Keene and Peterson (2007) conducted a study of the importance of the role of liquidity in the asset pricing model during the period July 1963 to December 2002 using six measures of liquidity. Other market conditions also analyzed in this study were the effect of liquidity in emerging capital markets compared to developed capital markets. This study uses data from the emerging capital market, the Indonesia Stock Exchange, and the developed capital market, the Tokyo Stock Exchange, to examine the effect of liquidity in the two conditions of the capital markets.
Investors' needs for liquidity should lead the investor to impose liquidity as one of the sources of risk in investment, especially in stocks. The concept of liquidity in this study includes immediacy, which is reflected in the concepts of stock turnover and depth, which are represented by the value of transaction volume. Keene and Peterson (2007) conducted a study about the importance of the role of liquidity in asset pricing models.
Bullish and bearish market conditions are closely related to investors' preference for the liquidity of its assets, which may describe the validity of the time-varying risk premium concept, as investor behavior in terms of liquidity is also influenced by the capital market itself. Meanwhile, the level of liquidity variability consists of the standard deviation and the coefficient of variation of turnover and trading volume (Chordia, Subrahmanyan, and Anshuman, 2001). BM: The average portfolio return of companies with a high book-to-market is subtracted from the average return of the low book-to-market.
Researchers will use the average value of the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange and the NIKKEI 225 index for the Tokyo Stock Exchange in determining market conditions.
Results
The liquidity level of the company can also be derived from the turnover value, trading volume and trading volume value. Extreme minimum value, which is close to zero for the amount of liquidity, shows that there are stocks that have made very few low-value trades during the observation period. Table 3 generally shows that there is no pattern in the correlation between risk and return.
The same can be observed in the volume liquidity size, the portfolio with the highest risk is also portfolio 5 with a standard deviation value of 0.113, but the portfolio with the highest average return value is a portfolio 2 with an average value of -0033. Information: Portfolio formed for each of the liquidity size based on company size, liquidity and book-to-market category over 72 months of the observation period. Information: Portfolio formed for each liquidity size based on company size, liquidity and book-to-market category over 72 months of the observation period.
The reason for portfolio formation using mimic factor is to get the liquidity value that is free from the influence of other risk variables that have had a strong correlation with stock returns, especially the size of the company. The average value of the factor imitating portfolio for the turnover stock size is -0018, while the average. For variability magnitude of liquidity, the mean value of the standard deviation of the turnover and trading volume is 0.022 and 0.017 respectively and the mean value of the coefficient of variation of the turnover and trading volume is 0.002 and 0.003 respectively.
The entire sample of companies in each of the capital markets will be entered into eight portfolio categories in accordance with the portfolio construction methodology. The returns of the eight portfolios formed will then be used as the dependent variable in regression analysis with residual liquidity of factor mimicking portfolio as an independent variable. Total regression tests for hypothesis one have been run a whopping 48 times (8 portfolios x 6 liquidity size) for each of the capital markets.
211 The results of the regression test for the Tokyo Stock Exchange hypothesis also show a similar result to the Indonesia Stock Exchange. The magnitude of equity turnover liquidity may explain the returns of the six portfolios of the eight portfolios formed. The test will be conducted through regression analysis using dummy variables to describe the state of the bullish and bearish market.
The liquidity factor will be able to explain most of the portfolio return for all measures of liquidity. A correlation pattern between liquidity and returns is also seen, but the test of the regression results does not support the third hypothesis.
Conclusion, Implications and Limitations Research
215 one of the sources of risk and its influence on the investment return in the development of CAPM models, such as the intertemporal CAPM or conditional CAPM. The test results for the three hypotheses indicate that liquidity factors have different effects on equity returns in emerging and developed capital markets. These results provide information that investors cannot use the liquidity factor to distinguish the characteristics of the Indonesian Stock Exchange and the Tokyo Stock Exchange.
This is useful for those investors who have a portfolio of stocks in both capital markets to determine the most suitable investment strategy related to the liquidity of the stock. It shows that the size of liquidity with the dimensions of immediacy, which is reflected in stock market turnover and depth, which is represented by the value of trading volume, cannot capture the differences in the characteristics of capital market development. Some other significant things found in this study are the correlation pattern between liquidity and returns of stocks in a portfolio of stocks with different liquidity characteristics.
Liquidity has a negative impact on high liquidity stock returns and positively impacts a low liquidity stock portfolio. Investors can use these results to calculate stock returns by considering the characteristics of the liquidity portfolio of stocks to be purchased or already owned. In this case, risk would have a different effect on equity returns in different liquidity conditions.
The results of this study can be the basis of the development of subsequent research on the impact of liquidity on stock returns. Amihud, Y., 2002, Illiquidity and stock returns: Cross-sectional and time-series effects, Journal of Financial Markets5, 31–56. Banz, R.W., 1981, The relationship between returns and market value of common stocks, Journal of Financial Economics 9, 3-18.
Breeden, D.T., 1979, An intertemporal model of asset pricing with stochastic consumption and investment opportunities, Journal of Financial Economics 7, 265-296. Chen, S, 1982, An examination of the risk-return relationship in bull and bear markets using time-varying betas, Journal of Financial and Quantitative Analysis. Francis, 1977, Stability tests for alpha and beta over bullish and bearish market conditions, Journal of Finance.
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