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

Our society teaches us, that it is good to be different. That our trading strategy must be always unique, creative and individualistic. It is boring and unprofitable to be the “average”, to do what the others do. And then, there is a research paper written by Bollen, Hutchinson and O’Brian which offers the opposite view. Their analysis explains there exist one hedge fund style where everything is the other way round – trend-following CTAs funds. Their interesting (but for some maybe controversial) paper shows that CTAs with returns that correlate more strongly with those of peers have higher performance. It appears that CTA strategy conformity is a signal of managerial skill. Now, that is an eccentric idea 🙂

Authors: Bollen, Hutchinson and O’Brian

Title: When It Pays to Follow the Crowd: Strategy Conformity and CTA Performance

Some see Bitcoin (BTC) as a payment method of the future; others see it as a speculative asset class. Despite the speculative activity connected with Bitcoin, after all, it is a currency that is different from fiat currencies like the US Dollar or Euro. If you hold fiat currency, there is an opportunity to earn a risk-free rate. But is there the same opportunity also in Bitcoin? And what are the Bitcoin’s risk-free and market rates? These are the questions we had in Quantpedia, and we invite you to join us in our thought experiment that tries to answer them …

Authors: Vojtko, Padysak

Title: What is the Bitcoin’s Risk-Free Interest Rate?

Dear readers,

Five new Quantpedia Premium strategies have been added into our database in January, and five new related research papers have been included into existing Premium strategies.

Additionally, we have produced 16 new backtests written in QuantConnect code. Therefore our database currently contains over 220 strategies with out-of-sample backtests/codes.

Every hedge fund manager and every trader wants to know what strategies are employed in a fund ran by his competition. The curiosity is even stronger if we want to see how strategies are mixed in the kitchen of the most successful hedge funds. Top performing funds are usually notoriously secretive about their portfolios. But we still can learn something from the history of their monthly returns. One such interesting methodology is described in a research paper written by Canepa, Gonzalez, and Skinner. Their analysis hints that the top-performing hedge funds are usually successful because they are able to manage their factor exposure better. They are not dependent so much on classical equity risk factors as average funds are. And if they are exposed to some risk factor, the top-performing hedge funds are able to close underperforming factor strategy sooner than average funds.

Authors: Canepa, Gonzales, Skinner

Title: Hedge Fund Strategies: A non-Parametric Analysis

There are many calendar / seasonal anomalies by which we can enhance our strategies to gain more return. One of the least frequent but still very interesting anomalies is for sure the Pre-Election Drift in the stock market in the United States. This year is the election year, and public discussion is getting more heated. The current president of the United States and candidate for re-election, Donald Trump, is a peculiar figure who split the population of the United States into two parts, ones who hate him and those who love him. We can probably expect volatile market moves as we will move closer to this year’s presidential election. But this post will not be about politics but about trading. In this post, we will try to uncover a pattern in historical data that shows significant market moves a few days before elections…

Authors: Vojtko, Cisar

Title: Pre-Election Drift in the Stock Market