Marijuana has been a frequent essential of discussions by the investors around globe. The main reason for the rise in the popularity of the Marijuana is, (i) first, the legalization of Marijuana in two states of US (Colorado and Washington on January 1, 2014) and (ii) secondly, the extent to...

In this paper we consider the question of how to improve the efficacy of strategies designed to capture factor premiums in equity markets and, in particular, from the value, quality, low risk and momentum factors. We consider a number of portfolio construction approaches designed to capture...

This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be utilised to predict returns on the price of gold.We first demonstrate that analysts are at least in part basing their earnings forecasts for gold firms on the return...

This paper explores stock return predictability by exploiting the cross-section of oil futures prices. Motivated by the principal component analysis, we find the curvature factor of the oil futures curve predicts monthly stock returns: a 1% per month increase in the curvature factor predicts...

We propose a novel method to estimate risk-neutral quantiles that uses sorting to minimize an objective function given by a convex combination of call and put option prices over the range of available strike prices. We demonstrate that this new method significantly improves the accuracy of...

This paper studies the intertemporal relation between U.S. volatility risk and international equity risk premia. We show that a common volatility risk factor constructed from the option-implied U.S. forward variances positively and significantly predicts future stock market returns of the...

We present a novel methodology to calculate the jump-induced tail risk premium for individual stocks and examine its effect on the following-month’s returns. The existence of a premium for bearing negative jump-induced tail risk is significantly associated with negative one-month future...

This paper investigates the performance of a factor-augmented regression (FAR) model with a mixture of stationary and nonstationary factors in stock return prediction. For comparison purpose, we also consider a traditional FAR model with only stationary factors. In an application with a dataset...

Economic theory identifies two potential sources of return predictability: time variation in expected returns (beta-predictability) or market inefficiencies (alpha-predictability). For the latter, Samuelson argued that macro-returns exhibit more inefficiencies than micro-returns, as individual...

Using the long-term wavelet component of monthly S&P 500 excess returns as supervision information, we employ a machine learning method to extract the common predictive information of 14 prevalent macroeconomic variables, and construct a new macroeconomic index aligned for predicting stock...