This research uses macro factors to explain four standard U.S. stock market risk premia, i.e. the market excess return (RM-RF), size (SMB), value (HML), and momentum (WML). We find in-sample predictive power of macro factors, in particular at a one-year horizon. Differentiating between bull and...

This research uses macro factors to explain four standard U.S. stock market risk premia, i.e. the market excess return (RM-RF), size (SMB), value (HML), and momentum (WML). We find in-sample predictive power of macro factors, in particular at a one-year horizon. Differentiating between bull and...

The prices of derivatives contracts can be used to estimate ‘risk-neutral’ probability density functions that give an indication of the weight investors place on different future prices of their underlying assets, were they risk-neutral. In the likely case that investors are risk-averse,...

This paper examines the role of pricing errors in linear factor pricing models, allowing for observed strong and semi-strong factors, and latent weak factors. It focusses on the estimation of ∅k = λk − μk which plays a pivotal role, not only in the estimation of risk premia but also in...

Fama and French (2015) recently proposed a five-factor model which adds investment and profitability terms to their seminal three-factor model. Motivated by the accounting-based nature of the new factors, we conduct a comprehensive test of variants of the models in Indonesia – a country which...

We propose factor models for the cross-section of daily cryptoasset returns and provide source code for data downloads, computing risk factors and backtesting them out-of-sample. In "cryptoassets" we include all cryptocurrencies and a host of various other digital assets (coins and tokens) for...

Current factor models do not identify risks that matter to investors. To address this issue, we provide a factor model implementation of the ICAPM, which captures market risk and intertemporal risk (i.e., changes in long-term expected returns and volatility). We build our intertemporal risk...

We propose a protocol for identifying genuine risk factors. The underlying premise is that a risk factor must be related to the covariance matrix of returns, must be priced in the cross-section of returns, and should yield a reward-to-risk ratio that is reasonable enough to be consistent with...

We propose a simple and intuitive method for estimating betas when factors are measured with error: ordinary least squares instrumental variable estimator (OLIVE). OLIVE performs well when the number of instruments becomes large, while the performance of conventional instrumental variable...

Earlier studies in the finance literature show that macroeconomic fundamentals can predict excess bond returns. We employ a multi-level factor model to estimate global and sectoral factors separately and show that (i)the real factors possess most important predictive power existing in the panel;...