This paper analyses the links between advances in financial technology, investors' sophistication, and their financial portfolios' composition and returns. We develop a simple portfolio choice model under asymmetric information and derive some theoretical predictions. Using detailed micro data...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

Robinhood (RH) investors increased their holdings in the March 2020 COVID bear market, indicating an absence of collective panic and margin calls. This steadfastness was rewarded in the subsequent bull market. Despite unusual interests in some “experience” stocks (e.g., cannabis stocks),...

I propose and test a unifying hypothesis to explain both cross-sectional return anomalies and subjective return expectation errors: some investors ignore discount rate dynamics when forming return expectations. Consistent with the hypothesis: (1) stocks' expected cash flow growth and...

We consider a sovereign wealth fund that invests broadly in the international financial markets. The influx to the fund has stopped. We adopt the life cycle model and demonstrate that the optimal spending rate from the fund is significantly less than the fund's expected real rate of return. The...

The present paper analyses an optimal consumption and investment problem of a retiree with a constant relative risk aversion (CRRA) who faces parameter uncertainty about the financial market.We solve the optimization problem under partial information by making the market observationally complete...

This paper analyses the links between advances in financial technology, investors’ sophistication, and the composition and returns of their financial portfolios. We develop a simple portfolio choice model under asymmetric information and derive some theoretical predictions. Using detailed...

Model risk has a huge impact on any risk measurement procedure and its quantification is therefore a crucial step. In this paper, we introduce three quantitative measures of model risk when choosing a particular reference model within a given class: the absolute measure of model risk, the...