During the global financial crisis, stressed market conditions led to skyrocketing corporate bond spreads that could not be explained by conventional modeling approaches. This paper builds on this observation and sheds light on time-variations in the relationship between systematic risk factors...

During the global financial crisis, stressed market conditions led to skyrocketing corporate bond spreads that could not be explained by conventional modeling approaches. This paper builds on this observation and sheds light on time-variations in the relationship between systematic risk factors...

This study examines the performance of fifty global exchanged-traded funds (ETFs) traded on US stock exchanges. Specifically, it refers to the period following the end of quantitative easing, which took place in 2014. Therefore, the data, on which the study is based, refer to the period from...

Although portfolio management didn’t change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a...

This study examines the performance of fifty global exchanged-traded funds (ETFs) traded on US stock exchanges. Specififcally, it refers to the period following the end of quantitative easing, which took place in 2014. Therefore, the data, on which the study is based, refer to the period from...

Buying profitable, undervalued stocks and shorting unprofitable, overvalued stocks yields significant return differentials in North America, Europe, Japan, and Asia. Using data from 1991-2016, we test Greenblatt's (2006) “Magic Formula” (MF) and find that a modified MF which uses gross...

This paper provides global evidence supporting the hypothesis that expected return models are enhanced by the inclusion of variables that describe the evolution of book-to-market-changes in book value, changes in price, and net share issues. This conclusion is supported using data representing...

We use pre-World War I Brussels Stock Exchange (BSE) data to investigate the relation between average stock returns and market beta, size, momentum, dividend yield and total risk on the cross-section of stock returns. Based on portfolio sorts and Fama–MacBeth regressions, we find no...

Resilient Asset Allocation (RAA) is a more aggressive version of our Lethargic Asset Allocation (LAA) strategy. It combines a more robust “All Weather” portfolio with even slower growth-trend (GT) filter and a faster market crash-protection. GT timing goes risk-off only when both the US...

Traditional machine learning methods have been widely studied in financial innovation. My study focuses on the application of deep learning methods on asset pricing.I investigate various deep learning methods for asset pricing, especially for risk premia measurement. All models take the same set...