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Risk Analysis of Stock Portfolios Using Value at Risk (VaR) with the Extreme Value Theory Approach (Case Study: Banking Sub-sector Stocks Period May 1, 2019 - May 31, 2025)
This document contains the R code syntax and computational workflow for an undergraduate thesis focusing on the risk analysis of a stock portfolio within the Indonesian banking sub-sector (BBCA, BBNI, BBRI, BMRI, and BRIS). This analysis specifically estimates market risk—rather than seeking an optimal portfolio—using the Extreme Value Theory (EVT) approach to capture fat-tail phenomena and extreme events in the capital market.
A crucial step in this computation is data transformation, where the log returns are multiplied by -1. This transformation is mandatory to invert the distribution direction so that the loss metric can be accurately modeled using extreme value theory.
