Machine Learning Based Automated Trading Strategies for Indian Stock Market

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Rajesh Dey, Salina Kassim, Sudhanshu Maurya, Rupali Atul Mahajan, Arup Kadia, Monika Singh

Abstract

Stock market is a very important and one of the main financial platforms for a country. It measures the growth of all financial components associated with the base of economy. Firms can raise capital through bonds, IPO, FPO etc. and investors can participate in this market. Different stock exchanges are regulatory bodies are responsible to regulate the system and provides the platform to the investors for the participation into market. In India investors participating in this marketplace over than 10 crores demat accounts. Investors analyses the fundamental, technical, price action and different research on the financial parameters of market or stocks before investing. This Machine Learning and Artificial Intelligence based proposed research provides an automated platform for the Indian investors to take decision about a strategy considering the different financial tools and price action. This research considering candlestick pattern and Exponential moving average (EMA) (10,50,100 and 200 EMAs) crossover together. Now a days large portfolio investors and different international financial intuitions such as Morgan Stanley, JP Morgan, Bank of America and the different domestic institutions such as LIC, SBI, HDFC mutual fund using different algo trading strategies for trading and investing.

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References

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