City Research Online

Abstract

The overall objective of the thesis is to understand volatility and to derive implications for options pricing with particular reference to the Nikkei 225 index, which has not been widely researched. Our brief survey shows us that the volatility models including the GARCH family can be applied for forecasting the volatility of the Nikkei 225 index daily returns. In addition, forecasting power of volatility is much stronger when using implied volatility rather than using historical volatility and the GARCH estimates. We observe the smile effect and term structure of implied volatility in the Nikkei 225 options market. From the perspective of the international linkage of the world major markets, both historical and implied volatilities spill over from one market to another. We can utilise those characteristics for two applications. One is that we can trade options by forecasting volatilities with volatility models. If our forecasts were higher than the implied volatility in the market, we would go short in some series of options with delta neutral hedging. If volatility has declined over the option period, we could capitalise the forecast with the option positions. Moreover, the information in the FTSE and S&P markets (historical and implied volatilities) is useful to forecast the Nikkei volatility, when we trade the Nikkei options. The other application is to evaluate option positions from the risk management point of view. Middle-office managers are concerned with profits and losses if the market and volatility move in a particular way. By using the information of smiles and term structures of implied volatilities, managers can evaluate their positions more accurately for risk management.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Bayes Business School Doctoral Theses Bayes Business School > Finance Doctoral Theses

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