Evaluating Markowitz Portfolio Performance, CvaR, and Monte Carlo Simulation: Evidence from MSCI Indonesia
DOI:
https://doi.org/10.32832/neraca.v21i2.24459Keywords:
Markowitz, Portfolio Performance, Tail risk, MSCI, CVaRAbstract
This research analyzes the formation of an optimal portfolio, evaluates potential extreme risks, and measures the performance of stocks listed on the Morgan Stanley Capital International Indonesia index during the 2024-2026 period. The study addresses four primary objectives using the Markowitz model to establish optimal asset allocations. The methodology utilizes computational solver constraints to generate an efficient frontier without short selling, incorporating annualized daily expected returns and the Indonesia Government Yield Curve as the risk-free proxy. Extreme risk is assessed via the Conditional Value at Risk approach to capture maximum loss potential, followed by Monte Carlo simulation to project future investment outcomes under various market scenarios. Furthermore, portfolio performance is comprehensively evaluated using the Sharpe, Treynor, and Jensen Alpha ratios. The findings indicate the optimization process successfully identifies an asset combination maximizing expected returns relative to acceptable risk. Performance measurements and simulations reveal how the optimally constructed portfolio compares against market benchmarks in Indonesia, providing investors with a quantitative framework for mitigating equity investment risks.
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