EURO 2024 Copenhagen
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2794. Value-at-Risk of an Option Portfolio Under Different Scenarios. A Proposal of a More Reliable Market Measure

Invited abstract in session TB-63: Risk Management and Cryptoassets, stream OR in Banking, Finance and Insurance: New Tools for Risk Management.

Tuesday, 10:30-12:00
Room: S14 (building: 101)

Authors (first author is the speaker)

1. Giacomo Gaggero
Department of Economics, University of Genoa
2. Pier Giuseppe Giribone
Department of Economics, University of Genoa
3. Duccio Martelli
Dept. of Economics, University of Perugia
4. Sanmoy Mukherjee
Department of Economics, University of Genoa

Abstract

Value at Risk is one of the most widely implemented methods in the financial sector for assessing the traditional market risk associated with a portfolio. We focus our attention on nonlinear pay-off derivatives such as options, proving the effectiveness of the proposed methodology also for non-standard options. To calculate the future projections of the analyzed portfolio, we implement a full-repricing forward-looking Monte Carlo method. Based on data from the last five years, we compute for each of the eleven stocks, on which options are written, the volatility implementing six different techniques (Close-to-Close, High-Low, High-Low-Close, EWMA, GARCH(1,1) methods and Implied Volatility), the dividend using two alternatives (Historical and Implied measures) and the drift using both traditional econometric approaches like ARIMA and innovative like LSTM technique. Subsequently, having estimated the volatility and the drift, we have implemented those for simulating the underlying prices for the next periods using a Geometric Brownian Motion. Doing this, we have used only the most prudential scenarios for the projection of the assets. We have consequently considered all the possible combinations for these inputs in the option pricing model, estimating the most reliable forward-looking fair value distributions of each option over the next days through 20,000 daily simulations. Value at risk has then computed taking the percentiles of this distribution.

Keywords

Status: accepted

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