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ETFs: What’s Better? Full Replication vs. Representative Sampling?

August 10, 2022

ETFs employ two fundamentally distinct methods to replicate their underlying benchmark index. The more conventional method, physical replication, involves holding all constituent securities (full replication) or a representative sample (representative sampling) of the benchmark index. In contrast, the synthetic replication achieves the benchmark return by entering into a total return swap or another derivative contract with a counterparty, typically a large investment bank. As we have previously discussed, there is no significant difference in the tracking ability between the physical and synthetic ETFs in the long term. And while our article compares physical and synthetic ETFs, it does not address the differences between the full replication ETFs and sampling ETFs. Therefore, one may ask a question: “When selecting a physically replicated ETF, which replication method is better, full replication or representative sampling?”

The Importance of Factor Construction Choices

July 22, 2022

Choosing the correct portfolio-construction techniques is very important. The new paper that is written by Amar Soebhag, Bart van Vliet, and Patrick Verwijmeren explores the various ways in which different design choices in portfolio construction can, either intentionally or unintentionally, influence and distort the statistical results of a market factor’s research. Their takeaway is that seemingly small differences in design can significantly impact the resultant portfolio’s performance.

Takeover Factor Explains the Size Effect

July 18, 2022

The size effect assumes a negative relationship between average stock returns and firm size. In other words, it states that low capitalization stocks outperform stocks with large capitalization. Although generally accepted, the size effect keeps being challenged. Researchers have been asking how important the firm size characteristic actually is, and whether it is possible to replace the traditional size factor of Fama and French asset pricing model (1993) with more accurate factor. Recently, one potential challenger has emerged – so-called takeover factor, employed by Easterwood et al. (2022). In their study, they work on the assumption that small firms are often targets of takeovers, which gives us a different perspective on merger and acquisition news in regards to size effect. Their results show that M&A component of average returns explains the size premium entirely.

Quantpedia Introduces 3rd Party Factors

June 28, 2022

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.

Best Performing Value Strategies – Part 2

June 8, 2022

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.

100-Years of Multi-Asset Trend-Following

May 27, 2022

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.

Extending Historical Daily Commodities Data to 100 Years

May 25, 2022

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.

Best Performing Value Strategies – Part 1

May 23, 2022

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.

Grading and Merging ESG Scores from Multiple Providers

May 13, 2022

Socially responsible investing, also known as ESG investing, is a recent trend in the world of portfolio management. More and more investors have started to look into the Environmental, Social, and Governance scores of the companies they invest in. However, one major problem with ESG scoring is that there is not one universal scoring system. Many companies sell ESG data, but the scores are not comparable, and additionally, the ESG data providers are not very transparent about how they create the ratings. These problems with ESG data mean we need to have a method to grade and merge the information from multiple providers.

How Often Should We Rebalance Equity Factor Portfolios?

May 10, 2022

Quantpedia has already covered a countless number of factor investing strategies and articles, from strategies in our Screener to multiple blog posts. Therefore, we can confidently say that we do like factor investing. However, there is always new research with a unique point of view. For example, we recently found a paper focused on the decay of the factor exposures of equity factor strategies. The study examines five factors: Value, Momentum, Quality, Investment, and Low Volatility, across 12 developed and emerging markets over a 20-year period. This research aims to find out how long it takes for a factor to decay after the portfolio is assembled. In other words, how often should the portfolio be rebalanced?