NDLI: Support Vector Regression Model of Currency Options Pricing with Stochastic Volatility Models and Forward Exchange Rate

Content Provider	IEEE Xplore Digital Library
Author	Ping Wang YunCheng Huang YuanSu Wang
Copyright Year	2009
Abstract	Support Vector Regression (SVR) is a new general learning method, proposed in the statistical Learning Theory. In this paper, we construct a new nonparametric currency options pricing model with SVR approach. We integrate stochastic volatility models (SV) into SVR to upgrade the forecasting ability of the price of currency options. And we use the forward exchange rate as the input variable of SVR, as the forward exchange rate takes the interest rates of the pair of currencies into account. The inputs of SVR will include the moneyness (Spot rate/strike price), forward exchange rate, the volatility of the spot rate, domestic risk free simple interest rate, and the time to maturity. Analytical results reveals that new model provides greater predictability than traditional approaches such as GK model and artificial neural network option pricing model on the same data sets.
Starting Page	1007
Ending Page	1012
File Size	466498
Page Count	6
File Format	PDF
ISBN	9781424452095
DOI	10.1109/NCM.2009.328
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-25
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Exchange rates Economic indicators Forward contracts Input variables Statistical learning Stochastic processes Pricing Artificial neural networks Predictive models
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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