If you think you are smart, you won't listen to others

Victor Ottati of Loyola University of Chicago has done some innovative research on social priming called the Earned Dogmatism Hypothesis. This hypothesis states that social norms dictate that experts will often adapt a dogmatic closed-minded orientation. When experts feel like experts, they are less likely to admit they are wrong or say they do not know something. Experts will act like experts even if they are wrong because they feel expected to have dogmatic opinions. 

He shows that priming people to feel knowledgeable means that they will less likely seek or listen to views of those who disagree with them. Put someone on Bloomberg, give them positive feedback in news articles and trade magazines, and they will start believing their own press. If you are told you are smart, you will start to believe it and act accordingly. Experts may believe they have earned the right to have strong dogmatic opinions. 

How many times have you heard an expert say that he got something wrong? By definition, if the expert becomes self-effacing and admits weakness, he is no longer an expert. 

Why will you listen to others, if you are the smartest person in the room? Why will you admit you are wrong when others have been telling you are good? The ego will not be checked at the door if people are telling you that you are smart. 

Don't follow the talking heads who are likely to be closed-minded. Asking for advice from those perceived to be experts can be perilous without doing your own homework. Your antennae should be raised for portfolio managers who have been lauded by the press and come with glowing press. They can be smart, but are they open to new ideas and will they be willing to adjust their views? 

If you don't listen to experts who should you listen to? The answer is simple, follow the data. Let data speak for itself. That will mean more work, but data are not primed for the Earned Dogmatism Hypothesis.   

Alternative risk premia and the advantage of cluster analysis

The return patterns for alternative risk premia strategies are not the same. The fact that there are risk premia differences is not out of the ordinary and should not be surprising; however, we can learn a lot by grouping the different risk premia to find what strategies can be substitutes and complements. 

Using information from the paper "A Framework for Risk Premia Investing: Anywhere to Hide" by Kari Vatanen and Antti Suhonen, we can find different patterns with the correlations across different risk premia strategies. In the first table, 28 different strategies are bundled into eight style groups. For each of the composites, there is presented an average correlation. The style groups are based on an assessment of style and not any statistical analysis. 

There are interesting commonalities as well as differences across style groups. For example, there is a wide difference between equity trend and the rest of the time series momentum group. The skew for equity trend is negative and the kurtosis is high even though the correlation between constituents is similar. The raw Sharpe ratios are very high for short volatility carry although there is significant negative skew. Clearly, there are significant difference both intra-style and across ARP styles with a lot of potential diversification benefit. 

Nonetheless, a very different perspective is gained from conducting a cluster analysis of the different styles. Cluster approach is sensitive to the data used and the methods employed, but this analysis shows that the groupings of style is not the same as what occurs when it is done through some naming convention. For example, credit carry and curve are more closely tied with equity size than with bond styles. FX carry is more closely related with short volatility carry. This grouping makes sense because FX carry is known to be volatility sensitive, but it is not something that will jump out at the investor who just looks at correlation across style names. 

The dendrogram developed in this paper also links some strategies together that make sense, albeit the similarity may not be immediately apparent. For example, trend is tied to equity defensive strategies and then to commodities and bonds. Credit is related to carry and then to value. 

There are two major groupings that could be called defensive risk-off and offensive risk-on strategies. Offensive will be focused on credit, carry, and value while defensive strategies are focused on trend, rates, commodities, and equity defensive. The clusters provide a nice simple framework for strategy classification. 

Given this deep knowledge on strategy differences, portfolios can be constructed that have a tilt to either defensive or offensive risk profiles. If there is a desire to minimize the strategies employed, cluster thinking can help with reducing duplication across strategies. Diversification analysis can be more nuanced than just looking at a correlation table. The value with ARP strategies is that focused mix and matching can be done in ways that are not available through hedge funds.

Smart people may have a bias blind spot

"I am fine as an investor analyst. The problem is with all the other analysts who are irrational! That is why I'm not making money." 

Many have a bias blind spot and believe that thinking biases exist with other people and not themselves. We have often heard the comments with respect to investing. The market is behaving irrationally. Those other investors are making mistakes not me. Those other investors have behavior biases but not me.

Actually, the bias blind spot exists there are extensive tests that provide strong evidence for a bias blind spot. Keith Stanovich along with two other researchers extensively tested individuals for the bias blind spot in their paper, "Cognitive Sophistication Does not Attenuate the Bias Blind Spot". Most find fault with others not themselves. What is surprising is that those who have higher SAT scores also have a slightly larger "bias blind spot". Smart people are not biased because they are smarter and make fewer cognitive mistakes. "Adults with more cognitive ability are aware of their intellectual status and expect to outperform others on most cognitive tasks", yet that is not present in the data. 

It's not me, it's them. Smart people should be able acknowledge a bias blind spot and adjust to it. That is not the case. They may be a desire to focus on the failure of others and not themselves when it comes to biases. They can lead to significant failure when playing a trading where you are competing against others for alpha.

Trend-following - Go deep or go wide - There is a balance on the number of markets traded

There are two key choices for building managed futures trend-following portfolios - going deep or wide with diversification. There are clear trade-offs with this choice. For 2019, the focused financial trend-followers, in general, did better than those that followed a strong diversification strategy. That strategy may not work in 2020. 

The go-wide diversification strategy - Trade as many market as possible. The investor gets the maximum amount of diversification and exposure to less liquid alternative commodity markets which often have a stronger tendency to see larger price moves than the more liquid markets. The portfolio cost is that there can be over diversification and higher transaction costs.

The go-deep diversification strategy - Trade only the most liquid markets which will allow for lower transaction costs but also has greater sector concentration. Bonds markets across the curve and across countries have high correlation. Global stock index markets are also highly correlated. The most liquid contracts are focused in the global equity index and bond markets. The cost of trading these markets is low based on the tight bid-ask spreads. 

Is one better portfolio strategy than the other? Simple theory may suggest that more diversification, that is more markets, should be better, but diversification is also a question of determining the marginal contribution of the next market added. If the additional markets are all highly correlated, adding more will not improve efficiency and just add complexity and costs. 

The other key portfolio question is whether there is a return advantage from adding less liquid commodity markets that will more than offset costs and complexity. There is some clear evidence that these small markets will add value. See "Trend's Not Dead (It's just moved to a trendier neighbourhood)" by the folks from Gresham Investment Management.

In their short paper, Gresham finds that autocorrelation terms (the sum of autocorrelations) of alternative commodity markets, (less liquid markets), are higher than that of liquid markets. There have also been more large moves with alternative markets relative to liquid markets. Finally, the chance of a large move has been greater for alternative commodity markets in the post Financial Crisis period relative to liquid markets that have seen a decrease in the number of large moves.

Unfortunately, as a trend-following firm gets more successful and larger, the size that can be traded in these small markets gets smaller. Large firms use the "go-deep" strategy because the "go-wide" is not available as an alternative. Still, a smaller firm that employs a "go-wide" strategy needs to have the technology and systems to manage the greater number of markets traded. 

Of course, the type of trading strategy will matter. A strategy that trades all markets with either long or short signals will suffer from dilution from trading more markets. A cross-sectional approach that trades only the best long and short trends will have an advantage of limited dilution but will still face liquidity issues. A portfolio construction technique that allocates a percentage of total exposure to each asset class can offset liquidity issues and concerns about marginal improvement from adding markets. 

The type of signals, the form of diversification, and the set of markets traded are all inter-related. These questions can be partially answered through a deeper quantitative analysis of specific choice. We wanted to call attention to key portfolio trade-off that needs to be explored.