Asset class picking

Hierarchical Risk Parity

21.February 2020

Various risk parity methodologies are a popular choice for the construction of better diversified and balanced portfolios. It is notoriously hard to predict the future performance of the majority of asset classes. Risk parity approach overcomes this shortcoming by building portfolios using only assets’ risk characteristics and correlation matrix. A new research paper written by Lohre, Rother and Schafer builds on the foundation of classical risk parity methods and presents hierarchical risk parity technique. Their method uses graph theory and machine learning to build a hierarchical structure of the investment universe. Such structure allows better division of assets into clusters with similar characteristics without relying on classical correlation analysis. These portfolios then offer better tail risk management, especially for skewed assets and style factor strategies.

Authors: Lohre, Rother and Schafer

Title: Hierarchical Risk Parity: Accounting for Tail Dependencies in Multi-Asset Multi-Factor Allocations

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How to Choose the Best Period for Indicators

3.December 2019

Academic literature recognizes a large set of indicators or factors that are connected with the various assets. These indicators can be utilized in a variety of trading strategies, which means that such indicators are popular among practitioners who seek to invest their funds. Usually, the indicators are connected with some evaluation period.

This paper aims to show some possible approaches to find the optimal evaluation periods of indicators. This is a key question among practitioners and therefore we see it as crucial to shed a light on this topic. Although we are focused on momentum strategies, the information in this paper is widely applicable also in the construction of any other trading strategy where the investor has to decide indicator’s period…

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Commodity Futures Risk Premium – Historical Analysis

17.October 2019

We at Quantpedia absolutely love long-term studies, and academic research paper written by Bhardwaj, Janardanan, and Rouwenhorst is really exceptional. There are a lot of studies covering a long history of equity and bond markets. But futures markets are not covered so well, and that’s the reason why is this paper so valuable. An additional plus is that study covers also delisted contracts, which makes the study’s data quality even better. Quantpedia’s recommended read to anyone interested in asset allocation into commodities …

Authors: Bhardwaj, Janardanan and Rouwenhorst

Title: The Commodity Futures Risk Premium: 1871–2018

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What Affects the Correlation Between Stocks and Bonds

26.August 2019

The correlation between bonds and stocks is essential information for asset allocation decisions; therefore understanding its macro-economic drivers is very valuable for all investors. Stocks-bonds correlation isn’t stable, as we have experienced in the last 30 years, as the correlation, which was positive until the end of the 1990s, changed sign at the turn of the century. Research paper written by Marcello Pericoli sheds more light on this issue and shows that the correlation is primarily influenced by the uncertainty about inflation and real interest rates as well as by co-movement between inflation, real interest rates and dividend growth.

Author: Pericoli

Title: Macroeconomics Determinants of the Correlation Between Stocks and Bonds

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