Factor investing

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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Large Cap Analysis

23.December 2020

Every week, through these posts, we point to interesting academic research papers. This week´s blog is slightly different, yet no less engaging. This blog includes numerous interesting charts from more than hundred charts in the CUSTOM REPORT: U.S. LARGE INDEX by the PHILOSOPHICAL ECONOMICS using OSAM Research Database. The report consists of the visually presented analysis of the U.S. Large index. The analysis includes the composition, returns, individual stocks, sector and factor allocations, and six fundamentals. The report contains comprehensive information about the large caps in the U.S. market from 1963 to 2020 and is worthy of a look.

We wish you all Merry Christmas …

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The Active vs Passive: Smart Factors, Market Portfolio or Both?

11.December 2020

While there may be debates about passive and active investing, and even blogs about the numbers of active funds that were outperformed by the market, the history taught us that the outperformance of active or passive investing is cyclical. As a proxy for the active investing, the new Quantpedia’s research paper examines factor strategies and their smart allocation using fast or slow time-series momentum signals, the relative weights based on the strength of the signals and even blending the signals. While the performance can be significantly improved, using those smart approaches, the factors still got beaten by the market in both US and EAFE sample. However, the passive approach did not show to be superior. The factor strategies and market are significantly negatively correlated and impressively complement each other. The combined Smart Factors and market portfolio vastly outperforms both factors and market throughout the sample in both markets. With the combined approach, the ever-present market falls can be at least mitigated or profitable thanks to the factors.

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Stock Price Overreaction to ESG Controversies

23.November 2020

Nobody can doubt that in the recent period, ESG investing has significantly grown and is a staple part of the financial markets. The academic literature has also grown with the popularity of ESG investing. The negative, mixed and positive results for ESG scores in portfolios have evolved, and generally, there is a consent that ESG scoring can be a vital part of the portfolio management process. It can be observed that in the past, the ESG scores were not priced in the equity market and still, the ESG is not priced in the corporate bond market (apart from Europe). Nowadays, the investors react to the ESG scores, but the research paper of Cui and Docherty (2020) has novel insights that investors may react too much to the ESG. Their research shows that investors overreact to the negative ESG events and stocks connected with negative ESG events sharply fall, but the prices have mean-reverting properties. As a result, there is a reversal after bad ESG events. Stocks firstly sharply fall, but then their prices are reverted to the previous values. Therefore, this paper is interesting from the market pricing or efficiency point, but it also can be utilized by a reversal investor.

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Can Analysts Predict Performance of the US and International Stocks?

12.November 2020

Analysts recommendations are quite puzzling topic among both practitioners and academics as well. The most important question related to the analysts is straightforward: what is the value of their recommendations? The research paper of Azvedo and Müller (2020) brings light on this topic, but also explores the relation of analysts recommendations and market anomalies. In line with other literature, it seems that the recommendations are significantly more valuable in international markets compared to the US market. While the prediction ability of analysts is not present in the US market, less developed markets and markets with higher limits-to-arbitrage are connected with valuable recommendations. Secondly, using around 200 cross-sectional anomalies, authors show that analysts are more lined up with anomaly-based composite mispricing measures in international markets. Therefore, there is not a bias from analysts to recommend overvalued stocks in global markets compared to the well-developed US market. We highlight several results and tables, but the paper is full of impressive results, ideas and tables. Therefore, we invite you to read this blog post as well as the source research paper.

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