| Pricing a risk management contract based on a machine learning approach |
| کد مقاله : 1062-FEMATH5 (R2) |
| نویسندگان |
|
مصطفی پورعلی زاده *1، عبدالرحیم بادامچی زاده2، هیربد آسا3 1تهران، خیابان شهید بهشتی، دانشکده علوم ریاضی و رایانه 2عضو هیت علمی/ دانشگاه علامه طباطبائی 3عضو هیت علمی/دانشگاه لیورپول |
| چکیده مقاله |
| The main goal of this paper is to price a risk management problem based on the price of European call options. First of all, we provide a risk management problem which plays the role of an insurance contract to manage the risk of losses caused by market price fluctuation. Then, working towards controlling price movements, we introduce a machine learning algorithm with a quadratic hypothesis to model implied volatility and rule out static arbitrage on call option surface. We address how to preclude over-fitting (high variance) and under-fitting (high bias) by a regularized cost function including a penalty term which controls the trade-off between over-fitting and under-fitting. Eventually, the results of a numerical implementation show that the proposed modeling of implied volatility yield a volatility surface free of static arbitrage, therefore it can be used to monitor price variability and also to improve the precision of contract pricing. |
| کلیدواژه ها |
| Risk Management; Implied Volatility; Static Arbitrage; Machine Learning. |
| وضعیت: پذیرفته شده برای ارائه شفاهی |