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Estimating Volatility for Option Valuation: In the Swedish Option Market
Stockholm University, Faculty of Social Sciences, School of Business.
2005 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The pioneering and award-winning formula for option pricing, introduced by Robert C Merton, Myron S Scholes and Fischer Black in 1973 demands five accurate inputs. The inputs are a risk free rate, a price of the underlying asset, a strike price, time to maturity and the volatility in the underlying asset. The volatility variable is by far the most difficult one to estimate. Scholars have introduced different statistical methods to model the behaviour of volatility. The theoretical background contains many contradictions. The objective of this thesis was to investigate the markets- and two selected models ability to estimate volatility in the Swedish market, for option valuation purposes, during a period with a large flow of new information. The selected models were GARCH (1.1) and ARIMA (p,d,q). An appropriate methodology for this objective was a quantitative approach based on statistical concepts. The data selected for the study was all the shares at Stockholm Stock Exchange with traded call options maturing in May. The empirical result showed that the market produced inaccurate estimates of volatility that were biased downwards. Forecasting with ARIMA gave a similar result in accuracy but these estimates had a positive bias that was larger in absolute terms. The GARCH model produced estimates that were slightly better than both the market and ARIMA. These estimates were biased upwards in smaller numbers than the ARIMA and comparable with the market, in absolute terms. In a theoretical view it would be possible to develop a trading strategy based on the more accurate estimates produced by the GARCH model and create profits larger than the Theta loss. However, the result must be generalized with caution because of the limited number of companies in the study, the distribution of errors for estimates and finally because the study was performed during a period with unusually large flow of new information.

Place, publisher, year, edition, pages
National Category
Business Administration
URN: urn:nbn:se:su:diva-5527OAI: diva2:195389
Available from: 2007-01-05 Created: 2007-01-05

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