and risk management. This study has important implications for international asset allocation and stock market regulation by way of identifying and recognizing the differences on regimes and on the dynamics of the swings which can be very useful in the field of portfolio and public financial management. Originality/value -The paper is novel in employing tests of MS under mean-variance framework to examine the regime shifts and volatility switching behavior in seven promising BRIICKS stock market. Further, using MS model, the authors analyze the duration (persistence) of each identified regime across sample markets. The empirical results of MS model have been used for making portfolio allocation

The Regime-Switching Behaviour of Exchange Rates and Frontier Stock Market Prices in Sub-Saharan Africa

“…In support of the evidence of a two-state switching behaviour in the stock market, Liu et al (2012) used Markov-switching models and found that the US stock market switches between two states: a low-return/high-volatility state and a high-return/low-volatility state. Ahmad and Sehgal (2015) employed a MS model to identify regime shift both in mean and variance for seven emerging countries during the period 1996-2012, and found that all the stock markets were characterised by two regimes, i.e., bear and bull markets. Employing a similar approach, Ismail and Isa (2008) provided evidence that an MS model was able to successfully capture the various timing of the regime shifts in the return series for Malaysia, Singapore, and Thailand.…”

A Test of Positive Feedback Trading among Foreign Portfolio Investors in Nigeria

“…Particularly, positive feedback trading (an irrational trading behavior) may exhibit varying trends across time. On one hand, studies such as Ahmed and Sehgal (2015) and Maharaj, Galagedera and Dark (2011) confirm that the movement of stock returns is time-variant. On the other hand, Pagliari and Hannan (2017) show that portfolio flows follow different trends over time for 65 countries, including emerging countries.…”

International Journal of Emerging Markets: a bibliometric review 2006–2020

“…Kumar (2013) determined the volatility spill-over between exchange rates and stock price in the IBSA nations (India, Brazil and South Africa) and found that domestic markets are more significant than foreign exchange markets for spill-overs. Ahmad and Sehgal (2015) examined the regime shifts and stock market volatility in the stock market returns of seven emerging economies – BRIICKS (Brazil, Russia, India, Indonesia, China, South Korea and South Africa). The research suggested that each market be treated individually, not as a homogeneous asset.…”