Book Description

For currency options pricing, this study examines the performance of implied volatility model (IVM) and GARCH (1,1)-based volatility model (GVM) for daily data, and realized volatility model (RVM) for intra-day data. The IVM and GVM provide mixed results for in-sample tests. The out-of-sample results indicate that IVM tends to outperform GVM in forecasting options prices. The results also indicate that RVM outperforms IVM and GVM for pricing options with higher accuracy by capturing exchange rate return behaviour for both in-sample and out-of sample. This implies that intra-daily level volatility model RVM contains adequate information which cannot be accommodated by the standard daily level volatility model IVM and GVM for pricing options. Thus using RVM is a novel approach for pricing currency options, and may add a new dimension to the options valuation technique. The last segment of this research is an innovation in options literature. In this segment, a general optimization framework is proposed to forecast options prices by exploiting their price volatility history, rather than the volatility of the underlying currencies. Thus, in this framework, spot and options markets are treated as separate entities. The approach is flexible in that different objective functions for predicting the underlying volatility can be modified and adapted in the proposed framework. The forecast performance of this framework is compared with the forecast performance of the Multiplicative Error Model (MEM) of implied volatility and the GARCH (1,1). The results indicate that the proposed framework is capable of producing reasonably accurate forecasts for put and call prices.