Capital Market Efficiency in Asia: An Empirical Analysis (original) (raw)

Abstract

This paper aims to test efficiency, in its weak form, in the capi­tal markets of the Philippines (PSEi), South Korea (KOSPI), Indonesia (JKSE), Thailand (SET), Malaysia (KLCI), China (SSEC) and Hong Kong (HSI) over the period from January 2, 2017, to February 17, 2022. The return series shows signs of deviation from the normality hypothesis, given the skewness and kurtosis coefficients. The results, therefore, support the conclusion that the random walk hypothesis is not supported by the indices, the values of the variance ratios are in all cases less than unity, implying that the returns are autocorrelated over time and there is mean reversion in all indices. The re­sults obtained allow for the rejection of the random walk hypothesis and the informational efficiency hypothesis of financial markets. These findings also open room for market regulators to pursue measures to ensure better infor­mation in these regional markets.

Figures (6)

Table 1. The name of countries and their indices used in this paper. 3.2. Methodology The research will develop over several stages. In the first stage, we will elaborate graphs, in re- turns, to estimate the evolution of Asian capital markets. The sample will be characterized us- ing descriptive statistics, to verify if the data follow a normal distribution. To assess whether the

Table 1. The name of countries and their indices used in this paper. 3.2. Methodology The research will develop over several stages. In the first stage, we will elaborate graphs, in re- turns, to estimate the evolution of Asian capital markets. The sample will be characterized us- ing descriptive statistics, to verify if the data follow a normal distribution. To assess whether the

Notes: DataStream: January 2, 2017, 1260 data point. Figure 1 shows the evolution, and return, of the 7 stock markets in Asia under analysis. All se- ries show a relatively high dispersion around the mean, as well as relatively synchronized behav- iour between the data series. Through graphical analysis, it is possible to observe the existence of sharp structural breaks due to the significant drop in stock prices, which led to a bearish period in the markets under analysis. This evidence was also found by the authors, Dias, Teixeira, Macho- va, et al. (2020), Dias and Pereira (2021), Dias, Heliodoro, Alexandre, Santos, and Farinha (2021).

Notes: DataStream: January 2, 2017, 1260 data point. Figure 1 shows the evolution, and return, of the 7 stock markets in Asia under analysis. All se- ries show a relatively high dispersion around the mean, as well as relatively synchronized behav- iour between the data series. Through graphical analysis, it is possible to observe the existence of sharp structural breaks due to the significant drop in stock prices, which led to a bearish period in the markets under analysis. This evidence was also found by the authors, Dias, Teixeira, Macho- va, et al. (2020), Dias and Pereira (2021), Dias, Heliodoro, Alexandre, Santos, and Farinha (2021).

Notes: ***, ** * represent significance at 1%. 5% and 10%, respectively. Table 2. Descriptive statistics, return, of the 7 Asian capital markets

Notes: ***, ** * represent significance at 1%. 5% and 10%, respectively. Table 2. Descriptive statistics, return, of the 7 Asian capital markets

Note: ** Probabilities for Fisher tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normality. Automatic lag length selection based on SIC: 0 to 10. Newey-West automatic ban- dwidth selection and Bartlett kernel. Table 3. Panel unit root test applied to the 7 Asian capital market: over the period from January 2", 2017 to February 17", 2022.

Note: ** Probabilities for Fisher tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normality. Automatic lag length selection based on SIC: 0 to 10. Newey-West automatic ban- dwidth selection and Bartlett kernel. Table 3. Panel unit root test applied to the 7 Asian capital market: over the period from January 2", 2017 to February 17", 2022.

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