Options
Option strategies based on semi-parametric implied volatility surface prediction
Journal
Journal of Investment Strategies
ISSN
1460-1559
Type
journal article
Date Issued
2011-12
Author(s)
Colangelo, Dominik
Abstract
We investigate whether a more sophisticated technique able to forecast accurately the future movements of the implied volatility surface may help in improving the performance of basic option strategies. To this goal we construct a set of strategies using predicted option returns for a forecasting period of ten trading days and form profitable hold-to-expiration, equally weighted, zero-cost portfolios with one month at-the-money options. The accurate predictions of the implied volatility surface dynamics are obtained using a statistical machine learning procedure based on regression trees. These forecasts assist in obtaining reliable option returns used as trading signals in our strategies. We test the performance of the proposed strategies on options on the S\&P100 and on its constituents between 2002 and 2006 getting positive annualized returns of up to more than 50\%. Comparing such performance to the ones obtained without using any complex model for the implied volatility surface we show that in most cases differences are small.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Incisive Media
Publisher place
London
Volume
1
Number
1
Start page
3
End page
41
Pages
39
Subject(s)
Division(s)
Eprints ID
207130