Mean-Variance Portfolio Optimization in India's Capital Goods and Defense Sectors: An Empirical Markowitz Analysis (2023–2026)

Author

Nihal Pramod Gawas, Dr. Sarita Agarwal


Abstract

 This study examines whether the exceptional returns of Indian capital goods and defense equities between April 2023 and March 2026 reflect genuine risk-adjusted performance, and derives the optimal allocation under Markowitz's mean-variance framework. Daily price series for six NSE-listed firms (Larsen & Toubro, Siemens India, ABB India, Bharat Electronics, Hindustan Aeronautics, and Mazagon Dock Shipbuilders) are analyzed against the Nifty 50, using a 6.80% risk-free rate based on the 91-day Treasury bill. Standalone Sharpe, Treynor, and Jensen metrics are combined with a six-asset covariance matrix, and long-only portfolios are obtained through non-linear quadratic optimization using the Microsoft Excel Solver add-in. All six stocks outperformed the benchmark, with Jensen's alphas from +10.89% to +43.67%; the three defense public-sector units recorded Sharpe ratios of 1.5000 to 1.5906 against 0.5920 for the Nifty 50. The Max Sharpe portfolio allocates 89.13% to defense units and delivers a 51.81% CAGR at 20.89% volatility, a Sharpe ratio of 2.1548, which exceeds the equal-weighted portfolio (2.0223), the minimum variance portfolio (1.6473), and the benchmark. A 70:30 core-satellite structure with semi-annual, ±5% threshold-based rebalancing is proposed. Results are in-sample and conditioned on a defense capital-expenditure upcycle.



Keywords

Markowitz portfolio optimization; efficient frontier; Sharpe ratio; Jensen's alpha; Indian defense stocks; capital goods sector; asset allocation



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