The general problem of asset pricing when the discount rate differs from the rate at which an asset's cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets). As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised, and single-curve models extended. In another application, inflation-linked, currency-based, and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

I investigate a pricing kernel in which coskewness and the market volatility risk factors are endogenously determined. I show that the price of coskewness and market volatility risk are restricted by investor risk aversion and skewness preference. The risk aversion is estimated to be between two and five and significant. The price of volatility risk ranges from -1.5% to -0.15% per year. Consistent with theory, I find that the pricing kernel is decreasing in the aggregate wealth and increasing in the market volatility. When I project my estimated pricing kernel on a polynomial function of the market return, doing so produces the puzzling behaviors observed in pricing kernel. Using pricing kernels, I examine the sources of the idiosyncratic volatility premium. I find that nonzero risk aversion and firms' non-systematic coskewness determine the premium on idiosyncratic volatility risk. When I control for the non-systematic coskewness factor, I find no significant relation between idiosyncratic volatility and stock expected returns. My results are robust across different sample periods, different measures of market volatility and firm characteristics.

The determinants of yield curve dynamics have been thoroughly discussed in finance models. However, little can be said about the macroeconomic factors behind the movements of short- and long-term interest rates as well as the risk compensation demanded by financial investors. By taking on a macro-finance perspective, the book’s approach explicitly acknowledges the close feedback between monetary policy, the macroeconomy and financial conditions. Both theoretical and empirical models are applied in order to get a profound understanding of the interlinkages between economic activity, the conduct of monetary policy and the underlying macroeconomic factors of bond price movements. Moreover, the book identifies a broad risk-taking channel of monetary transmission which allows a reassessment of the role of financial constraints; it enables policy makers to develop new guidelines for monetary policy and for financial supervision of how to cope with evolving financial imbalances.

Edited by Rajnish Mehra, this volume focuses on the equity risk premium puzzle, a term coined by Mehra and Prescott in 1985 which encompasses a number of empirical regularities in the prices of capital assets that are at odds with the predictions of standard economic theory.

Investors seek to hedge against interest rate risk by taking long or short positions on bonds of different maturities. We study changes in risk taking behavior in a low interest rate environment by estimating a market stochastic discount factor that is non-linear and therefore consistent with the empirical properties of cashflow valuations identified in the literature. We provide evidence that non-linearities arise from hedging strategies of investors exposed to interest rate risk. Capital losses are amplified when interest rates increase and risk averse investors have taken positions on instruments with longer maturity, expecting instead interest rates to revert back to their historical average.

This book provides a unifying structure for the activities that fall under the process typically called "standard setting" on tests of proficiency. Standard setting refers to the methodology used to identify performance standards on tests of proficiency. The results from standard setting studies are critical for supporting the use of many types of tests. The process is frequently applied to educational, psychological, licensure/certification, and other types of tests and examination systems. The literature on procedures for standard setting is extensive, but the methodology for standard setting has evolved in a haphazard way over many decades without a unifying theory to support the evaluation of the methods and the validation of inferences made from the standards. This text provides a framework for going beyond specific standard setting methods to gain an understanding of the goals for the methods and how to evaluate whether the goals have been achieved. The unifying structure provided in this text considers policy that calls for the existence of performance standards, the relationship of proficiency test design to the policy, and tasks assigned to subject matter experts to help them convert the policy to estimates of locations on the reporting score scale for the test. Guidance is provided for how to connect the psychometric aspects of the standard setting process to the intentions of policy makers as expressed in policy statements. Further, the structure is used support validity arguments for inferences made when using standards. Examples are provided to show how the unifying structure can be used to evaluate and improve standard setting methodology.

Winner of the prestigious Paul A. Samuelson Award for scholarly writing on lifelong financial security, John Cochrane's Asset Pricing now appears in a revised edition that unifies and brings the science of asset pricing up to date for advanced students and professionals. Cochrane traces the pricing of all assets back to a single idea--price equals expected discounted payoff--that captures the macro-economic risks underlying each security's value. By using a single, stochastic discount factor rather than a separate set of tricks for each asset class, Cochrane builds a unified account of modern asset pricing. He presents applications to stocks, bonds, and options. Each model--consumption based, CAPM, multifactor, term structure, and option pricing--is derived as a different specification of the discounted factor. The discount factor framework also leads to a state-space geometry for mean-variance frontiers and asset pricing models. It puts payoffs in different states of nature on the axes rather than mean and variance of return, leading to a new and conveniently linear geometrical representation of asset pricing ideas. Cochrane approaches empirical work with the Generalized Method of Moments, which studies sample average prices and discounted payoffs to determine whether price does equal expected discounted payoff. He translates between the discount factor, GMM, and state-space language and the beta, mean-variance, and regression language common in empirical work and earlier theory. The book also includes a review of recent empirical work on return predictability, value and other puzzles in the cross section, and equity premium puzzles and their resolution. Written to be a summary for academics and professionals as well as a textbook, this book condenses and advances recent scholarship in financial economics.