Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

We constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and the difference...

We provide a fresh look at the performance of the stock prices of firms that launched an IPO between 2009 and 2019 and assess the role of their size, age and sector in affecting future performance. We utilize data about 1611 IPOs spanning 11 economic sectors using the event study method. We...

This paper investigates the performance and characteristics of survivor stocks in the S&P 500 index. Using both in-sample and out-of-sample comparisons, survivor stocks outperformed this market index by a considerable margin. Relative to other S&P 500 index companies, survivor stocks tend to be...

Through globalization and financial market liberalization, the opening up of markets has increased cross-border investments as investors search for higher risk-adjusted returns. This ability to invest internationally has raised the attention given to emerging markets that offer higher...

Using monthly data from January 2000 to August 2018, this paper examines how the Canadian oil and gas industry and individual firms’ equity prices react to oil price fluctuations, which are measured by the traditional West Texas Intermediate (WTI) benchmark and the Canada-specific Western...

We investigate the risk-return trade-off on the US and European stock markets. We investigate the non-linear risk-return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk-return...

This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are studied separately. We start from the historical trend in...

The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes over time, and this variation is largely driven...

This paper examines the impact of changes in economic policy uncertainty (EPU) and COVID-19 shock on stock returns. Tests of 16 global stock market indices, using monthly data from January 1990 to August 2021, suggest a negative relation between the stock return and a country’s EPU. Evidence...