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Articles by Vinayagamoorthi Vasanth
Total Records ( 2 ) for Vinayagamoorthi Vasanth
  Sigo Marxiaoli , Murugesan Selvam , Kasilingam Lingaraja and Vinayagamoorthi Vasanth
  Prediction of financial markets, especially prediction of highly volatile stochastic stock market indices, plays a crucial role in identifying profitable investment avenues by the financial investors at large. The investing community encompasses retail investors, financial institutions, investment banks and Foreign Institutional Investors who look for the creation of wealth in the form of capital appreciation and earning the title of ownership of business enterprises by investing in the securities market, through buying and selling of shares of stock exchange listed corporate entities. The forecasting of dynamic financial market movements is one of the scientific endeavours which demands a great deal of market intelligence, financial acumen and domain knowledge of the characteristics of behavioural finance in a wider spectrum. This paper aims to discuss the non-linear movement pattern/trend of the most active two stock indices of India, namely, the Sensex and Nifty, during the study period from 2009-2015 by applying the traditional logistic regression method and one of the neural network tools, namely, k-nearest neighbourhood algorithm. This study would help the investors to streamline their investment patterns and strategies in order to take well informed investment decisions and optimize their stock returns by using the relevant market information.
  Kasilingam Lingaraja , Murugesan Selvam and Vinayagamoorthi Vasanth
  The dynamic linkages between emerging Asian stock market indices and developed stock market index are examined in this study. Asian stock markets attract huge inflows of portfolio investments which promote the economic development in the continent. The purpose of the study is to make a better-quality point with respect to Dynamic Linkages among the Emerging Stock Market returns in Asia and Developed Stock Market (USA-Dow Jones Industrial Average). This study was based on secondary daily time series data for a period of 12 years from 1st January, 2002 to 31st December, 2013. Statistical tools like descriptive statistics, unit root, correlation matrix and Granger Causality Test were employed. It was found that the emerging stock market indices of Asia, namely, S&P CNX Nifty (India), FTSE Bursa (Malaysia) and Philippine Stock Index (Philippines), recorded dynamic linkages with Dow Jones Industrial Average (USA) and the other five Asian emerging market indices (i.e., SSE Composite Index (China), Jakarta Composite Index (Indonesia), Korea Stock Exchange Index (Korea), TSEC Weighted Index (Taiwan) and SET Index (Thailand)) did not develop dynamic linkages with USA (DJIA), a developed country. The findings of this study would help the investors in making efficient investment decisions in the indices of emerging stock markets in Asia.
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