Whenever traders want to assess the stock market’s mood, there is one really popular and useful index the most of them turn to. Yes, you guessed it right, it’s CBOE’s VIX Index. And which index can we use if we want to determine the mood of the cryptocurrencies? We can turn to a paper written by Fabian Woebbeking, which offers the methodology to compute two cryptocurrency volatility indexes (CVX & CVX76). The CVX and CVX76 Indexes also extract the market’s expectation of future volatility from option prices, but from options on the Bitcoin. The research suggests that the cryptocurrency option market has finally reached a sufficient market size to extract stable cryptocurrency volatility information.

Authors: Fabian Woebbeking

Title: Cryptocurrency Volatility Markets

The bear markets were and surely would be present in the equities in the future. While many fear them, experienced investors accept that the growth of the equity market cannot be constant and that inherent equity risk often manifests as a painful market drawdown. When someone designs a strategy, it is a general practice to check its performance during such downturns. Therefore, we can recommend an interesting novel research paper by Paul Geertsema and Helen Lu. The selected paper analyzes the risk of the most common equity factors and plots their over- or under-performance during multiple crisis periods since the Vietnam war until the COVID-19.

Authors: Paul Geertsema, Helen Lu

Title: The Risk in Risk Factors

How should be equity factor strategies implemented? In a long-only smart beta) way? As a long-short strategy, as most of the hedge funds usually do? Or in a partially-hedged fashion by going long equity factor and shorting market to offset some of the market risks? There is no one universal answer as it depends on the investment mandate and constraints of each fund manager contemplating to implement factor investing strategies. But recent academic paper written by Benaych-Georges, Bouchaud and Ciliberti suggests that it’s a good idea to go in the direction of long-short implementation (if it’s possible). Managing short book can be challenging; however, the added benefit of lower correlation among strategies gives resultant factor portfolio a significant boost in the return-to-risk ratio (even after accounting for realistic implementation and shorting costs).

Authors: Benaych-Georges, Bouchaud, Ciliberti

Title: Equity Factors: To Short Or Not To Short, That is the Question

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.

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.

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