Stock market efficiency is an important concept in growing economy since it help in understanding the market risk and return behavior for investors and shareholders. Literature on market efficiency and return volatility behavior is plenty for a developed stock market. The study involves efficiency of the correlation matrix and co-integration model or CAPM. In this study we will investigate which of these models is efficient in investigating the efficiency of the stock. The study will forecast the stock of USA companies using there models; correlation matrix, co-integration model and CAPM model. Before modeling the stock and volatility, it very important to determine the efficient of the market. This is because the market inefficiency may slow down the flow of information on corporate performance for the participants, which create difficulties for investors to allocate their money optimally among different types of investments. The best model to model and forecast volatility will be determined using the ADF, the non-parametric Run test, and Philip-Prerron test.
Theoretical frame work
Efficient markets are necessary prerequisite if it is desired that funds should be allocated to the highest valued projects. A stock market is termed as efficient if the price fully reflects all information in the markets. Market efficiency and the risk return behavior in a number of emerging stock market economies have been examined by Bekaert and Harvey 91997). Volatility is the tendency of assets prices fluctuating either up or down. Increased volatility is perceived as indicating a rise in the financial risk which can adversely affect investor’s assets and wealth. According to Glosten et. al (1993), negative and often significant relationship between the volatility and return. Stock volatility has been received a great attention from practitioners because it can be used as a measure of risk in financial markets. The chinise stock market forecast of volatility using the Garch model was done by Hongyu and Zhichao (2006).
Design and methods
In this study, the forecasting of the stock market of USA stock market using the models correlation matrix, co- integration, and CAPM.
Null hypothesis: there is no significant evidence to conclude that there is significant difference in the three models to forecast the volatility in the stock market
Alternative hypothesis: there is significant evidence to conclude that there is significant difference in the three models to forecast the volatility in the stock market
The study will therefore empirically contributes to the literature available on the stock market by investigating the market form of efficient using the ADF test, non – parametric run test and Philip-Perron test. 4
|Proposal preparation, defense and corrections|
|Preliminary studies and modeling of the stock market in the three models|
|Computation of the forecast of the models and running the test in the analysis and compiling the results|
|Dissertation writing and defense|
Bekaert. G and Harvey. C. R (1997). Emerging equity market volatility. Journal of financial
Economics 43: 29 -77
Glosten L. R, Jagannathan, R, and Runkle D. E (1993). “ on the relation between the epected
value and the volatility of the nomimal ecess return on stock” journal of financial 48:
Hongyu. P and Zhichao, Z (2006). Forecasting financial volatility: evidence from chinese stock
market. Working paper in econonics and financial no 0602 university of Durham.
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