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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7287| Title: | A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks |
| Issue Date: | 9-Oct-2013 |
| Description: | We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-1471 http://hdl.handle.net/1721.1/7287 |
| Appears in Collections: | MIT Items |
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