Computational Risk Management for Strategic Investors: An Engineering-Inspired Approach to Portfolio Diversification - Hasan, Nonce; Rahim, Robbi; Sapinah, Sapinah; Pramono, Susatyo Adhi; Abroza, Ahmad (PT Mattawang Mediatama Solution, 2025)
This study presents an engineering-inspired approach to computational risk management, focusing on portfolio diversification strategies for strategic investors. Utilizing Monte Carlo simulation techniques, we assess the Value at Risk (VaR) of two prominent companies in Indonesia’s entertainment sector: MD Pictures Tbk (FILM) and MNC Studios International Tbk (MSIN). Daily return data from January 2022 to December 2022 are analyzed to evaluate both individual and combined risk-return profiles. The results show distinct characteristics between the two stocks, with FILM exhibiting a higher average daily return (0.42%) but greater volatility (standard deviation of 4.01%), compared to MSIN's more moderate return (0.33%) and lower volatility (3.64%). At a 95% confidence level, VaR estimates indicate potential maximum daily losses of 6.12% for FILM and 5.81% for MSIN. When combined into an equally weighted portfolio, significant diversification benefits emerge, reducing portfolio standard deviation to 2.77% and improving the VaR to 4.58%. This represents a risk reduction of 25.2% compared to FILM and 21.2% compared to MSIN. For a hypothetical investment of IDR 100 million, these improvements translate to reduced potential daily losses of IDR 1,540,482 and IDR 1,229,142 respectively. The findings demonstrate that even within a single industry, effective risk management can be achieved through strategic intra-sector diversification when constituent firms differ in business model and operational focus. This research bridges the gap between financial engineering and strategic portfolio management by offering a quantitative, simulation-based framework that supports informed decision-making for risk-conscious investors.