Markets are in turmoil, and there exist very few investors who are unscathed by current global events related to coronavirus pandemic. It’s a good time to revisit how are various groups of algorithmic trading strategies navigating current troubled times. The selected sample for this short article consists of 7 well-known equity factor strategies – size, value, momentum, quality, investment, short-term reversal and low volatility factors.

Our analysis shows that we have two groups of factors: strong winners and bad losers. There is no middle ground. A current bear market is ruthless, equity long-short factor strategies either totally nailed it and had a stellar performance or totally disappointed.

Mirror, mirror on the wall, what’s the best factor model of them all? We at Quantpedia are probably not the only one asking this question. A lot of competing factor models are described in the academic literature and used in practice. That’s the reason why we consider a new research paper written by Matthias Hanauer really valuable. He compared several commonly employed factor models across non-U.S. developed and emerging market countries and answered the question from the beginning of this paragraph. Which model seems the winner? The six-factor model proposed in Barillas et al. (2019) that substitutes the classic value factor in the Fama and French (2018) six-factor model for a monthly updated value factor …

Authors: Hanauer

Title: A Comparison of Global Factor Models

Once upon a time, there was everybody’s favourite finance tool in a town – Capital Asset Pricing Model, which was liked and used by nearly everyone. But a few decades ago, it went out of fashion. Easier accessibility of cheap finance databases allowed a lot of researchers to dig deeper into those data. They uncovered a tremendous amount of evidence for a lot of market anomalies not consistent with CAPM. A new research paper written by Park and Wang shows that CAPM is maybe not completely useless. The rise of automated trading causes individual stocks’ returns to align more closely with the market. Intraday correlation in the equity market is rising, and so is the fraction of firms’ returns that are explained by market returns …

Authors: Park, Wang

Title: Did Trading Bots Resurrect the CAPM?

Professor Robert Shiller’s work and his famous CAPE (cyclically-adjusted price-to-earnings) ratio is well known among the investment community. His methodology for assessing a valuation of the U.S. equity market is not the first one but is surely the most cited and the most discussed. There are numerous papers that tweak or adjust Shiller’s methodology to assess better if U.S. equities are under- or over-valued. We recommend the work of Wang, Ahluwalia, Aliaga-Diaz, and Davis (all from The Vanguard Group ) in which they use a combination of machine learning and a regression-based approach to obtain forecasted CAPE ratio, and subsequently, U.S. stock market returns, more accurately.

Authors: Wang, Ahluwalia, Aliaga-Diaz, Davis

Title: The Best of Both Worlds: Forecasting US Equity Market Returns using a Hybrid Machine Learning – Time Series Approach

The end of the year is a good time for a short recapitulation. Apart from other things we do (which we will summarize in our next blog in a few days), we have published around 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to summarize 10 of them, which were the most popular (based on Google Analytics tool). Maybe you will be able to find something you have not read yet …

Professor Roger Ibbotson is one of the most respected and influential researchers of the current era. His book “Stocks, Bonds, Bills, and Inflation” is a classic and often serves as a reference for information about capital market returns. Therefore we always pay attention to his publications. His actual work, “Popularity – A Bridge between Classical and Behavioral Finance”, which is written with Thomas M. Idzorek, Paul D. Kaplan, and James X. Xiong, is now available on SSRN.

In their work, authors explain the term “Popularity” from an asset pricing point and show how “Popularity” can be a broad umbrella under which nearly all market premiums and anomalies (including the traditional value and small-cap) can fall. They develop a formal asset pricing model that incorporates the central idea of “Popularity”, which they call the “popularity asset pricing model” (PAPM). Based on this model, they predict characteristics as a company’s brand, reputation, and perceived competitive advantage to be new equity factors.

It’s a long read, but we at Quantpedia really recommended it for all equity portfolio managers …

Authors: Ibbotson, Idzorek, Kaplan, Xiong

Title: Popularity: A Bridge between Classical and Behavioral Finance