Pricing and Hedging Contingent Claims by Entropy Segmentation and Fenchel Duality

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY
José L. Vilar-Zanón, Barbara Rogo
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引用次数: 0

Abstract

We present a new approach to the problem of characterizing and choosing equivalent martingale pricing measures for a contingent claim, in a finite-state incomplete market. This is the entropy segmentation method achieved by means of convex programming, thanks to which we divide the claim no-arbitrage prices interval into two halves, the buyer’s and the seller’s prices at successive entropy levels. Classical buyer’s and seller’s prices arise when the entropy level approaches 0. Next, we apply Fenchel duality to these primal programs to characterize the hedging positions, unifying in the same expression the cases of super (resp. sub) replication (arising when the entropy approaches 0) and partial replication (when entropy tends to its maximal value). We finally apply linear programming to our hedging problem to find in a price slice of the dual feasible set an optimal partial replicating portfolio with minimal CVaR. We apply our methodology to a cliquet style guarantee, using Heston’s dynamic with parameters calibrated on EUROSTOXX50 index quoted prices of European calls. This way prices and hedging positions take into account the volatility risk.

通过熵分割和芬谢尔二元性对或有索赔进行定价和对冲
在有限状态不完全市场中,我们提出了一种新方法,用于描述和选择或有索赔的等价马丁格尔定价措施。这是一种通过凸编程实现的熵分割方法,通过这种方法,我们将索赔无套利价格区间分为两半,即在连续熵水平上的买方价格和卖方价格。当熵水平接近 0 时,经典的买方和卖方价格就会出现。接下来,我们对这些基元程序应用芬切尔对偶性来描述套期保值头寸,在同一表达式中统一了超级(或次级)复制(当熵接近 0 时出现)和部分复制(当熵趋于最大值时)的情况。最后,我们将线性规划应用于对冲问题,以在对偶可行集的价格片段中找到具有最小 CVaR 的最优部分复制投资组合。我们将我们的方法应用于 Cliquet 式担保,使用 Heston 的动态方法,参数根据 EUROSTOXX50 指数的欧洲看涨期权报价进行校准。这样,价格和对冲头寸就考虑到了波动风险。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
58
审稿时长
6-12 weeks
期刊介绍: Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics. The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests: -Algorithms- Approximations- Asymptotic Approximations & Expansions- Combinatorial & Geometric Probability- Communication Networks- Extreme Value Theory- Finance- Image Analysis- Inequalities- Information Theory- Mathematical Physics- Molecular Biology- Monte Carlo Methods- Order Statistics- Queuing Theory- Reliability Theory- Stochastic Processes
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