Motivated by extensive evidence that stock-return correlations are stochastic, we analyze whether the risk of correlation changes (affecting diversification benefits) is priced. We propose a direct and intuitive test by comparing option-implied correlations between stock returns (obtained by combining index option prices with prices of options on all index components) with realized correlations. Our parsimonious model shows that the substantial gap between average implied (39.5% for S&P500 and 46.0% for DJ30) and realized correlations (32.5% and 35.5%, respectively) is direct evidence of a large negative correlation risk premium. Empirical implementation of our model also indicates that the index variance risk premium can be attributed to the high price of correlation risk. Finally, we provide evidence that option-implied correlations have remarkable predictive power for future market returns, which also stays significant after controlling for a number of fundamental market return predictors.

We study whether exposure to market-wide correlation shocks affects expected option returns, using data on Samp;P100 index options, options on all components, and stock returns. We present evidence of priced correlation risk based on prices of index and individual variance risk. A trading strategy exploiting priced correlation risk generates a high alpha and is attractive for CRRA investors without frictions. Correlation risk exposure explains the cross-section of index and individual option returns well. The correlation risk premium cannot be exploited with realistic trading frictions, providing a limits to arbitrage interpretation of our yacute;ndings of a high price of correlation risk.

A thorough guide to correlation risk and its growing importance in global financial markets Ideal for anyone studying for CFA, PRMIA, CAIA, or other certifications, Correlation Risk Modeling and Management is the first rigorous guide to the topic of correlation risk. A relatively overlooked type of risk until it caused major unexpected losses during the financial crisis of 2007 through 2009, correlation risk has become a major focus of the risk management departments in major financial institutions, particularly since Basel III specifically addressed correlation risk with new regulations. This offers a rigorous explanation of the topic, revealing new and updated approaches to modelling and risk managing correlation risk. Offers comprehensive coverage of a topic of increasing importance in the financial world Includes the Basel III correlation framework Features interactive models in Excel/VBA, an accompanying website with further materials, and problems and questions at the end of each chapter

Standard asset pricing theories treat return volatility and correlations as two intimately related quantities, which hinders achieving a neat definition of a correlation premium. We introduce a model with a continuum of securities that have returns driven by a string. This model leads to new arbitrage pricing restrictions, according to which, holding any asset requires compensation for the granular exposure of this asset returns to changes in all other asset returns: an average correlation premium. We find that this correlation premium is both statistically and economically significant, and considerably fluctuates, driven by time-varying correlations and global market developments. The model explains the cross-section of expected returns and their counter-cyclicality without making reference to common factors affecting asset returns. It also explains the time-series behavior of the premium for the risk of changes in asset correlations (the correlation-risk premium), including its inverse relation with realized correlations.

Investors hold portfolios of assets with different risk-reward profiles for diversification benefits. Conditional on the volatility of assets, diversification benefits can vary over time depending on the correlation structure among asset returns. The correlation of returns between assets has varied substantially over time. To insure against future quot;low diversificationquot; states, investors might demand securities that offer higher payouts in these states. If this is the case, then investors would pay a premium for securities that perform well in regimes in which the correlation is high. We empirically test this hypothesis and find that correlation carries a significantly negative price of risk, after controlling for asset volatility and other risk factors.

This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk is priced in the cross-section because shocks to average stock volatility and correlation are priced. Both long and short run volatility and correlation factors have explanatory power for returns. Finally, I resolve the idiosyncratic volatility puzzle by showing that short-term idiosyncratic risk is positively priced whereas long-term idiosyncratic volatility carries a negative price.