The usage of alternative data is now a main-stream topic in investment management and algorithmic trading. So let’s together explore the textual analysis of 10-K & 10-Q filings and analyze how these datasets could be used as a profitable part of investment portfolios. We invite you to read this short summarization of the research. Full version can be found on the SSRN.

The presidential campaign is becoming hotter as we are moving closer to this year’s election. But we still have enough time to dig deeper into data about the past elections and prepare for autumn. Therefore, we have prepared a short video recapitulation of our paper on the pre-election drift.

The best course of action for every quant researcher is to try to fundamentally understand anomalies and explore their functioning besides the original scope of the academic research papers. The goal of this article was to look for inspiration and further explore the Skewness affect – the tendency of assets with the lowest skewness to outperform assets with the highest skewness. It seems that this anomaly is present not only in commodities but also in currencies, fixed income and equities. Trading strategy that exploits the effect of skewness in the multi-asset setting would earn an annual return of 7.67% when leveraged to the 15% volatility.

During past months we made a set of articles analyzing the performance of equity factors and selected systematic strategies during coronavirus crisis. These articles were short-ranged with data only from the start of the year 2020, which is enough for the purpose of the quick blog posts, but very short-sighted to see the nature of these strategies. Therefore, we expanded the time range by 20 years. For a better understanding of hedge possibilities of these strategies, we have added a comparison to essential safe-haven assets, not only to equities.

What will happen if we mix ESG scoring with price momentum? Can we improve simple ESG investing strategy?

The pure price momentum can be combined with ESG scores using a Knapsack algorithm. Knapsack algorithm is a well-known mathematical problem of optimization, and in the case of momentum and ESG, can be used to make the momentum portfolios significantly more responsible, with lower volatility and better risk-adjusted return. The second option is to make the ESG portfolio substantially more profitable by using Knapsack algorithm to construct high ESG portfolio with large momentum. The approach resulted in a strategy with high ESG score and compared to pure momentum or momentum-ESG strategy, with significantly reduced volatility. Therefore, the ESG-momentum strategy has the best risk-adjusted return, the lowest drawdown, the lowest volatility and the most consistent returns.

After a month, we are back with a year-to-date performance analysis of a few selected trading strategies. In the previous article, we were writing about the performance of equity factors during the coronavirus crisis. Several readers asked us to take a look also on different types of trading strategies, so we are now expanding to other asset classes. We picked a subset of strategies that can be used as a hedge at the times of market stress (at least, that’s what the source academic research papers indicate) and checked how they fared.