Volatility effect

Bitcoin in a Time of Financial Crisis

16.March 2020

One of the very often promoted attributes of Bitcoin is said to be its “safe heaven” characteristic. Some cryptocurrency proponents advocate that Bitcoin can be used as a store of value mainly during the economic and financial crisis. We argue that it’s not so.

Bitcoin (and all cryptocurrencies too) is, in our opinion, fundamentally more similar to stocks of small companies from the technological sector. It is a very speculative bet on blockchain technology. It may seem unrelated to the broader equity market (like the S&P 500 index) during normal times. But when a stressful time comes, investors are more concerned to meet a deadline for the next mortgage payment. This is the time when the speculative bets are closed, and cash is raised. And this is precisely the time when Bitcoin falls as equities do too.

Continue reading

Rational Panic on Markets Because of Coronavirus?

10.March 2020

Financial markets are in panic mode. Everybody is talking about the next bear market and economic implications of spreading coronavirus to the whole world. People are split into two groups. One group reasons that a new covid-19 virus is just a stronger flu. Other are worried and draw parallels to Spanish flu pandemic with tens of millions of dead.

We would like to show you two charts which can explain why the high market volatility can be completely rational.

Continue reading

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

Continue reading

Why Do Top Hedge Funds Outperform?

30.January 2020

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

Continue reading

Pre-Election Drift in the Stock Market

23.January 2020

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

Continue reading

Why Did Trend-Following Underperform Last Decade?

20.December 2019

Trend-following funds and strategies were once extremely popular after the 2008/2009 crisis. They offered attractive performance, and diversification properties made them a nice addition to investor’s portfolios. Ten years later, “trend-following strategy” is not such a popular word. Strategies didn’t blow-up, but their performance was far from spectacular. What are the main reasons for that? Is it an increased correlation among markets? Are trend rules inefficient? An important recent academic study written by Babu, Hoffman, Levine, Ooi, Schroeder, and Stamelos (all from AQR Capital Management) analyzes trend-following performance for each decade in the last 140 years and uses three distinct factors: the magnitude of market moves, the efficacy of trend-following strategies at capturing profitability from market moves, and the degree of diversification across trends in a trend-following portfolio. They show that it’s the first factor (a lack of large risk-adjusted market moves, positive or negative) that had the biggest impact in the last decade. This suggests that trend-following strategies should be able to deliver better performance in the future if the size of the market moves reverts to levels more consistent with the long-term historical distribution of returns…

Authors: Babu, Hoffman, Levine, Ooi, Schroeder, and Stamelos

Title: You Can’t Always Trend When You Want

Continue reading

Subscribe for Newsletter

Be first to know, when we publish new content


    logo
    The Encyclopedia of Quantitative Trading Strategies

    Log in