As we have mentioned several times, the best course of action for a quant analyst who wants to develop a new trading strategy is to understand a well-known investment anomaly/factor fundamentally and then improve it. Quantpedia is a big fan of transferring ideas derived from academic research from one asset class to another. But that’s not the only possibility of improvement – we can try to embrace Roger Ibbotson’s theory of popularity, which states that popular assets/securities are usually overpriced compared to less-known (exotic) assets/securities. Additionally, more professional investors usually follow popular assets, and this market segment is probably significantly more efficient.

So, we went in this direction. We took a well-known commodity momentum factor strategy and investigated its performance among commodity futures that were part of the S&P GSCI respectively BCOM commodity indexes and then compared the strategy’s performance with a variant that traded only non-indexed commodity futures. As we had expected, the trading strategy using exotic assets performed significantly better.

In the first part of our article, we talked about quantitative strategies which achieved even better results in 2021 than passive US equity investors. Then, we focused more on tendencies and trends among the best quantitative investment strategies. Today we will talk more deeply about specific trading strategies and shortly describe number #10 to number #6 of the best quantitative strategies of 2021.

As of the first half of August, the year 2021 seems to be a phenomenal year for equities. World equities have earned more than +16%, and US equities, even more, topping +20% gains. Is there even any better strategy this year than just holding US equities? Well, yes, there are actually several of them. Are they all tied to US equities? Many of them are, but many of them are not. Some of them are not even tied to equities at all.

Note: This blog is Part 1 of a series. Part 2 is available here, and Part 3 is available here.

We started to systematically search for systematic cryptocurrency trading strategies in academic research approximately two years ago. This article is a short analysis of the performance of systematic crypto strategies in 2021. We conclude that non-price predictors offered advantages over price-based only trading strategies in the previous year-to-date and 12-months periods.

This blog post will give you a short recapitulation of the five quick market/portfolio insights built from Quantpedia Pro reporting.

– Gold displays a strong seasonal tendency in returns in days around US public holidays.

– The performance of Bitcoin is usually the worst during the same time as stock market experiences the bear market.

– Cryptocurrency market correlation slowly increases, and we can’t rule out the financialization of the crypto market (the same process that happened in commodities approximately ten years ago).

– Skewness-based trading strategies could serve as a practical hedge/diversification during stock market drawdowns.

– We show the main attribute of most of the risk parity portfolios – lower total returns but significantly lower risk measures.