Information Environment Quality and its Impact on Return and Investment Decision
This study contributes to literature in four ways to explore the dynamics of stock price synchronicity (SPS). Firstly, it tests the weak form of market efficiency. Secondly, measures the effect of information environment on SPS by using firm specific variables i.e. liquidity, illiquidity, cost of information, trading cost and investor attention. Thirdly, this study attempts to investigate the relationship between information environment and foreign investment. Fourthly, role of information environment premium or SPS premium in explaining equity returns is explored.
This study investigates the weak form of efficiency of Karachi stock exchange using a set of parametric and non-parametric tests that include Jarque-Bera and Kolmogrov-Smirnov (KS) test for normality, autocorrelation and Run test for autocorrelation, Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) for stationarity and multiple variance ratio (MVR) test. The results of the study indicate that daily, weekly and monthly returns do not follow random walk. So, investors can use technical analysis to devise investment strategies.
This study also examines the relationship between SPS and firm specific variables associated with information environment. Results indicate that age, size, institutional ownership, book to market ratio, trading cost, liquidity, illiquidity and returns have significant impact on SPS. Various proxies of liquidity and illiquidity are used to test the robustness of results. These proxies include volume, turnover rate, value traded, Amihud illiquidity and percentage of zero volume days. The results suggest that the differences in idiosyncratic volatility are not linked with the more or less information of firm specific attributes. It appears to be linked with noise in returns. Findings of this study are in line with West (1988) and Lettau Malkiel and Xu (2001). This study further suggests that low stock price synchronicity is a result of imbedding of firm specific variables information in to stock prices. If quality of information environment is good, market model R square will be higher represented by large institutional holding, greater age, lower trading cost, large size, value stocks, low illiquidity, high liquidity and large information events.
In next phase, this study examines the relationship between foreign investment and information
environment. Results indicate that Institutional ownership, age, trading cost, size, liquidity and illiquidity influence foreign investment. Institutional ownership, size and percentage of zero volume days have significant and positive impact on foreign investment and trading activities have negative association with foreign investment. Such deviations might be the effect of herding, noise trading and instable dynamics of emerging markets.
Finally, this study explores the impact of size premium, value premium, information efficiency premium on average equity returns using the methodology proposed by Fama and French (1992, 1993). Result indicates that size premium, values premium and information efficiency premium are priced by the market. Market premium, size premium, value premium and information efficiency premium significantly explain equity returns in single factor, three factor and four factor model. Capital asset pricing model (CAPM) is valid for explaining average equity returns but multifactor model captures additional information. Therefore, it can be concluded that size premium, value premium and information efficiency premium are considered as systematic risk and priced by the market.