When a new asset keeps changing its narrative, investors find difficulty in classifying and understanding the new asset. Rational investors therefore face unprecedented uncertainty and learn about the joint dynamics to optimize their portfolio accordingly. Bitcoin's "digital gold" narrative, as...

We examine the effect of learning of uninformed traders in a dynamic limit order market with asymmetric and short-lived information. We show that the learning is effective and valuable with respect to information acquisition, forecasting and buy-sell decision accuracies, and profit opportunity...

Recent survey evidence suggests that investors form beliefs about future stock returns by predominantly extrapolating their own experience: They overweight returns they have personally experienced while underweighting returns from earlier years and consequently expect high (low) stock market...

We study the dynamics of a Lucas-tree model with finitely lived agents who "learn from experience." Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic boom-and-bust fluctuations around the...

We study the dynamics of a Lucas-tree model with finitely lived agents who 'learn from experience.' Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic boom-and-bust fluctuations around the...

We study the dynamics of a Lucas-tree model with finitely lived agents who "learn from experience." Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic boom-and-bust fluctuations around the...

This paper considers the impact of heterogeneous gain learning in an asset pricing model. A relatively stylized model is shown to generate persistent swings of asset prices from their fundamental values which replicates long range samples of U.S financial data. The detailed mechanisms of the...

This paper presents a new agent-based financial market. It is designed to be both simple enough to gain insights into the nature and structure of what is going on at both the agent and macro levels, but remain rich enough to allow for many interesting evolutionary experiments. The model is...

We study the dynamics of a Lucas-tree model with finitely lived individuals who "learn from experience." Individuals update expectations by Bayesian learning based on observations from their own lifetimes. In this model, the stock price exhibits stochastic fluctuations around the rational...