An Option Pricing Model Using High Frequency Data
| Autor: | Yousung Park, Saebom Jeon, Won Chang |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
040101 forestry
050208 finance Computer science Autoregressive conditional heteroskedasticity Monte Carlo methods for option pricing 05 social sciences Bayesian probability European Call Option 04 agricultural and veterinary sciences Black–Scholes model Implied volatility Bayesian GARCH-M model MCMC algorithm Valuation of options Volatility 0502 economics and business Econometrics 0401 agriculture forestry and fisheries General Earth and Planetary Sciences Call option Finite difference methods for option pricing Volatility (finance) General Environmental Science |
| Zdroj: | Procedia Computer Science. 91:175-179 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2016.07.035 |
| Popis: | We propose a European call option evaluation framework accommodating GARCH-M model and its extension to handle irregularly spaced high-frequency data. The framework takes Bayesian approach to derive the predictive distribution for option prices and their volatilities. These predictive distributions vary as time approaches to the expiry data and provide credibility intervals to evaluate the option market. In empirical study, we illustrate the application using KOSPI200 and its options. Our approach results well-suited in the simulation based option pricing and explains a behavior of option prices close to the expiry. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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