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Statistics & Risk Modeling

with Applications in Finance and Insurance

Editor-in-Chief: Stelzer, Robert

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Implied basket correlation dynamics

Wolfgang Karl Härdle
  • Ladislaus von Bortkiewicz Chair of Statistics, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; and Sim Kee Boon Institute for Financial Economics, Singapore Management University, Administration Building, 81 Victoria Street, 188065, Singapore
  • Email:
/ Elena Silyakova
  • Corresponding author
  • Ladislaus von Bortkiewicz Chair of Statistics, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
  • Email:
Published Online: 2016-07-28 | DOI: https://doi.org/10.1515/strm-2014-1176


Equity basket correlation can be estimated both using the physical measure from stock prices, and also using the risk neutral measure from option prices. The difference between the two estimates motivates a so-called “dispersion strategy”. We study the performance of this strategy on the German market and propose several profitability improvement schemes based on implied correlation (IC) forecasts. Modelling IC conceals several challenges. Firstly the number of correlation coefficients would grow with the size of the basket. Secondly, IC is not constant over maturities and strikes. Finally, IC changes over time. We reduce the dimensionality of the problem by assuming equicorrelation. The IC surface (ICS) is then approximated from the implied volatilities of stocks and the implied volatility of the basket. To analyze the dynamics of the ICS we employ a dynamic semiparametric factor model.

Keywords: Correlation risk; dimension reduction; dispersion strategy; dynamic factor models

MSC 2010: 62H25; 62H15; 62H20


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About the article

Received: 2014-12-25

Revised: 2016-06-14

Accepted: 2016-06-30

Published Online: 2016-07-28

Published in Print: 2016-06-01

Funding Source: Deutsche Forschungsgemeinschaft

Award identifier / Grant number: CRC 649 “Economic Risk”

The authors gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft through CRC 649 “Economic Risk”.

Citation Information: Statistics & Risk Modeling, ISSN (Online) 2196-7040, ISSN (Print) 2193-1402, DOI: https://doi.org/10.1515/strm-2014-1176. Export Citation

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