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.

A comprehensive reference for financial economics, balancing theoretical explanations, empirical evidence, and the practical relevance of knowledge in the field. This volume offers a comprehensive, integrated treatment of financial economics, tracking the major milestones in the field and providing methodological tools. Doing so, it balances theoretical explanations, empirical evidence, and practical relevance. It illustrates nearly a century of theoretical advances with a vast array of models, showing how real phenomena (and, at times, market practice) have helped economists reformulate existing theories. Throughout, the book offers examples and solved problems that help readers understand the main lessons conveyed by the models analyzed. The book provides a unique and authoritative reference for the field of financial economics. Part I offers the foundations of the field, introducing asset evaluation, information problems in asset markets and corporate finance, and methods of statistical inference. Part II explains the main empirical facts and the challenges these pose for financial economists, which include excess price volatility, market liquidity, market dysfunctionalities, and the countercyclical behavior of market volatility. Part III covers the main instruments that protect institutions against the volatilities and uncertainties of capital markets described in part II. Doing so, it relies on models that have become the market standard, and incorporates practices that emerged from the 2007–2008 financial crisis.

This paper considers the impact and implications of quot;largequot; changes in asset prices on the intra-market correlations in the domestic and international markets. Assuming that asset returns are normally-distributed, we show that the absolute magnitude of the correlation, conditional on a change greater than or equal to a given absolute size in one of the variables, is monotonically increasing in the magnitude of that absolute change. We present empirical tests using domestic and international-market data that support this theoretical result. These results have significant implications for hedging interest rate risk, tests of asset pricing models, Roll's R 2 concern with the explanatory power of financial asset pricing models, and the implementation of the value-at-risk concept.

This book rehabilitates beta as a definition of systemic risk by using particle physics to evaluate discrete components of financial risk. Much of the frustration with beta stems from the failure to disaggregate its discrete components; conventional beta is often treated as if it were "atomic" in the original Greek sense: uncut and indivisible. By analogy to the Standard Model of particle physics theory's three generations of matter and the three-way interaction of quarks, Chen divides beta as the fundamental unit of systemic financial risk into three matching pairs of "baryonic" components. The resulting econophysics of beta explains no fewer than three of the most significant anomalies and puzzles in mathematical finance. Moreover, the model's three-way analysis of systemic risk connects the mechanics of mathematical finance with phenomena usually attributed to behavioral influences on capital markets. Adding consideration of volatility and correlation, and of the distinct cash flow and discount rate components of systematic risk, harmonizes mathematical finance with labor markets, human capital, and macroeconomics.

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.