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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|12999||2014||17 صفحه PDF||سفارش دهید|
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|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||12 روز بعد از پرداخت||693,000 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||6 روز بعد از پرداخت||1,386,000 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Emerging Markets Review, Volume 18, March 2014, Pages 45–61
It seems reasonable to expect financial market efficiency to be related to the economic development level. We study a 16 year sample, covering 22 countries. The Hurst–Mandelbrot–Wallis rescaled range is our efficiency measure, which we apply to returns and volatility. We find strong evidence of long memory persistence in volatility over time, which is unsurprising. However, unlike previous researchers, we could not find evidence of rescaled ranges trending down over time. However, we introduce an alternative measure of economic development, namely, whether FTSE (2011) classify an emerging market as ‘advanced’ or ‘secondary’. This measure shows greater efficiency in returns and volatility for ‘advanced’ emerging markets.
According to the weak form of the Efficient Market Hypothesis (EMH), asset prices should exhibit no pattern that could enable future prices to be forecast with any consistency. Consequently, asset returns are supposed to be normally distributed and sequentially independent. In other words, asset returns should exhibit no long-term memory of the price series that precedes it. In this paper, we measure long-term memory by means of the rescaled range methodology. If this measure shows either persistence or anti-persistence (i.e. mean reversion), then a trading strategy utilising that information could earn an abnormal profit. On the other hand, asset returns which are neither persistent nor anti-persistent are unpredictable, therefore cannot be exploited for profit and so would be an affirmation of the EMH. One would expect that if market inefficiencies do exist, then they should be more prevalent in unsophisticated, under-researched markets rather than in highly developed markets. Moreover, as financial markets evolve from a primitive to a sophisticated state, one would expect to see a steady progression in their level of market efficiency. This idea is consistent with Grossman and Stiglitz (1980) who argued that some price inefficiency is necessary to incentivise arbitrageurs to find and trade mis-priced assets, thereby enforcing market efficiency. As trading volume and the number of research analysts and arbitrageurs increase, the inefficiencies that constitute the arbitrageurs' profit opportunities should be identified earlier and competed away more quickly. Henry (2002) suggests that long memory persistence in equity returns would imply that stock returns are forecastable. Qian and Rasheed (2007) found that markets with high measures of long memory persistence, generate superior forecasting estimates. However, Barkoulas et al. (2000) noted that empirical studies have devoted very little attention to the issue of serial dependence in emerging markets. A number of empirical papers on emerging markets have come out in the decade since. Cajueiro and Tabak (2004a, 2004b) find evidence of long memory persistence in emerging markets which they note is a contradiction of EMH. Furthermore, Tolvi (2003) found that smaller emerging markets are more likely to exhibit significant long memory. Our aim in the present paper is to explicitly investigate the link between market development and market efficiency. In order to do this, we propose two proxies for development. Our first proxy is time: we employ 16 years of data (30/06/1995–30/06/2011), which is a much longer history than any previous paper in this literature. Our second proxy is a state of development classification. We use FTSE (2011) classification of ‘advanced’ and ‘secondary’ emerging markets which is based on a number of indicators of market development. We examine statistical measures of long memory for each sub-group. Our analysis builds upon the empirical work of previous researchers, most notably Cajueiro and Tabak (2004b). It has long been known that volatility clustering is often observed in financial markets, i.e. price sequences typically show blocks of big price swings bunched together, flanked by calmer periods where the price swings are discernibly smaller. Although widely acknowledged, this phenomenon is actually inconsistent with weak-form market efficiency. Indeed, trading activity has the ability to dissipate these volatility clusters in a similar way to how they erode asset prices inefficiencies. Highly developed financial systems have derivative markets in which derivative traders are able to construct trading strategies (e.g. holding simultaneously put and call options with different strike prices) to exploit time-varying volatility, so long as the latter is forecastable. None of the markets we study has a liquid derivative market, which means that this mechanism for eroding long-memory persistence in volatility is not present. We use our rescaled range analysis to examine long memory in volatility, alongside our study of long memory affecting price levels. The following section discusses the findings from established financial theory and empirical research which provide the theoretical framework from which the methodological approach of this paper is constructed. Section 3 justifies the sample selection and describes the methods of data collection. In Section 4, the key methodology is then defined and the benefits and limitations of using the methodology are analysed. Section 5 presents the findings from this empirical research and illustrates these results with appropriate tables and graphs. Section 6 concludes the paper.
نتیجه گیری انگلیسی
In this paper, we investigated the relationship between price efficiency and market development using a long data sample from the emerging markets. Our research builds upon earlier works by Cajueiro and Tabak (2004b). We use the Hurst–Mandelbrot–Wallis rescaled range statistic to measure long-memory persistence in both price change and volatility. We examine this measure over time, where we use time as a proxy for development. We also segregate our data into two blocks based on how advanced each emerging market is deemed by FTSE (2011) to be, which gives us a second proxy for development which is cross-sectional. We find strong evidence of long memory in volatility clustering and weak evidence of long memory in returns, which are not surprising findings. However, contrary to Cajueiro and Tabak (2004b), our evidence shows that a downward sloping rescaled range measure, indicative of progressive economic development, is far from the norm in emerging markets that they suggest. Rather, we observe widely fluctuating levels of serial dependence in 22 emerging markets across our long 16 year study, some of which trend up, whilst others trend down, and yet others have no trend at all. When regressed on their trend lines, most of these series have very poor R-squares. That said, we did find an alternative link between economic development and market efficiency. We found that Qian and Rasheed (2004)H = 0.65 threshold could be used as an effective means of separating the ‘advanced’ from the ‘secondary’ emerging markets. This split is in line with intuition in that the more advanced markets exhibited the least memory persistence, and so appear the most efficient. Our results constitute evidence against the weak-form EMH, as they still indicate profit opportunities, which according to EMH should never exist. They also conflict with the Grossman and Stiglitz (1980) argument that markets tend towards efficiency over time by incentivising arbitrageurs to exploit and eliminate price anomalies. However, our persistent market memory finding is consistent with the alternatives to EMH we discussed earlier, namely the Heterogeneous Market Hypothesis and the Adaptive Market Hypothesis.