Introduction to Clustering Methods In Portfolio Management – Part 1

16.September 2021

At the beginning of October, we plan to introduce for our Quantpedia Pro clients a new Quantpedia Pro report dedicated to clustering methods in portfolio management. The theory behind this report is more extensive; therefore, we have decided to split the introduction into our methodology into three parts. We will publish them in the next few weeks before we officially unveil our reporting tool. This first short blog post introduces three clustering methods as well as three methods that select the optimal number of clusters. The second blog will apply all three methods to model ETF portfolios, and the final blog will show how to use portfolio clustering to build multi-asset trading strategies.

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Does Gambling Influence Stock Markets Around the World?

13.September 2021

Is there any association between the country’s stock market and its gambling policy? Surprisingly, yes, and there’s more to it than one would think. In a new research paper, Kumar, Nguyen and Putnins offer a complex study of gambling activities in 38 countries worldwide to estimate the impact on their financial markets.

The research’s dataset follows that around 86% of the estimated total global gaming revenue comprises traditional gambling forms – casinos, lotteries, sports betting, and many others. Moving to the financial markets, the authors introduce a split of stocks into lottery-like and non-lottery stocks to estimate the amount of gambling in stock markets. Lottery-like stocks are expected to be traded much more often than other stocks. It turns out that 14% of developed markets, 18% of emerging ones and 33% of retail-dominated Asian markets (China, Thailand) is being gambled. Generally, there is 3.5 times more capital gambled in the stock market around the world compared to the traditional ways combined together.

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How to Use Lexical Density of Company Filings

10.September 2021

The application of alternative data is currently a strong trend in the investment industry. We, too, analyzed few datasets in the past, be it ESG datasentiment, or company fillings. This article continues the exploration of the alt-data space. This time, we use the research paper by Joenväärä et al., which shows that lexically diverse hedge funds outperform lexically homogeneous as an inspiration for us to analyze various lexical metrics in 10-K & 10-Q reports. Once again, we show that it makes sense to transmit ideas from one research paper to completely different asset class.

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A New Return Asymmetry Investment Factor in Commodity Futures

8.September 2021

As mentioned several times, Quantpedia is a big fan of transferring ideas from one asset class to another. This article is another example; we use an idea originally tested on Chinese stocks and apply it to the commodity futures investment universe. The resultant return new asymmetry investment factor in commodities is an interesting trading strategy unrelated to other common factors and has a slightly negative correlation to the equity market and can be therefore used as an excellent diversifier in multi-asset multi-strategy portfolios.

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Find Your Crisis Hedge – Quantpedia Highlights in August 2021

6.September 2021

Hello all,

What have we accomplished in the last month?

– A new important Crisis Hedge Quantpedia Pro report
– 10 new Quantpedia Premium strategies have been added to our database
– 10 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 10 new backtests written in QuantConnect code
– And finally, 12 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

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Factor Exposures of Thematic Indices

31.August 2021

Numerous new businesses are emerging related to autonomous traffic, clean energy, biotechnology, etc. Without any doubt, these new companies look promising and at least the technology behind them seems to be the future. Moreover, this novel trend is also supported by the most prominent index creators S&P and MSCI. Both providers have created numerous thematic indexes connected to these hot industries. The popularity has caused that ETFs are nowhere behind, and as a result, these thematic indexes could be easily tracked. However, popularity itself does not guarantee the best investment, and we should be interested in these indexes in greater detail. A vital insight provides the novel research paper of Blitz (2021). The findings are interesting – the thematic investors bet against quantitative investors or, more precisely, against the most common factors that are well-known from the asset pricing models.

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