Factor investing

Retail Investment Boom, Robinhood, Passive Investing and Market Inelasticity

19.March 2021

This week’s blog is unique compared to our previous posts. We have identified two papers that are connected, each with interesting findings and implications. One of today’s leading topics is the Robinhood trading platform, but not from the point of view of recent short squeezes and speculations. The Robinhood can be an interesting insight into retail investing and implications for the market. Research suggests that despite the very low share of retail investors, their power is significantly high. This seems to be caused by the inelastic market, which passive investing contributes to. Therefore, inelasticity is another crucial point.

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Does Social Media Sentiment Matter in the Pricing of U.S. Stocks?

15.March 2021

Although the models cannot entirely capture the reality, they are essential in the analysis and problem solving, and the same could be said about asset pricing models. These models had a long journey from the CAPM model to the most recent Fama French five-factor model. However, the asset pricing models still rely on fundamentals, and as we see in the practice every day, the financial markets or investors are not always rational, and prices tend to deviate from their fundamental values. Past research has already suggested that the assets are driven by both the fundamentals and sentimen. The novel research of Koeppel (2021) continues in the exploration of the hypothesis mentioned above and connects the sentiment with the factors in Fama´s and French´s methodology. The most interesting result of the research is the construction of the sentiment risk factor based on the direct search-based sentiment indicators. The data are sourced by the MarketPsych that analyze information flowing on social media. For comparison, public news is not a source of such exploitable sentiment indicator.

The sentiment score extracted from social media can be exploited to augment the Fama French five factors model. Based on the results, this addition seems to be justified. Adding the sentiment to the pure fundamental model explains more variation and reduce the alphas (intercepts). Moreover, the factor is unrelated to the well-known and established risk factors utilized in the previous asset pricing models, including the momentum. Finally, the sentiment factor seems to be outperforming several other factors, even those established as the smart beta factors.

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A Robust Approach to Multi-Factor Regression Analysis

24.February 2021

Practitioners widely use asset pricing models such as CAPM or Fama French models to identify relationships between their portfolios and common factors. Moreover, each asset class has some widely-recognized asset pricing model, from equities through commodities to even cryptocurrencies. 

However, which model can we use if our portfolio is complex and consists of many asset classes? Which factors should we include and which should we omit? (Especially if we have a database that consists of several hundreds of potential factors). Additionally, we know that equities influence bonds, commodities influence equities and vice versa. Hence the question, what about the cross-asset relationships? 

These are the problems and questions we faced when looking for a methodology for our Multi-Factor Analysis report in the Quantpedia Pro platform. This blog post aims to introduce the model, its logic and the method we have decided to use. 

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Basic Properties of Various Real Asset Portfolios

5.February 2021

Do not put all your eggs in one basket is a common phrase that resonates among investors worldwide. The errand of such a famous saying is simple, diversify! However, how to diversify, if in the crisis, everything seems to be highly correlated? Last week, we wrote a blog about the Macro Factor Risk Parity, but it certainly is not the only option. Real assets such as REITs, various commodities, and the ever-popular gold are commonly added into portfolios as diversifiers. However, Parikh and Zhan (2019) research examine a much bigger set of real assets than the aforementioned evergreens. Real assets like Timberland, Farmland, Infrastructure, Natural Resources and many others are presented in the paper. All those assets have different sensitivities to inflation, GDP growth, equities or bonds. Therefore, real assets could have a value in the portfolios to protect an investor from inflation, stagnation, or simply distributing the eggs mentioned above in many baskets. All these strategies are presented in the paper and compared to equities, bonds and traditional 60/40. 

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Macro Factor Risk Parity

29.January 2021

Risk and diversification are critical interests of every investor, especially when things go south since the correlations across assets tend to rise during stressful times. Therefore, in the asset allocation, the risk parity allocation is one of the key topics. Factors are commonly known as underlying sources of both risk and returns, and it is assumed that they can be utilized to achieve superior risk-adjusted returns and diversification. However, there seems to be a lack of research that would be related to the macro factors. This gap is quite striking since there is a general consent that macro factors (for example, inflation) largely influence the broad set of assets. Amato and Lohre (2020) research paper fills the gap and studies the usage of macro factors as diversifiers in asset allocation.

The authors divide the macro factors to two groups, where the first consists of TERM, MARKET, USD, OIL and DEF (default risk), and the second group consists of CLI (a measure of output by OECD), G7.INFLATION, G7.Short.Rate and VIX. The research shows, that when the diversification matters the most, only the second group improves both the risk and returns, acting as a successful diversification during various economic regimes and particularly, during high economic uncertainty. Overall, the paper offers exciting insights into diversification and macro factors, accompanied by more complex mathematical models definitely worth looking into.

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