Precise Stock Price Prediction for Robust Portfolio Design from Selected Sectors of the Indian Stock Market
Jaydip Sen, Ashwin Kumar R S, Geetha Joseph, Kaushik Muthukrishnan,, Koushik Tulasi, and Praveen Varukolu

TL;DR
This paper develops a method for precise stock price prediction within selected Indian market sectors to construct efficient portfolios, enhancing investment decisions through advanced optimization and backtesting techniques.
Contribution
It introduces a comprehensive approach combining multiple portfolio optimization methods with stock price prediction for improved portfolio performance in the Indian stock market.
Findings
Built minimum variance and optimal risk portfolios for five sectors.
Achieved high-precision stock price predictions for portfolio construction.
Demonstrated improved backtest performance over equal weight portfolios.
Abstract
Stock price prediction is a challenging task and a lot of propositions exist in the literature in this area. Portfolio construction is a process of choosing a group of stocks and investing in them optimally to maximize the return while minimizing the risk. Since the time when Markowitz proposed the Modern Portfolio Theory, several advancements have happened in the area of building efficient portfolios. An investor can get the best benefit out of the stock market if the investor invests in an efficient portfolio and could take the buy or sell decision in advance, by estimating the future asset value of the portfolio with a high level of precision. In this project, we have built an efficient portfolio and to predict the future asset value by means of individual stock price prediction of the stocks in the portfolio. As part of building an efficient portfolio we have studied multiple…
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