آزمون های گام تصادفی و بهره وری در بازار ارز خارجی آسیا و اقیانوس آرام: شواهدی از داده های بحران ارزی آسیایی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|14898||2009||17 صفحه PDF||سفارش دهید||9264 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Research in International Business and Finance, Volume 23, Issue 3, September 2009, Pages 322–338
This paper empirically tests the random walk and efficiency hypothesis for 12 Asia-Pacific foreign exchange markets. The hypothesis is tested using individual as well as panel unit root tests and two variance-ratio tests. The study covers the high (daily) and medium (weekly) frequency post-Asian crisis spot exchange rate data from January 1998 to July 2007. The inferential outcomes do not differ substantially between the unit root tests and the variance-ratio tests when using daily data but differ significantly when using weekly data. With the daily data, both types of unit root tests identify unit root components for all the series and two variance-ratio tests provide the evidence of martingale behavior for majority of the exchange rates tested. With the weekly data, panel unit root tests identify unit root component for the exchange rates and, the unit root tests on a single series basis identify unit root component for 10 foreign exchange markets. However, the variance-ratio tests reject the martingale null for the majority of the exchange rates when using weekly data.
The recent study1 in the financial market efficiency indicates that different kinds of methodologies and data frequencies are used to explain the random walk behavior of the financial market. It is fair to say that economists have not yet reached a consensus about whether exchange rates are unpredictable (or FX markets are efficient). However, the inferences from the different methodologies and from the high or low frequency data should be distinguished with the policy implications conducive to the state of the development of concerned foreign exchange (or financial) markets. Otherwise, both the investors and the policy makers would be puzzled and misled. The distinction of the results across the methodologies and the data frequencies is important for several reasons. First, it reduces the ongoing debates between the finance practitioners and the academics with regard to the market efficiency; the former presume that the markets are inefficient and the latter believe that the markets are efficient. Second, even within the identically developed financial markets, the traders behave differently. For example, some traders behave rationally, primarily relying on the fundamental analysis and hence treated as ‘rational arbitrageurs’, while some traders do not behave rationally rather primarily relying on ‘sentiments’ and/or ‘noises’ and hence treated as ‘less rational noise traders’ (see Menkhoff, 1998). Third, the high frequency data are better estimates of the market efficiency of developed markets, where the volume of trading is very high, the foreign exchange markets are relatively developed, markets are very competitive and market players are better informed than the underdeveloped or small markets. This indicates that the low and medium frequency data are better estimates of the market efficiency of transitional and undeveloped/developing markets. Thus, unlike Lo and MacKinlay (1988), Liu and He (1991) and Wright (2000), who suggest to use the medium frequency (weekly) data to avoid the shortcomings with the high and low frequency data, we argue that the selection of the data for drawing conclusions on the market efficiency should be based on the type and development of the markets concerned. Los (1999), Lee et al. (2001), Jeon and Seo (2003), Lo and Lee (2006) and among others use the high frequency data to explain the foreign exchange market efficiency. We use both the high and medium frequency data so that the appropriate policies conducive to the capital market development of the respective countries can be alienated. From the econometric point of view, the random walk implies both that a series has a unit root component and that the increments of a series are uncorrelated (or a series has a martingale property). If both properties are found to exist in a financial market, the financial series is said to follow a random walk. However, a series might have a unit root component but not a martingale property and vice versa. While the first property of the random walk is identified by the unit root tests, the uncorrelated increments are identified by the variance-ratio (VR) tests. These tests supplement each other in investigating the random walk behavior of the financial markets. Lo and MacKinlay, 1988 and Lo and MacKinlay, 1989, Cecchetti and Lam (1994) and Gilmore and McManus (2003) argue that the variance-ratio test is more reliable than the traditional unit root tests. The premise of the random walk and efficiency hypothesis is that if price formation in a foreign exchange market is random and the return from that market is not predictable, then we fail to reject the hypothesis of market efficiency.2 In this (efficient) market it is impossible for an exchange trader to gain excess returns over time through speculation, because prices do reflect all relevant and available market information. Conversely, if the return from a financial market is predictable and in this sense non-random, then the markets are not efficient, which implies that the exchange traders can generate (abnormal) returns through speculation. There might be several reasons why the markets are not efficient. First, the prices in these markets do not quickly adjust to the new information (Fama, 1970 and Melvin, 2004). Second, the prices in this market are not set at the equilibrium level due to distortions in the pricing of capital and the valuing of risk (Smith et al., 2002). Third, the emergence of a parallel/black market due to the existence of the exchange rate controls and resulting divergence between the equilibrium rate and the official rate (see Diamandis et al., 2007). Fourth, the exchange rate regime is also a major determinant of foreign exchange market efficiency. If the regulatory agencies do not allow the foreign banks the free access to the foreign exchange markets and products, the foreign exchange market may not be efficient. Several pacific basin countries, namely Indonesia, South Korea, Malaysia, the Philippines, Singapore and Thailand have experienced a ‘parallel’ or a ‘black’ market for US dollar due to different types of foreign exchange controls. Appendix B shows the growth of foreign exchange market turnover in the selected Asia Pacific countries and Appendix C shows the exchange regime of the countries selected for this study. Markets may be inefficient for other reasons too. Grossman and Stiglitz (1980) argue that perfect informationally efficient markets are impossible, because if markets are perfectly efficient the profits from trading on information would be zero while the cost of gathering and trading on information is positive. In other words, either markets are inefficient to a point in order to ensure enough profit opportunities or the markets would collapse. The profit opportunities can arise from different reasons. They can be viewed as economic rents derived by information-seeking investors. The profits that accrue an investment professional need not be market inefficiency, but may simply be the fair reward to the breakthroughs in financial technology or other competitive advantage (e.g., superior information). They may come from the presence of noise traders, i.e. investors who trade on what they think is information but is in fact merely noise. They may be the result of investors who trade for reasons other than information, e.g. unexpected liquidity needs. So, this is rather a difficult task on the part of both the economists and the finance practitioners to confirm why a particular financial market is inefficient. Since the central aim of this paper is to simply sketch the nature of the foreign exchange market efficiency, we do not elaborately focus on the institutional and economic factors/reasons that affect market efficiency of the exchange rates examined. While the existing literature on random walk test in stock market is rich, there is not remarkable research on random walk and efficiency tests in the foreign exchange rates of the Asia-Pacific countries. There are, of course, numerous studies on different aspects of foreign exchange market. In the 1980s, several studies examine the random walk and efficiency tests in foreign exchange markets. Darby (1983), Adler and Lehmann (1983), Huizinga (1987), Baillie and Selover (1987) and Taylor (1988) apply the unit root tests to examine the random walk behavior in the exchange rates of developed countries. All these studies fail to reject the unit root hypothesis for the real exchange rate. Coughlin and Koedijk (1990) and Lothian (1990) conduct the random walk test using the (Dickey-Fuller and Augmented Dickey-Fuller) unit root tests and cointegration tests. The Ng and Perron (2001) tests were not developed at the time the above studies were conducted. Of the recent studies, Jeon and Seo (2003), Chortareas and Kapetaneos (2003), Chen and Leung (2003), Aroskar et al. (2004), Sweeney (2006), Chu and Lu (2006) and Phengpis (2006) use different tests to study the foreign exchange market efficiency. But, they neither apply the Ng and Perron (2001) tests nor the variance ratio tests. We choose the Ng and Perron's (2001) methodology because the test itself has four tests. Ng and Perron (2001) argue that their modified AIC (MIC) provide those tests with desirable size and power properties. In order to check whether the results from the Ng and Perron (2001) tests (that are applied to the individual time series) are robust to the use of panel data techniques, we implement different types of panel unit root tests assuming both the common unit root process and the individual unit root process. Liu and He (1991), Smoluk et al. (1998), Wright (2000), Lee et al. (2001) and Chang (2004), among others, employ the variance-ratio tests to the foreign exchange market efficiency. We focus on diverse markets in the Asia-Pacific region. The major purposes of this paper are identified as follows: (i) to examine the random walk behavior in 12 Asia-Pacific foreign exchange markets following the Asian currency crisis; (ii) to detect whether the exchange rate series have unit root components; (iii) to compare the inferential outcomes of the variance-ratio tests of Lo and MacKinlay (1988) with that of Wright (2000) as regards the martingale behavior for the period from January 1998 to July 2007. The rest of the paper is organized as follows. Section 2 describes the methodologies and, reports the critical values obtained through Monte Carlo Simulation. Section 3 discusses the data structure. Section 4 demonstrates the empirical findings. The paper ends with some concluding remarks in Section 5.
نتیجه گیری انگلیسی
The purpose of this study was to report the differential outcomes from the econometric applications in explaining the financial market behavior and efficiency. Since the inferences are subject to change, it is very difficult to simply rely on estimation techniques in drawing conclusions on the market efficiency. Two major properties of the random walk hypothesis: (i) the unit root component and (ii) the martingale hypothesis are markedly observed in almost all currencies in the short-horizon but not in the long-horizon. For the inefficient markets in the short-horizon, the influence of the central bank and of the currency board should be reduced to turn these markets into efficient ones. Using both high and medium frequency data, the Wright's (2000) VR tests give fairly consistent results in terms of iid/mds null violations. But the L–M VR tests give mixed results under the assumption of homoskedasticity and heteroskedasticity. Further, the L–M VR tests are characterized as consistent for the weekly data. We can draw several other conclusions from the findings. Since the daily data reflect the most new information in the prices, we find that the majority of the exchange rate series exhibits a random walk and hence there is not much motivation for the investors. But, some of the investors usually hold the currencies in their portfolios for more than one trading days to offset any loss from the daily trading. In that case, weekly data can be taken to draw conclusions. The results from the weekly data indicate that the returns from the majority of the exchange rates investigated are correlated and consequently, the random walk hypothesis can be strongly rejected for these markets. Based on this, investors try to bet on speculative/arbitrage opportunities. In both cases, investors should carefully evaluate the risks involved with the currencies they trade, the relevant financial market policies and the foreign exchange rate regimes. In the markets where the access to the official exchange market is limited, there is the dominance of parallel/black markets. In these markets, policy implications should be linked to the low and medium frequency data. It is true that the inferences would differ across the data sets taken for analysis. Any policy implications should be linked to the exchange rate regime, the size and the development of the financial markets. This is because there is much reason to find the evidence of market efficiency for the developed market with the high frequency data but not with the low or medium frequency data. The reverse is true for the emerging/underdeveloped markets, where the policies should be linked to the low or medium frequency data. Our results indicate that the markets are efficient with the high frequency data but not with the medium or low frequency data. One of the policies toward making these markets efficient is to adopt financial deregulation measures, including the relaxation of foreign exchange market intervention and allowing an expanded role of the foreign banks to increase the scale and scope of the markets and products. Otherwise, the inter-temporal market inefficiency as observed in some markets with the long holding period and/or low frequency data may persuade the investors to take risky decisions on the currencies they deal. In this case, mostly the small investors suffer both profit and capital losses unless they trade in the parallel/black markets, where the access to official exchange market is restricted and/or online trading is yet to be developed. The natural development of the capital market is also hindered. In the developed markets where trading is mostly handled online and the speculative positions are less than a minute, the small investors cannot wait for long to take investment decision. If they do so, they will make huge losses that cannot be replenished by a meager amount of capital. On the contrary, the large investors have the ability to allow the prices to fluctuate and adjust with new market information. Nonetheless, both the risks and gains for them are enormously high and any bad information would result in losses for them as well but their capital is sufficient to cover the losses to survive in the trading. The paper ends with some future research directions. While the paper explores a number of bilateral exchange rates with the US, not all the currencies, however, behave under free-floating. Some countries, as noted in Appendix C, are found to maintain a peg with the Dollar. Thus, some of the markets are not efficient due to the policy of exchange rate regulations that they follow. It is to note that bilateral exchange rates do not describe fully the triangular nature of nominal prices. For instance, the bilateral exchange rate of Korea and Japan with the US and its evolution also affects the behavior of the exchange rate between Korea and Japan by arbitrage. This suggests that exchange rates are interdependent, and in turn may be quite often correlated. Since exchange rates (and their innovations) are potentially correlated, it may be more sensible to explore the time series properties of the data jointly for all countries. Future researcher may try to explore these issues considering the exchange rate regimes and the factors that affect the inefficiency of foreign exchange markets.