• International Area Studies Review
• /
• v.13 no.2
• /
• pp.255-276
• /
• 2009

This article has examined the international transmission of returns among S&P500, Nikkei225 and SENSEX stock index cash markets using the daily closing prices covered from January 4, 2002 to February 6, 2009. For this purpose we employed dynamic time series models such as the Granger causality analysis and variance decomposition analysis based on VAR model. The main empirical results are as follows; First, according to Granger causality tests we find that S&P500 stock index has a significant prediction power on the changes of SENSEX and Nikkei225 stock index market and vice versa. However, US stock market's influence is dominant to the other stock markets at a significant level statistically. Second, according to variance decomposition, SENSEX stock index is more sensitive to the movement of S&P500 than that of Nikkei225 stock index. These kinds of empirical results shows that the three stock markets are integrated over times and these results will be informative for the international investors to build the world-wide investment portfolio and risk management strategies, etc.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.741-749
• /
• 2021

The research paper endeavors to investigate the presence of seasonal anomalies in the Indian equity market. It also aims to verify the notion that equity markets are for long-term investors. The study employs daily index data of Sensex, Bombay Stock Exchange, to understand its volatility for the period ranging from January 2001 to August 2020. To analyze the seasonal effects in the stock market of India, multiple regression techniques along with descriptive analysis, graphical analysis and various statistical tests are used. The study also employs the rolling returns at different time intervals in order to understand the underlying risks and volatility involved in equity returns. The results from the analysis reveal that daily and monthly seasonality is not present in Sensex returns i.e., investors cannot earn abnormal returns by timing their investment decisions. Hence, the major finding of this study is that the Indian stock market performance is random, and the returns are efficient. The other major conclusion of the research is that the equity returns are profitable in the long run providing investors a hope that they can make gains and compensate for the loss in one period by a superior performance in some other periods.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.311-324
• /
• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.