Every year, Quantpedia’s team investigates thousands of academic research papers to bring you the most promising ideas from the academic world. We read papers, identify ideas and backtest them to build our unique database. As a result, we have already identified hundreds of factors and built tools to help you orient better in the broad universe of trading strategies and systematic investment factors.

And now, we are opening the possibility to all external researchers, quants, and portfolio managers to contribute to Quantpedia.

A recent spring 2022 crisis in the cryptocurrency market emphasized the importance of market-neutral crypto trading strategies. It’s not enough just to HODL crypto market and hope for the everlasting bull market. Therefore, we continue our series of research articles about the cryptocurrency market and offer an analysis of the skewness anomaly. So after our description of the skewness effect in commodities, an article about the multi-asset skewness strategy, and observation of the skewness/lottery effect in ETFs, we have one more asset class, where we can find lottery/skewness anomaly – in cryptocurrencies.

We focused the first part of this article more on tendencies and trends among these US Equity Value strategies. Today we will talk solely about specific top-performing equity value strategies. More specifically, about numbers #7 to #1 from Quantpedia’s ranking. We will also take a look at combining all the value strategies together into a diversified portfolio of value strategies.

Trend-following strategies have gained extreme popularity in the recent decade. Almost every asset manager utilizes trend following, or momentum, in some form – whether consciously or subconsciously. We at Quantpedia are convinced that each and every strategy has to be scrutinized thoroughly before it’s put into use. This is one of our motivations why we will introduce to you our framework for building a 100-year daily history of a multi-asset trend-following strategy today.

Finding a high-quality data source is crucial for quantitative trading strategies. Also, having a long history is beneficial. Fama & French, for example, offer free historical data for stocks and a variety of factors. However, it is very hard to get good-quality and free data for other asset classes. For this reason, we have already examined how to extend historical daily bond data to 100 years.

For any event-driven analysis or to perform stress tests of various historical situations, long-enough data can only help. Whether one wants to analyze past market patterns, or simply examine the risk of their portfolio under different historical scenarios, the use case for long data is pretty straightforward.

Following the theme of our previous article, we decided to extend historical data of another asset class, commodities. This article explains our commodity data methodology and introduces data sources, which helped us extend historical daily commodities data to 100 years.

Equity Value strategies have suffered hardly during years 2018, 2019 and also 2020. Due to the poor performance of Value during this period, many investors have abandoned the strategy, often expressing view that “Value strategy is not working anymore”. Nevertheless, equity Value strategies have managed a strong comeback recently, turning attention of investors and traders back to them. In our blog today, we will take a close look at many different equity Value strategies, their performance and how they behave.