We investigate the movements of the yield curve after the release of major U.S. macroeconomic announcements through the lenses of an arbitrage-free dynamic term structure model with macroeconomic fundamentals. Combining estimated yield responses obtained using high-frequency data with model...

We investigate the movements of the yield curve after the release of major U.S. macroeconomic announcements through the lenses of an arbitrage-free dynamic term structure model with macroeconomic fundamentals. Combining estimated yield responses obtained using high-frequency data with model...

Using survey forecasts, we find that systematic errors in expectations of long-term inflation and short-term nominal earnings growth are the main driver of prices and return puzzles for bonds and stocks. We demonstrate this by deriving and testing a single necessary and sufficient condition...

We propose a novel reinforcement learning approach to extract high-frequency aggregate growth expectations from asset prices. While much expectations-based research in macroeconomics and finance relies on low-frequency surveys, the multitude of events that pass between survey dates renders...

We study a simple static economy with collateralized loan contracts and an incomplete asset market. We study whether economic forces operate to keep asset price equal to fundamentals in this economy. We find that asset prices may be higher than the valuation of any agent in the economy, i.e.,...

We propose an extension of the class of rational expectations bubbles (REBs) to the more general rational beliefs setting of Kurz (1994a,b). In a potentially non-stationary but stationarizable environment, among an heterogenous population of agents, it is possible to hold more than one...

The paper studies the emergence of contrarian behavior in information networks in an asset pricing market. Financial traders coordinate on similar behavior, but have heterogeneous price expectations and are influenced by friends. According to a popular belief, they are prone to herding. However,...

I set up a model in which two types of ambiguity-averse traders disagree on how to interpret a public signal. When traders first observe contradicting interpretations of the signal, they don't know whether to attribute the clash of opinions to different information processing or to information...

We estimate a dynamic asset pricing model characterized by heterogeneous boundedly rational agents. The fundamental value of the risky asset is publicly available to all agents, but they have different beliefs about the persistence of deviations of stock prices from the fundamental benchmark. An...

We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...