Equity basket correlation is an important risk factor. It characterizes the strength of linear dependence between assets and thus measures the degree of portfolio diversification. It can be estimated both under the physical measure from return series, and under 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 over the recent 2 years and propose several hedging schemes based on implied correlation (IC) forecasts. Modeling IC is a challenging task both in terms of computational burden and estimation error. First the number of correlation coefficients to be estimated would grow with the size of the basket. Second, since the IC is implied from option prices it is not constant over maturities and strikes. Finally, the IC changes over time. The dimensionality of the problem is reduced by an assumption that the correlation between all pairs of equities is constant (equicorrelation). The IC surface (ICS) is then approximated from implied volatilities of stocks and implied volatility of the basket. To analyze this structure and the dynamics of the ICS we employ a dynamic semiparametric factor model (DSFM).JEL classification codes: C14, C32, G12, G13, G15, G17
Traditionally volatility is viewed as a measure of variability, or risk, of an underlying asset. However recently investors began to look at volatility from a different angle. It happened due to emergence of a market for new derivative instruments -variance swaps. In this paper first we introduse the general idea of the volatility trading using variance swaps. Then we describe valuation and hedging methodology for vanilla variance swaps as well as for the 3-rd generation volatility derivatives: gamma swaps, corridor variance swaps, conditional variance swaps. Finally we show the results of the performance investigation of one of the most popular volatility strategies -dispersion trading. The strategy was implemented using variance swaps on DAX and its constituents during the 5-years period from 2004 to 2008.
Traditionally volatility is viewed as a measure of variability, or risk, of an underlying asset. However recently investors began to look at volatility from a different angle. It happened due to emergence of a market for new derivative instruments -variance swaps. In this paper first we introduse the general idea of the volatility trading using variance swaps. Then we describe valuation and hedging methodology for vanilla variance swaps as well as for the 3-rd generation volatility derivatives: gamma swaps, corridor variance swaps, conditional variance swaps. Finally we show the results of the performance investigation of one of the most popular volatility strategies -dispersion trading. The strategy was implemented using variance swaps on DAX and its constituents during the 5-years period from 2004 to 2008.
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