Asset allocation

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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Probability Distributions of Bull and Bear Market States

22.January 2021

Numerous academic papers have shown that the options markets are not only the place where the supply and demand for options meets. For example, they might point out to the smart money positioning, help to assess risk in the form of implied volatility, or be base of the well-known fear index VIX. Novel research of Bhansali and Holdom (2021), uses information embedded in options markets to construct a probability-weighted mixture of two distributions of bull and bear market states for the S&P 500 index. The results show that the implied return distributions drastically change switching from normal to stressed market states and vice versa. Moreover, the uncertainty in both distributions changes in the same fashion.

An excellent example is the shift of distribution before and after the recent US presidential election, which can be found below. Many have feared that if the democrat candidate Biden wins the elections, it would be a bad signal for the markets. However, after the uncertainty has passed, the fear has seemed to disappear. Additionally, the paper also shows how to use the bimodality in return distributions for the asset allocation using various utility functions. Allocations are made using a risky asset, risk-free and even options. Indeed, this research is worth reading. 

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