Static Pricing of Exotic Derivatives Under Conditional Value-at-Risk (CVaR) in Incomplete Markets

This paper optimizes portfolios using Conditional Value-at-Risk (CVaR) as a risk measure with tradable assets such as cash, call and put options on the S&P 500. It develops a static pricing model for the buy-and-hold strategy and evaluates dynamic strategies. The CVaR model is compared to the mean-variance model, demonstrating its ability to minimize CVaR while achieving required returns and showing sensitivity to parameters, namely, the shape of the variance-gamma distribution, volatility, confidence level, and required return. Although the mean-variance model results in lower standard deviation, the CVaR-based optimization consistently yields lower CVaR values. For portfolios with liabilities, the model incorporates hedging strategies for standard European call option and Exotic options such as quadratic, log, digital, sine, and butterfly spread options in an incomplete market. The CVaR-based approach demonstrates risk reduction and robustness in the backtesting.

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Publication Details

Journal
Computational Economics
Published
2025-04-16
DOI
https://doi.org/10.1007/s10614-025-10938-9
Citations
1
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
2.21

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article

Static Pricing of Exotic Derivatives Under Conditional Value-at-Risk (CVaR) in Incomplete Markets

Udomsak Rakwongwan, Ratinan Boonklurb, Benyanee Kosapong
1 citations
Computational Economics
Stochastic processes and financial applications
2.21
article

Static Pricing of Exotic Derivatives Under Conditional Value-at-Risk (CVaR) in Incomplete Markets

Udomsak Rakwongwan, Ratinan Boonklurb, Benyanee Kosapong
article en
1 citations

Abstract

This paper optimizes portfolios using Conditional Value-at-Risk (CVaR) as a risk measure with tradable assets such as cash, call and put options on the S&P 500. It develops a static pricing model for the buy-and-hold strategy and evaluates dynamic strategies. The CVaR model is compared to the mean-variance model, demonstrating its ability to minimize CVaR while achieving required returns and showing sensitivity to parameters, namely, the shape of the variance-gamma distribution, volatility, confidence level, and required return. Although the mean-variance model results in lower standard deviation, the CVaR-based optimization consistently yields lower CVaR values. For portfolios with liabilities, the model incorporates hedging strategies for standard European call option and Exotic options such as quadratic, log, digital, sine, and butterfly spread options in an incomplete market. The CVaR-based approach demonstrates risk reduction and robustness in the backtesting.

Computational Economics
Chulalongkorn University (TH), Kasetsart University (TH)
National Research Council of Thailand
Openalex Percentile: Top 15%
Stochastic processes and financial applications
2.21
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Static Pricing of Exotic Derivatives Under Conditional Value-at-Risk (CVaR) in Incomplete Markets — Udomsak Rakwongwan, Ratinan Boonklurb, et al. · Computational Economics (2025) | TGRS Research Map | TGRS