Momentum is the tendency of investments to persist in their performance. Assets that perform well over a 3 to 12 month period tend to continue to perform well into the future. The momentum effect of Jegadeesh and Titman (1993) is one of the strongest and most pervasive financial phenomena. Momentum investment strategies have been mostly applied to equities (see momentum in equities), however there is large evidence documenting momentum across different asset classes. Typical strategy consists of a universe of major indices on equity, bonds, real estate and commodities. The aim is to keep long only portfolio where an index with positive past 12 month returns is bought and negative returns sold. A well-known example of trend following momentum strategy is from Faber (2007). He creates 10 month moving average for which assets are sold and bought every month based on price being above or below the moving average. Using a 100 years of data, Faber claims to outperform the market with the mean return of 10.18% , 11.97 % volatility and max draw-down of 50.29%, compared to S&P 500 return of 9.32%, volatility of 17.87% and max draw-down of 83.46%.
In general, we distinguish between absolute and relative momentum. Absolute momentum is captured by trend following strategies that adjusts weights of assets based on past returns such as relative level of current prices compared to moving averages. Relative or cross sectional momentum, on the other hand, use long and short positions applied to both the long and short side of a market simultaneously. It makes little difference whether the studied markets go up or down, since short momentum positions hedge long ones, and vice versa. When looking only at long side momentum, however, it is desirable to be long only when both absolute and relative momentum are positive, since long-only momentum results are highly regime dependent. In order to increase performance, the simple momentum strategy is expanded to capture both relative and absolute momentum creating a long short portfolio.
Various extensions to the simple strategies shown above have been suggested. For example we can deploy mean-variance optimisation to re-weight our assets to minimise the risk given return. Moreover, we can diversify the strategy by restricting the weights to different asset classes and risk factors as well as adding various risk management practices to decrease leverage during heightened volatility periods. Furthermore, taking into account the cyclicality and idiosyncratic momentum of various sub-indices to Faber’s original asset classes produces even stronger improvements to risk-adjusted returns. Unfortunately, cross-sectional strategies use high number of stocks resulting in high trading costs. Luckily, it has been found that using sectors and indices instead of individual stocks still earns similar momentum returns while having lower trading costs.
Numerous empirical studies report on benefits of extending momentum strategy across asset classes (see Rouwenhorst 1998, Blake 1999, Griffin, Ji, and Martin 2003, Gorton, Hayashi, and Rouwenhorst 2008, Asness, Moskowitz, and Pedersen 2009). For example, including commodities in a momentum strategy can achieve better diversification and protection from inflation while having equity like returns (Erb and Harvey, 2006). Foreign exchange is another asset class with published momentum effects. Okunev and White (2003) find the well-documented profitability of momentum strategies with equities to hold for currencies throughout the 1980s and the 1990s. Contrary to already mentioned asset classes, bond returns have generally not displayed momentum. However, some later evidence suggests that assorting bonds with volatility adjusted returns leads to observation of momentum. Using 68,914 individual investment-grade and high-yield bonds, Jostova et al. (2013) find strong evidence of momentum profitability in US corporate bonds over the period from 1973 to 2008. Past six-month winners outperform past six-month losers by 61 basis points per month over a six-month holding period. Last but not least, momentum has been documented in real estate with a cross-sectional momentum buy/sell strategy significantly reducing volatility and drawdown of a long only REIT fund.
An often cited benefit of momentum strategies is their sustainable performance attributed to a true anomaly rather than skewedness in the return probability distribution that is cited to be responsible for value and carry strategy. Reasons explaining the momentum anomaly include analyst coverage, analyst forecast dispersion, illiquidity, price level, age, size, credit rating, return chasing and confirmation bias, market-to-book, turnover and others.
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
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 tcosts 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
Trend-following strategies are very effective when markets are cleanly trending, but they suffer when trends end too soon. How markets behaved during the last few years, were they prone to last-longing trends? Are we able to immunize trend-following to endure the negative impact of trend breaks better? A research paper written by Garg, Goulding, Harvey, and Mazzoleni finds a negative relationship between the number of turning points (a month in which slow 12-month and faster 2-month momentum signals differ in their indications to buy or sell) and risk-adjusted performance of a 12-month trend-following strategy. The average number of turning points experienced across assets has increased in recent years. But we can implement a “dynamic” trend-following strategy that adjusts the weight it assigns to slow and fast time-series momentum signals after observing market breaks to recover much of the losses experienced by static-window trend following…
Authors: Garg, Goulding, Harvey, Mazzoleni
Title: Breaking Bad Trends
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
Socially Responsible Investing (also called ESG Factor Investing) grows in popularity. More and more investors enter the stock market not just to invest their savings, but they are also want to support companies that bring positive social or environmental change. ESG factor investing can bring satisfaction to those investors. But does it also brings a real outperformance in a financial sense? Is there some ESG factor alpha? How big is it? These are some of the questions we have decided to investigate – we obtained data, identified ESG factor strategies and tested them. Feel free to explore them with us…