تعمیم روش توان هرست به بهره وری در بازارهای خاورمیانه و شمال آفریقا

We study the time-varying efficiency of 15 Middle East and North African (MENA) stock markets by generalized Hurst exponent analysis of daily data with a rolling window technique. The study covers a time period of six years from January 2007 to December 2012. The results reveal that all MENA stock markets exhibit different degrees of long-range dependence varying over time and that the Arab Spring has had a negative effect on market efficiency in the region. The least inefficient market is found to be Turkey, followed by Israel, while the most inefficient markets are Iran, Tunisia, and UAE. Turkey and Israel show characteristics of developed financial markets. Reasons and implications are discussed.

The efficient market hypothesis (EMH) has been a highly controversial topic in theory of finance. It states that prices already reflect all known information, and in its weak form (WEMH), it suggests that all past market prices are fully reflected in asset prices, and thus one cannot beat the market by any investment strategy. According to the WEMH, the existence of serial correlations between observations is not possible. While short serial correlation is accepted by supporters of the EMH, long serial correlation is generally rejected. The presence of long-range dependence in asset returns has been an intriguing subject for a long time. Starting with the revolutionary paper of Mandelbrot [1], the existence of long memory has been shown to exist in asset returns (see Ref. [2] and the references therein for details). Besides the violation of the EMH, the presence of long-range dependence brings out several other problems in real-life applications: the investment horizon becomes a factor in the investment risk [3], derivative pricing techniques (such as the Black–Scholes technique) may not be useful anymore, and usual tests based on the Capital Asset Pricing Model (CAPM) cannot be applied to series that have long memory [4] and [5]. Despite the extensive research on long-range dependence in developed markets, less is known about it in emerging ones, especially the markets belonging to the MENA region (see Refs. [6] and [7] and references therein). Therefore, this study intends to examine behavior of efficiency of 15 MENA stock markets. The topic is interesting, since MENA markets are expected to display some properties that are not present in developed markets, such as investors’ slow reaction to new information, the effect of highly volatile foreign capital flow, and possible severe effects of non-synchronous trading [4]. Considering the increasing dominance of MENA countries in the international arena also makes the research more important. This study uses the generalized Hurst exponent with a rolling window approach to measure the long-range dependence.1 Combining the generalized Hurst exponent and the rolling window technique was initially suggested by Morales et al. [11] to evaluate the level of stability/instability of financial firms in the US stock market. The authors revealed that such an approach can be used as an early warning indicator for financial crises.2 With an extended motivation, this study applies the same approach to stock markets in the MENA region. Another contribution to the literature is that this study contains the largest country set among other studies on the subject, and considers a time period including the recent Arab Spring, so the external effects can be observed. The rest of the paper is organized as follows. Section 2 elucidates the methodology associated with testing for time-varying long-range dependence, and Section 3 describes the data and presents the results. Section 4 gives a robustness check of our analysis, and finally Section 5 offers a brief conclusion.

Market efficiency is a vital concept that is not easy to test or measure empirically. Most of the literature has focused on developed stock markets, however; the amount of literature that focuses on emerging markets is relatively small. To fill this gap, the concept of generalized Hurst exponents has been applied to MENA markets’ daily data between 2007 and 2012 by a rolling window approach. Such a time-varying approach can help us to detect the unstable times (herding behavior, market bubbles, crashes, and manipulation) in the stock markets, thus providing policy-making guidance to improve efficiency, which in its turn reduces distortions in the economy. The results show that the MENA markets, in general, exhibit persistent characteristics. Before the Arab Spring, the markets have an evolving tendency towards efficiency, but the protests take this effect away in the majority of the markets. The efficiency of the markets has been analyzed by mean and multiple median comparison of H(1)H(1), and the least inefficient market is found to be Turkey, followed by Israel, while the most inefficient markets are Iran, Tunisia, and UAE (the robustness of the results has been checked). Furthermore, the stability of H(1)H(1) in the markets of Turkey and Israel differs from that of the others, showing characteristics of a developed market. This situation reveals that, even though they belong to the same region, concepts like economic management, political stability, and the risk profile of a country distinguish the efficiency levels of stock markets. Considering the efficiency rankings and the major liquidity indicators (market capitalization, trade volume, and turnover) of these markets shows that these variables play an important role in explaining the long-range dependence. However, they are very difficult to quantify in a precise way for the MENA region, and thus we cannot present an analytic comparison. Since market efficiency implies firms being able to finance themselves using the correct cost of capital, the relatively lower inefficiency of the stock markets of Turkey and Israel reduces the cost of capital for companies that are listed in these countries. This situation eventually creates a better environment for portfolio and risk managers in decision making and risk pricing. In most of the cases, the density of H(q)H(q) shows bimodality. This is particularly important, since it suggests structural breaks or shifts in the price dynamics of these stock markets, possibly due to the major political changes in the region caused by the Arab Spring. Considering the increasing importance of the region in the world economy, understanding the source of long-range dependence in the region’s stock markets is certainly a topic that should require more attention. We hope that our results will be helpful for investors, policy makers, and risk and portfolio managers.