Our society teaches us, that it is good to be different. That our trading strategy must be always unique, creative and individualistic. It is boring and unprofitable to be the “average”, to do what the others do. And then, there is a research paper written by Bollen, Hutchinson and O’Brian which offers the opposite view. Their analysis explains there exist one hedge fund style where everything is the other way round – trend-following CTAs funds. Their interesting (but for some maybe controversial) paper shows that CTAs with returns that correlate more strongly with those of peers have higher performance. It appears that CTA strategy conformity is a signal of managerial skill. Now, that is an eccentric idea 🙂

Authors: Bollen, Hutchinson and O’Brian

Title: When It Pays to Follow the Crowd: Strategy Conformity and CTA Performance

The end of the year is a good time for a short recapitulation. Apart from other things we do (which we will summarize in our next blog in a few days), we have published around 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to summarize 10 of them, which were the most popular (based on Google Analytics tool). Maybe you will be able to find something you have not read yet …

Professor Roger Ibbotson is one of the most respected and influential researchers of the current era. His book “Stocks, Bonds, Bills, and Inflation” is a classic and often serves as a reference for information about capital market returns. Therefore we always pay attention to his publications. His actual work, “Popularity – A Bridge between Classical and Behavioral Finance”, which is written with Thomas M. Idzorek, Paul D. Kaplan, and James X. Xiong, is now available on SSRN.

In their work, authors explain the term “Popularity” from an asset pricing point and show how “Popularity” can be a broad umbrella under which nearly all market premiums and anomalies (including the traditional value and small-cap) can fall. They develop a formal asset pricing model that incorporates the central idea of “Popularity”, which they call the “popularity asset pricing model” (PAPM). Based on this model, they predict characteristics as a company’s brand, reputation, and perceived competitive advantage to be new equity factors.

It’s a long read, but we at Quantpedia really recommended it for all equity portfolio managers …

Authors: Ibbotson, Idzorek, Kaplan, Xiong

Title: Popularity: A Bridge between Classical and Behavioral Finance

Everyone who lived during the 2007 and 2009 crisis knows what the biggest weakness of the equity momentum strategy was. It was right during the spring of 2009 when the financial markets were on its inflection point when the momentum strategy crashed. Right after that inflection point, stocks which were the biggest losers during the previous year performed exceptionally well and caused strong under-performance of classical long-short momentum strategy. How can we prevent this situation from happening again? That’s the topic of our favorite new recent study written by Matthias Hanauer and Steffen Windmueller. They analyze three momentum risk management techniques – idiosyncratic momentum, constant volatility-scaling, and dynamic scaling, to find the remedy for momentum crashes. It’s our recommended read for this week for equity long-short managers …

Authors: Matthias Hanauer and Steffen Windmueller

Title: Enhanced Momentum Strategies

Financial academics have described so many equity factors that the whole universe of them is sometimes called “factor zoo”. Therefore, it is no surprise that there is a quest within an academic community to bring some order into this chaos. An interesting research paper written by Favilukis and Zhang suggests explaining a lot of equity factors with momentum anomaly. They show that very often, up to 50% of the equity factor returns can be linked to returns of momentum strategy. This link is especially prevalent in short legs of equity factors.

Authors: Favilukis, Zhang

Title: One Anomaly to Explain Them All

No doubt, the correct datasets are the key when one does some analysis in the financial markets. Nowadays, futures contracts are widely spread and popular among practitioners. However, each delivery month is connected with a different price where the price of the underlying asset should stand at a given date in the future (the expiration date). The industry standard for backtesting futures strategies is to construct one data sequence from a stream of contracts. Our short article shows the importance of choosing the correct methodology for building continuous futures contracts data series…