Abstract

This study evaluates the risk-adjusted performance of a diversified portfolio in the Indian financial market from 2011 to 2021, incorporating Nifty 50 stocks and new-age assets. Leveraging Monte Carlo simulations and mathematical optimization, the research identifies an optimal portfolio on the efficient frontier. Integration of the Black-Litterman model provides a comparative analysis, emphasizing the impact of investor views. Despite transaction costs, optimized portfolios outperform the Nifty 50 index, with the rebalanced portfolio demonstrating higher cumulative returns. Key findings include TCS. NS is a leader in share price, HDFCBANK.NS showcasing stability and alternative assets exhibit higher volatility but have the potential for amplified returns. This research offers valuable insights for investors seeking resilient strategies in the Indian financial landscape.

Keywords: Portfolio Optimization, Nifty 50, Monte Carlo Simulation, Transaction Costs, Rebalancing Strategies

How to Cite:

Meher, P. & Mishra, R. K., (2024) “Risk-Adjusted Portfolio Optimization: Monte Carlo Simulation and Rebalancing”, Australasian Accounting, Business and Finance Journal 18(3), 85-101. doi: https://doi.org/10.14453/aabfj.v18i3.06