Extreme Dependencies and the Idiosyncratic Volatility Puzzle

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In the context of the previous project, we could show (i) that stocks that exhibit strong extreme dependence with the market (i.e. crash-sensitive stocks) deliver a pronounced positive return premium, (ii) that similar effects can be observed for liquidity, and (iii) that the return patterns also hold internationally. Based on the developed methodology to measure systeamtic risk based on copulas---that allows for a flexible modelling of non-linear dependencies---the projects from this continution grant will focus on idiosyncratic volatility. As the total return volatility of a stock is comprised of its systematic and its idiosyncratic component, this is a natural continution and extension, respectively, of the initial project. If the measurement and extent of systematic risk changes, the amount of idiosyncratic volatility for a given level of total volatility necessarily also has to change. In the context of the new project, the following two specific subprojects will be analyzed: (1) Copula-based idiosyncratic volatility and the idiosyncratic volatility puzzle (IVP): We want to analyze whether idiosyncratic volatility measured in the traditional way (i.e. as risk not explained by linear exposures to risk factors) is different from idiosyncratic volatility for the case of a more precise copula-based measurement of systematic (and eventually idiosyncratic) volatility. Furthermore, we then want to analyze whether the theoretically unexpected negative relationship between stock returns and idiosyncratic volatility (the IVP) is due to the incorrect measurement of idiosyncratic volatility in previous work and whether it is reduced once we use our newly suggested copula-based measure of idiosyncratic volatility. (2) Daily stock rankings and the IVP: Many newspapers and websites regularly publish rankings of the stocks with the highest and lowest daily returns and are thus very visible for readers. We expect that the attention of potential investors is driven towards these stocks. In the second sub-project we thus want to analyze whether stocks that appear in daily return rankings (irrespective of whether they appear in top- or bottom-rankings) are overvalued in the short-term due to the attention they raise and subsequently exhibit negative abnormal returns as compared to stocks that do not appear in the daily rankings. Furthermore, we want to analyze whether such a potential pattern could also contribute in sovling the IVP. This is not unlikely as stocks that appear in the daily rankings probably also exhibit higher idiosyncrativ volatility. The suggested analyses of the IVP can be conducted with traditional or our newly developed, copula-based measures for idiosyncratic volatility and the analysis suggested here is thus also closely linked to the first subproject.