We study the set of marginal utility-based prices of a financial derivative in the case where the investor has a non-replicable random endowment. We provide an example showing that even in the simplest of settings - such as Samuelson's geometric Brownian motion model - the interval of marginal...

We introduce an evolutionary equilibrium asset pricing model with heterogeneous agents who can either act as brokers or hedge funds. Hedge funds can trade on margin, taking short or (leveraged) long positions in the assets. Brokers provide asset loans and credit to margin traders. In any...

The paper rst shows that nancial market equilibria need not to exist if agents possesscumulative prospect theory preferences with piecewise-power value functions. This is due tothe boundary behavior of the cumulative prospect theory value function, which might causean innite short-selling...

I study the effects of short sale constraints in a rational framework with asymmetric information. I consider the cases of Bernoulli-distributed (à la Glosten and Milgrom) and continuously distributed (à la Kyle) liquidation values, and focus on the latter case.In this case my model is able to...

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading...

Empirical studies investigate various causes and effects of sustainable investments. While some attempts have been made to describe the results found by theoretical models, these are relatively complex and idiosyncratic. We relate to existing studies and use a parsimonious CAPM in which we model...

We use transaction data gathered by a large fintech firm to study retail investors’ investments in cryptocurrencies. Crypto investors tend to be young, male, high-income, and live in wealthy urban areas with high levels of self-employment and low levels of altruism. Crypto investments are...

We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

We construct a momentum factor that identifies cross-sectional winners and losers based on a weighting scheme that incorporates all the price data, over the entire lookback period, as opposed to only the first and last price points of the window. The weighting scheme is derived from the...

The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called...