During past months we made a set of articles analyzing the performance of equity factors and selected systematic strategies during coronavirus crisis. These articles were short-ranged with data only from the start of the year 2020, which is enough for the purpose of the quick blog posts, but very short-sighted to see the nature of these strategies. Therefore, we expanded the time range by 20 years. For a better understanding of hedge possibilities of these strategies, we have added a comparison to essential safe-haven assets, not only to equities.

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

After a month, we are back with a year-to-date performance analysis of a few selected trading strategies. In the previous article, we were writing about the performance of equity factors during the coronavirus crisis. Several readers asked us to take a look also on different types of trading strategies, so we are now expanding to other asset classes. We picked a subset of strategies that can be used as a hedge at the times of market stress (at least, that’s what the source academic research papers indicate) and checked how they fared.

A lot of backtests of systematic trading strategies omit transaction costs (in the form of spreads and fees). Simulation is then simpler, but resultant model portfolio and its performance can be misleading. In the case of currency factor investing, backtest without the costs simulation can pick currencies with wider spreads and higher volatilities. And in real trading, with real-world transaction costs, a strategy can, therefore, perform significantly worse than expected. A research paper written by Melvin, Pan, and Wikstrom offers an elegant optimization methodology to incorporate transaction costs into the backtesting process which allows strategies to retain their alpha …

Authors: Michael Melvin, Wenqiang Pan, Petra Wikstrom

Title: Retaining Alpha: The Effect of Trade Size and Rebalancing Frequency on FX Strategy Returns

Four new strategies have been added.

Four new related research papers have been included into existing strategy reviews and two short free blog posts have been published during last few weeks. Plus, eight trading strategies have been backtested in QuantConnect in the previous two weeks.