Quantpedia in August 2023

Hello all,

What have we accomplished in the last month?

– A new Component Analysis report for Quantpedia Pro subscribers
– 11 new Quantpedia Premium strategies have been added to our database
– 11 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 7 new backtests written in QuantConnect code
– 5 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month
– we present an independent test of Quantpedia’s strategy by AllocateSmartly
– and finally, we would like to invite you to “A systematic approach to ESG investing” webinar we co-organize

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Performance of Factor Strategies in India

India is a big emerging market, actually the second biggest after China. We primarily look at developed markets, mostly the U.S. and Europe, and from Emerging Markets, China at most, and we are aware that we neglect this prospective country. We would like to correct this notion and give attention to a country that is (along with China) being cited as a new potential rising superpower and already looking to take the lead of Emerging Markets (EM) countries. Today, we would like to review the paper that analyzes the performance of main equity factors (with an emphasis on the Quality factor) and is a good starting point to understand the specifics of factor investing strategies in India.

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Dissecting the Performance of Low Volatility Investing

Low volatility investing is an appealing approach to compound wealth in the stock market for the long term. This particular factor investing style exploits the popular naive notion that lower (higher) risk must always equal lower (higher) overall returns. But in fact, this naive assumption is not true, as low-volatility investments often yield more than their high-volatility counterparts. While low-volatility investing has many advantages, it also results in some disadvantages. How to overcome them? Bernhard Breloer, Martin Kolrep, Thorsten Paarmann, and Viorel Roscovan, in their study Dissecting the Performance of Low Volatility Investing, propose a solution.

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Predicting Stock Market Performance with the Global Anomaly Index

Today’s article focuses on investigating long-short anomaly portfolio return predictability in international stock markets, which often undergo mispricing due to investors’ sentiment. A paper by Jiang, Fuwei et al. (Apr 2023), suggests using the AAIG (Global Anomaly Index), and it examines the ability of the aggregate anomaly index to predict future returns in 33 stock markets. While previous research finds that a high aggregate anomaly measure predicts a low return in the U.S. market, this study further demonstrates that the global component of AAI (aggregate anomaly indices) is the key that drives international return predictability and reveals that the global anomaly index is a strong and robust predictor of equity risk premiums not just in the U.S. market but also in international markets, both in- and out-of-sample, consistently delivering significant economic values.

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