Predicting performance of stock markets has been a quest for all investors. An investor relies on his understanding of Global cues and expert advice and would plan the investment strategy. This requires an intense effort to watch the market trends and factors influencing the markets carefully and be proactive in trading as per the cues. Many predictive models have been used to assess the market using mathematical tools like Machine Learning and other techniques which are complex for a normal person to grasp. With the globalisation of the economy, the stock markets have become closely correlated. This paper examines if the correlation of the stock markets can be used to predict the stock prices and a no-effort trading policy that performs auto-trades, without any intervention by the trader, can be derived. The study uses stock indices data for 2020 to predict behaviour of BSE SENSEX and selected stocks in 2021. Using the correlation, it derives a trading strategy to beat the market in 2021 to generate value that is higher than the rise in stock prices over 2021. Lagged indices are used to take advantage of different operating hours of the stock markets. Correlation models, polynomial relationships and mathematical models are used to carry out the analysis.

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Keywords: Investment Strategy, Global Cues, Globalisation, Correlation, Trading Strategy.