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

Nearly two months ago, in a time of the highest turmoil during the current pandemic crisis, we performed a quick assessment of the status of performance of equity factor strategies. The world has still not been able to ward-off health-care crisis completely, but a lot of countries have made significant progress (on the other hand, there are still a lot of countries in a worse state than a few months ago). Equity indexes have rebounded from the March lows and have removed some of the losses. Therefore, we have received multiple inquiries about the current situation of equity factor strategies.

So it may be a good time to revisit once again how they are performing.

Financial markets are full of pricing anomalies, and their existence is often explained by human behavior. Behavioral finance postulates that cognitive irrationality is manifested in biases like the disposition effect (the tendency of people to sell assets that have increased in value, but keeping assets that have dropped in value in portfolio) or overconfidence bias (the tendency of people to be more confident in their own abilities). There are some papers which directly link investment decision making caused by these biases to actual physiology of investors (for example, a known impact of testosterone on investment performance). A new research paper written by Nofsinger, Patterson, and Shank examines not only testosterone but also cortisol levels of testing subjects and then compares their performance in a mock investment contest. Both hormones are strongly related to higher portfolio turnover and inability to accept losses, with cortisol levels even more significant than testosterone.

Author: Nofsinger, Patterson, Shank

Title: On the Physiology of Investment Biases: The Role of Cortisol and Testosterone

In many academic fields like physics, chemistry or natural sciences in general, laws do not change. While economics and theory of investing try to find rules that would be true and always applicable, it is not that simple, there is a “complication“ – human. Psychology of humans is very complex. In the one hand, it creates anomalies in the market, that academics study and practitioners use. On the other hand, after an anomaly is discovered, often, the strategy becomes less profitable.

While for academics, it is just another research question, investors may be worried that the anomaly is arbitraged away, and it will become unprofitable in their portfolios. In this article, we will look deeper on whether the anomaly can be arbitraged away, if the profits are lower for the specific strategy once the strategy becomes well-known, and even if the strategies can be timed. Quantpedia‘s readers are often interested in these common topics, and we will try to shed some light on them.

Mirror, mirror on the wall, what’s the best factor model of them all? We at Quantpedia are probably not the only one asking this question. A lot of competing factor models are described in the academic literature and used in practice. That’s the reason why we consider a new research paper written by Matthias Hanauer really valuable. He compared several commonly employed factor models across non-U.S. developed and emerging market countries and answered the question from the beginning of this paragraph. Which model seems the winner? The six-factor model proposed in Barillas et al. (2019) that substitutes the classic value factor in the Fama and French (2018) six-factor model for a monthly updated value factor …

Authors: Hanauer

Title: A Comparison of Global Factor Models