تحقیقات تجربی از حجم معاملات و نوسانات بازده بازار سهام تایوان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|15715||2014||23 صفحه PDF||سفارش دهید||7216 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Global Finance Journal, Volume 12, Issue 1, Spring 2001, Pages 55–77
This study examines the Mixed Distribution Hypothesis (MDH) using 5-min interval stock returns of the Taiwan Stock Index (TSI). Startlingly enough, the persistence of stock volatility remains dominant after the stochastic mixing variable was included in the variance equation. It implies that the MDH cannot explain away the ARCH phenomenon. We have found that the composition of participants (approximately 92% of participants are individual investors) in TSI is a major contributing factor to the persistent volatility. In addition, the existence of limits on price changes, to some extent, accounts for the persistence phenomenon. Similar results are also found for individual stocks in the sample. Interestingly enough, the explanatory power of trading volume exhibits a U-shaped pattern in explaining return volatility in Taiwan Stock Market.
Taiwan, the orphan of Asia, has had more than her share of political vicissitude throughout her 400-year-old history. Prior to the war of 1895 in which Taiwan was seceded to Japan, the staple of export had been deer hides and camphor products under the rule of Dutch and Manchu regimes. During Japanese occupation, the lion's share of export hinges on sugar industry. It was not until early 1960s that Taiwan develops her sound export-oriented trade policy under the nationalist government. Since then, the bubbling economy of Taiwan is considered an example of successful economic development especially for Asian emerging economies. The fact that the Taiwan Stock Index (TSI) is included in Morgan–Stanley Emerging Market Free Index, World Free Index, and Fareast (except Japan) Free Index is testimonial to an ever increasing financial role Taiwan plays in the Asian market. Prior to the announcement (April 3, 1996), the Taipei market had gained 95 points with the closing index of 5127.49 valued at US$30.86 billion. On April 6, TSI rocketed to 5377.19 (valued at US$76.97 billion) with a sizable gain of 201.44 points in just 2 h. Because Morgan–Stanley index is one of the major guiding principles for portfolio managers, the inclusion of TSI makes the Taiwan market an attractive choice in international financial market. However, in an attempt to prevent the first popular presidential election (March 23, 1996) in Taiwan, mainland China launched a series of missile exercises around the island. As a consequence, TSI took a plunge to about 4700 points, but bounced back to approximate 5500 points as more positive information arrived. Since then, other economic upheavals and political jitters have caused TSI to be very sensitive to newly arrived information. Recent stock turmoils in Hong Kong, Taiwan, and other Asian emerging economies inevitably transmitted its volatility to the record 554-point plunge and 337-point, next-day rebound of the Dow Jones industrial average in October 1997. Hence, a careful examination of the variance equation of TSI can be of critical importance in understanding the nature of volatility in an emerging market. As pointed out by Huang (1995), only 5% of participants in TSI were institutional investors, with a great majority of 95%, individual investors.2 Such an unusual composition creates an environment, which is conducive to the formation of “irrational exuberance” in which individual investors focus primarily on short-term profit. As such, the great majority of TSI investors appears very jittery to the arrival of new information, while the fundamental aspects of firms play only a secondary role. No sooner had TSI (77 individual stocks) been included in the Morgan–Stanley Emerging Market Free Index and the Dow Jones World Index than the bubbling Taiwan market became a financial safari for foreign investment companies. A conservative estimate of new international investment on TSI is US$30 billion in the first 2 years. The flip side is that an emerging market in general does not have a well-structured financial system and lacks maturity in terms of market scales and regulations. Needless to say, the bottom line for many investors is the profitability (abnormal profit) of the Taiwan market, which inevitably begs to the question of the weak form efficient market hypothesis. Majority of studies of the efficient market hypothesis on TSI (e.g., Huang, 1995 and Huang & Yang, 1995) cannot find a serious deviation from the random walk hypothesis.3 Their conclusion, based on the variance ratio (VR) test and rescaled range (R/S) test, does not necessarily suggest an efficient market for TSI. The discrepancy between statistical results and the widely-held view about the Taiwan market may be attributed to (1) power of the statistics employed and/or (2) the limited information (only price variables are used). However, the R/S technique is known to be robust (with respect to Gaussian assumption), and the V/R technique is heteroscedasticity-consistent. They do not appear to have major flaw(s). Hence, it is likely that using only price data leaves out an important variable: quantity or trading volume, which may well lead to inadequate descriptions of the market. As Beaver (1968) put it, “An important distinction between the price and volume tests is that the former reflects change in the expectations of the market as a whole while the latter reflects changes in the expectations of individual investors.” Viewed in this perspective, it is important to examine joint distribution of both price and volume variables in order to provide more accurate statistical inferences. Well known in the literature, empirical investigations on speculative prices have revealed kurtotic properties as compared to the normal distribution. The leptokurtic distribution of rates of return is a sampling consequence, when data are pooled from a mixture of distributions (MD) with varying conditional variances. This is to say that statistical tests employing both price and volume variables tend to support the MD hypothesis. In this light, price data can be viewed as a conditional stochastic process with a changing variance parameter that can be proxied by volume (Karpoff, 1987). Simultaneous consideration of both price and volume variables could shed new light on the understanding of the financial market. Lamoureux and Lastrapes (1990) successfully used daily trading volume as the proxy variable for information arrivals.4 Their model or (LL model) shows that autoregressive conditional heteroscedasticity (ARCH) phenomena tend to vanish if volume is considered in explaining the return volatility. Because the mixed stochastic variables are often the cause of the leptokurtic distribution of stock returns, an inclusion of trading volumes as the proxy can explain away much of the nonnormality. In particular, trading volumes are found to be a good proxy for information arrivals in the US market (Lamoureux & Lastrapes, 1990). In the case of emerging markets, previous studies in general fail to include volumes into the analysis (e.g., the GARCH model by Huang, Liu, & Yang, 1995). This being the case, the objective of this paper is to apply the LL model to the Taiwan Stock Market in which individual investors constitute the lion's share of the equity market. In particular, we will test the MD hypothesis in this unique market. Such tests are instrumental in supporting or refuting the MD hypothesis and have the potential to provide intuitively clear interpretations to many ARCH-related empirical findings. Beyond that, we employ intraday data of different time segments. This approach is important because the returns and volumes within time intervals in a given trading day are known to be quite different from that at market open or market close. The segmentation of daily transactions into various subintervals can provide precious information to practitioners and academicians as well. The organization of the paper is as follows. Section 2 provides a description of the LL model. Section 3 explains the data and some basic statistics. Section 4 discusses empirical results of the Taiwan Stock Market for various time segments. Section 5 investigates the same phenomenon for each individual stock and explains why the result of the Taiwan Stock Market is different. The conclusion is given in the Section 6.
نتیجه گیری انگلیسی
The Taiwan Stock Market is known for its unusually high turnover ratio. Other than that, the majority of prior studies on TSI have found that the Taiwan market is very much in line with other developed stock markets. Their results are, in most cases, based on price variables only. That is, half of the information needed for an equilibrium market is missing. In the price–volume model, it is known that the ARCH effect is an artifact generated by a mixture of returns, with the rate of information arrivals being the stochastic mixing variable. After taking information arrival into account, the stock returns are expected to be normally distributed. Lamoureux and Lastrapes (1990), among others, support the MDH for the US market. Similarly, Fraser and Power (1996) verify the MDH for the emerging markets. However, their choice of proxy (unexpected innovation of market value) is rather different from trading volumes often used as the proxy by most researchers. In either case, the persistent volatility of stock returns declines significantly once the proxy is included. Surprisingly, such is not the case for the Taiwan market. The empirical evidence from our result does not support the MDH, and the persistence of stock return volatility still remains strong. In a nutshell, the persistent volatility of TSI perhaps has its root in the way it assimilates and disseminates information contents. Inasmuch as it prevails, the persistent volatility remains even after trading volume is included in the estimation. The failure to support the MDH in the Taiwan market can be attributed to two rather unique factors. First, the great majority of participants are short-term individual investors who fervently engage in speculative activities. Lacking fundamental analyses, their behavior can be characterized by overreaction to news announcements. Second, the price limits imposed by Taiwan Security Exchange Committee do contribute, to some extent, to the persistence of return volatility. Such price limits hinder the information transmission mechanisms; the price can only go down once the ceiling is reached. Hence it intensifies the return volatility. Combined with these two factors, history of Taiwan is replete with political and economic instabilities. The unfortunate past of Taiwan's history, to a great extent, accounts for overreactive and speculative behaviors in the market. Viewed in this perspective, the efficient market hypothesis for TSI needs to be reevaluated and reconsidered cautiously in the future.