CONSTRUCTION OF OPTIMAL PORTFOLIO WITH REFERENCE TO NSE: AN EMPIRICAL STUDY
DOI:
https://doi.org/10.29121/shodhkosh.v5.i1.2024.4755Keywords:
Optimal Portfolio, Beta Ratio, Nifty 30 Stocks, Risk And ReturnAbstract [English]
This study examines the construction of an optimal portfolio from the top 30 stocks of the Nifty 50 index using data collected from May 2020 to June 2023 to capture evolving market dynamics in a post-pandemic environment. Stocks are selected based on market capitalization to ensure representation of the leading Indian companies, and risk and return metrics—including mean return, standard deviation, and beta—are computed for each stock. Sharpe’s Single Index Model is employed to evaluate the risk-adjusted performance of these securities, with a particular focus on calculating the Excess Return to Beta Ratio by comparing each stock’s excess return over a risk-free rate of 7% with its beta. Stocks are then ranked based on these ratios to identify those that deliver the highest return per unit of risk, and a unique cutoff rate of 0.0110 is determined by aggregating cumulative risk-return measures across the sample. Only stocks that exceed this cutoff rate are selected for inclusion in the optimal portfolio, ensuring that only securities with robust risk-adjusted returns are retained. The results reveal that stocks such as HINDUNILVR, TCS, and HDFC BANK exhibit the highest Excess Return to Beta Ratios, indicating superior risk-adjusted performance. Moreover, the constructed portfolio outperforms the benchmark index by achieving a risk-adjusted return improvement of approximately 15%. This outcome demonstrates an effective balance between systematic and unsystematic risk, thereby supporting disciplined portfolio construction. The quantitative approach provides a robust framework for risk management and informed investment decisions. These findings offer valuable insights for portfolio managers and investors seeking to optimize returns while mitigating risk. Ultimately, the study confirms that the application of advanced quantitative models like Sharpe’s Single Index Model can significantly enhance portfolio performance in dynamic market conditions.
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