The fall in US macroeconomic volatility from the mid-1980s coincided with a strong rise in asset prices. Recently, this rise, and the crash that followed, have been attributed to overconfidence in a benign macroeconomic environment of low volatility. This paper introduces learning about the...

Survey respondents strongly disagree about return risks and, increasingly, macroeconomic uncertainty. This may have contributed to higher asset prices through increased use of collateralisation, which allows risk-neutral investors to realise perceived gains from trade. Investors with lower risk...

New evidence suggests that individuals "learn from experience," meaning they learn from events occurring during their own lifetimes as opposed to the entire history of events. Moreover, they weigh more heavily the more recent events compared to events occurring in the more distant past. This...

I estimate a search-and-bargaining model of a decentralized market to quantify the effects of trading frictions on asset allocations, asset prices and welfare, and to quantify the effects of intermediaries that facilitate trade. Using business-aircraft data, I find that, relative to the...

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy....

This Paper shows that many of the empirical biases of the Black and Scholes option pricing model can be explained by Bayesian learning effects. In the context of an equilibrium model where dividend news evolves on a binomial lattice with unknown but recursively updated probabilities, we derive...

We present a decision theoretic framework with agents that are learning about the behavior of market determined variables. Agents are 'internally rational', i.e., maximize discounted expected utility under uncertainty given consistent beliefs about the future, but may not be 'externally...

We develop a multi-period model of strategic trading in an asset market where traders are uncertain about market liquidity. In our model, informed traders strategically trade against competitive market makers to exploit their short-lived private information. Unlike market makers, informed...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...