CORRECTING THE BIASEDNESS OF VALUE-AT-RISK AND CONDITIONAL TAIL EXPECTATION ESTIMATORS

• Main Author: FAJRI RAHMI (NIM: 10113087), NUZULIA
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/23611
• Institution: Institut Teknologi Bandung

Stocks and Options are investment instruments. Investments are prone to the risk of losses caused by, for example, market risk. The risks of losses need to be measured so that investors may be able to make plans to mitigate the loss. In practice, the variance of the return on investment is often used to measure investment risk. <br /> However, in order to manage the risk more appropriately, other risks measures are needed. This final project (tugas akhir) discusses two risk measures, namely the Value-at-Risk (VaR) and the Conditional Tail Expectation (CTE). These risk measures require the calculation of the quantiles of a loss distribution. VaR is defined as the maximum loss that can be tolerated to a certain level of significance. <br /> CTE measures losses in terms of the expectation of the excess of a particular VaR. In this final project, a number of estimators for the VaR and CTE are discussed. <br /> The biasedness of such estimators are measured and corrected. The Monte Carlo simulation and the Bootstrap method are used to measure the biasedness. biasedcorrected <br /> estimators are then applied to estimate the VaR and the CTE of the loss distribution of the returns of an investment on a particular stock.