This is a survey of the basic theoretical foundations of intertemporal asset pricing theory. The broader theory is first reviewed in a simple discrete-time setting, emphasizing the key role of state prices. The existence of state prices is equivalent to the absence of arbitrage. State prices,...

We study the consumption based asset pricing model in a discrete time pure exchange setting with incomplete information. Incomplete information leads to a filtering problem which agents solve using the Kalman filter. We characterize the solution to the asset pricing problem in such a setting....

We explore the effects of fat tails on the equilibrium implications of the long run risks model of asset pricing by introducing innovations with dampened power law to consumption and dividends growth processes. We estimate the structural parameters of the proposed model by maximum likelihood. We...

We introduce a new class of flexible and tractable matrix affine jump-diffusions (AJD) to model multivariate sources of financial risk. We first provide a complete transform analysis of this model class, which opens a range of new potential applications to, e.g., multivariate option pricing with...

Revisiting the two-factor valuation of financial futures contracts and their derivatives, we propose a new approach in which the covariance process between the underlying asset price and the money market interest rate is set endogenously according to investors' arbitrage operations. The...

The uncertainty around future changes to the Federal Reserve target rate varies over time. In our results, the main driver of uncertainty is a "path" factor signaling information about future policy actions, which is filtered from federal funds futures data. The uncertainty is highest when it...

In this paper, motivated by existing and growing evidence on multiple macroeconomic volatilities, we extend the long-run risks model of Bansal and Yaron (2004) by allowing both a long- and a short-run volatility components in the evolution of economic fundamentals. With this extension, the new...

We study a consumption-based asset pricing model with incomplete information and a- stable shocks. Incomplete information leads to a non-Gaussian filtering problem. Bayesian updating generates fluctuating confidence in the agents' estimate of the persistent component of the dividends' growth...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...

In an exchange economy with recursive preferences (Epstein and Zin, 1989), we propose a novel nonparametric generalized method of moment (GMM) series approach to estimate unknown policy functions which are recursively specified in a system of nonlinear conditional expectation models...