• MKNair

Stock market indices help to identify the broad trends in the markets and is important for the investor to know the index value to earn profit. Prediction of stock prices has got a very significant role in today’s economy, since a reasonably accurate prediction has the possibility to yield high financial benefits and hedge against market risks. In this work, Nifty, the index for the National Stock Exchange of India Ltd. (NSE) is taken to represent Indian stock market and the influence of selected Asian stock market indices on Nifty is studied. The Asian stock market indices considered for this study are Straits Times Index(FTSE) representing Singapore’s stock market index, HangSeng representing Hongkong’s stock market index, KOSPI representing South Korea’s stock market index, Nikkei225 representing Japan’s stock market index, Shanghai Composite Index (SSE) representing China’s stock market index, and TSEC representing Taiwan’s stock market index. The correlation and regression of Nifty with these selected asian stock indices were analysed with the help of machine learning techniques Linear regression and Gradient boosting regression. It is found that there exists a relationship between NSE and the selected Asian stock markets and these Asian markets could be used for predicting changes in Indian stock market. This study suggests that the gradient boosting regression method yields better results when compared to linear regression method in prediction of Nifty with respect to these selected asian stock market indices.

A STUDY OF RELATIONSHIP BETWEEN INDIAN AND ASIAN STOCK MARKETS USING MACHINE LEARNING TECHNIQUES

"A STUDY OF RELATIONSHIP BETWEEN INDIAN AND ASIAN STOCK MARKETS USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 2, page no.228-234, February-2017, Available :http://www.jetir.org/papers/JETIR1702037.pdf

"A STUDY OF RELATIONSHIP BETWEEN INDIAN AND ASIAN STOCK MARKETS USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 2, page no. pp228-234, February-2017, Available at : http://www.jetir.org/papers/JETIR1702037.pdf