We show that the net corporate payout yield predicts both the stock market index and house prices and that the log home rent-price ratio predicts both house prices and labor income growth. We incorporate the predictability in a rich life-cycle model of household decisions involving consumption...

In a calibrated consumption-portfolio model with stock, housing, and labor income predictability, we disentangle the welfare effects of skill and luck. Skilled investors are able to take advantage of all sources of predictability, whereas unskilled investors ignore predictability. Lucky...

Discrimination is a pervasive aspect of modern society and human relations. Statistical discrimination theory suggests that profit-maximizing employers should use all the information about job candidates, including information about group membership (e.g., race or gender), to make accurate...

Companies are increasingly adopting Artificial Intelligence (AI) today. Recently however debates started over the risk of human cognitive biases being replicated (and scaled) by AI. Research on biases in AI predicting consumer choice is incipient and focuses on observable biases. We provide a...

We develop a novel characterization of participants’ forecasts with a mixture of normal variables arising from a Markov component. Using this characterization, we formulate five behavioral specifications, including four implied by the diagnostic expectations approach, as well as three implied...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

We comprehensively analyze the predictive power of several option implied variables for monthly S & P 500 excess returns and realized variance. The correlation risk premium (CRP) emerges as a strong predictor of both excess returns and realized variance. This is true both in- and out-of-sample....

This paper studies a basket of risk statistics that are widely used to measure investment performance. Those risk statistics were used to rank the performance of the assets. The dependent information was removed from the set of risk measures that were used in the test. The risk statistics were...

Stochastic optimisation has found a fertile ground for applications in finance. One of the greatest challenges remains to incorporate a set of scenarios that accurately models the behaviour of financial markets, and in particular their behaviour during crashes and crises, without sacrificing the...

Modelling and forecasting of asset volatility and covariance is of prime importance in the construction of portfolios. In this paper, we present a generalised multi-factor model that incorporates heteroskedasticity and dependence in the idiosyncratic error terms. We apply this model to...