Properties Of The Pricing Kernel And Implications

Based on a family of discrepancy functions, we derive nonparametric stochastic discount factor (SDFs) bounds that naturally generalize variance (Hansen and Jagannathan, 1991), entropy (Backus, Chernov and Martin, 2011), and higher-moment (Snow, 1991) bounds. These bounds are especially useful to identify how parameters affect pricing kernel dispersion in asset pricing models. In particular, they allow us to distinguish between models where dispersion comes mainly from skewness from models where kurtosis is the primary source of dispersion. We analyze the admissibility of disaster, disappointment aversion and long-run risk models with respect to these bounds.

We derive a lower bound for the size of the permanent component of asset pricing kernels. The bound is based on return properties of long-term zero-coupon bonds, risk-free bonds, and other risky securities. We find the permanent component of the pricing kernel to be very large; its volatility is about 100% of the volatility of the stochastic discount factor. This result implies that, if the pricing kernel is a function of consumption, innovations to consumption need to have permanent effects.

We evaluate the asset pricing implications of a class of models in which risk sharing is imperfect because of limited enforcement of intertemporal contracts. Lustig (2004) has shown that in such a model the asset pricing kernel can be written as a simple function of the aggregate consumption growth rate and the growth rate of consumption of the set of households that do not face binding enforcement constraints. These unconstrained households have lower consumption growth rates than all other households in the economy. We use household data on consumption growth from the U.S. Consumer Expenditure Survey to identify unconstrained households, to estimate the pricing kernel implied by these models and evaluate their performance in pricing aggregate risk. We find that for high values of the relative risk aversion coefficient, the limited enforcement pricing kernel generates a market price of risk that is substantially closer to the data than the one obtained using the standard complete markets asset pricing kernel.

We incorporate costly external finance in an investment-based asset pricing model and investigate whether financing frictions are quantitatively important for pricing a cross-section of expected returns. We show that common assumptions about the nature of the financing frictions are captured by a simple financing cost' function, equal to the product of the financing premium and the amount of external finance. This approach provides a tractable framework for empirical analysis. Using GMM, we estimate a pricing kernel that incorporates the effects of financing constraints on investment behavior. The key ingredients in this pricing kernel depend not only on fundamentals', such as profits and investment, but also on the financing variables, such as default premium and the amount of external financing. Our findings, however, suggest that the role played by financing frictions is fairly negligible, unless the premium on external funds is procyclical, a property not evident in the data and not satisfied by most models of costly external finance.

In the mid-eighties Mehra and Prescott showed that the risk premium earned by American stocks cannot reasonably be explained by conventional capital market models. Using time additive utility, the observed risk pre mium can only be explained by unrealistically high risk aversion parameters. This phenomenon is well known as the equity premium puzzle. Shortly aft erwards it was also observed that the risk-free rate is too low relative to the observed risk premium. This essay is the first one to analyze these puzzles in the German capital market. It starts with a thorough discussion of the available theoretical mod els and then goes on to perform various empirical studies on the German capital market. After discussing natural properties of the pricing kernel by which future cash flows are translated into securities prices, various multi period equilibrium models are investigated for their implied pricing kernels. The starting point is a representative investor who optimizes his invest ment and consumption policy over time. One important implication of time additive utility is the identity of relative risk aversion and the inverse in tertemporal elasticity of substitution. Since this identity is at odds with reality, the essay goes on to discuss recursive preferences which violate the expected utility principle but allow to separate relative risk aversion and intertemporal elasticity of substitution.

We take a similar form of pricing kernel which developed by Christoffersen et al (2013) to extend the multiple volatility components model. By that way, we can obtain a more elaborate model which also explains some puzzles in the market. Apart from that, a surprise result is we don't need to estimate full parameters in model. Instead of that, we estimate the scaling factor which plays an important role when changing of measure. Empirical tests demonstrate the well ability of generalized model when reconcile time series properties of stock returns with the option prices. Furthermore, we also use the in-sample and out-sample for testing the predictability of the generalized model. The result shows the pricing kernel more or less enhancing the predictability than before..

The book presents models for the pricing of financial assets such as stocks, bonds, and options. The models are formulated and analyzed using concepts and techniques from mathematics and probability theory. It presents important classic models and some recent 'state-of-the-art' models that outperform the classics.

The pricing kernel, or the state-price density, which relates future cash flows to today's price, is the fundamental building block of modern asset pricing theory. In abstract, the state-price density process can be regarded as a positive supermartingale, or, under some regularity conditions, a potential. The theory of Markov processes provides a rich framework for the generation of examples of potentials. In this paper, we begin the modeling of bond and currency prices from the modeling of the state-price density satisfying basic properties of a potential. We provide extensive examples on the potential modeling of the state-price densities and their implications on bond and currency pricing. We show that most classic interest rate models are special cases of this general approach. We also investigate the connection between the potential approach and the Heath, Jarrow, and Morton approach widely used in the finance area. One advantage of the potential approach resides in its great ease in modeling the yield curves of many countries at the same time, together with the exchange rates between them. We derive the properties of exchange rates under each example and illustrate their possibility in explaining the forward premium puzzle.

The sixteen essays in this collection are organized around five themes. The first group is concerned with the pricing implications of recent developments in the theory of the firm. The subject of the second group is wage-price guidelines, in theory and practice. The third set deals with pricing in regulated industries, with special attention to marginal cost pricing. Marketing models and empirical studies of pricing behavior are considered in the fourth set of essays. And the final group, closely related to this, deals with the rationality properties of business pricing decisions and the implications of pricing practices for antitrust enforcement. If a common view on pricing emerges from these provocative and timely papers; it is that an eclectic approach to pricing theories, policies, and practices appears at this stage to be appropriate, since neither neoclassical theory nor recent amendments, extensions, or alternatives to it appear individually rich enough to embrace the full range of variety that pricing behavior affords.