Sunday, January 21, 2018

Who makes a good hedge fund manager? Judgment - the combination of assessment, action, and feedback

Knowledge is the Treasure, but Judgment is the Treasurer of a Wise Man. He that has more knowledge than Judgment, is made for another Man's use more than his own. 
-William Penn

My father used to tell me that brains are like muscles: they can be hired by the hour. It is character and judgment that are not for sale. 
-Antonin Scalia 

Markets are efficient in the sense that it is hard to generate excess returns. Information is readily available and employed so there is an immediate reaction to any new information event. There are very few funds which have to ability to obtain new information, certainly not legally, or create new information. A recent exception has been using news story counts and twitter hits as a source of data, but the number of firms employing these strategies has increased significantly in the last few years.

The quality that separates managers is not data but the judgment on how to use or manipulate data to tell a better forecast story than what is discounted in market prices. A key part of judgment is the assessment and weighing of facts in order to tell a coherent story of what may happen in the future relative to the opinion of others. 

So what makes good forecast judgment? It could be quantitative or discretionary, but it is founded on the interpretation of facts not the gathering of facts. For interpretation, there is a need for a philosophy or view on how the world works. Many can have facts but the assessment of these facts is the value-added skill. 

The assessment or narrative with the facts, however, is not enough. There also needs to be a decision and action. An assessment without action is of no value to the investor. The assessment has to be converted into a decision which one can call a bet and the action of taking the bet and placing it in the market. 

Along with the action, there needs to be a review and feedback. A manager' skill is not just taking the same bet when given a set of facts but learning if the markets have changed and adjusting so the decision process or judgment is improved. 

The triplet of assessment, action, and review is the manager's judgment and the skill for which investors should pay. Hence, the focus or assessment on skill has to be on the judgment value chain.

Best sovereign credit period since the Financial Crisis - What a surprise in growth will do

A year ago the market was concerned about global credit risks. The sovereigns with a negative outlook were high and the number of positive outlooks was low, but that has changed in one year given the improvement in global growth. The number of negative outlooks is at post Financial Crisis lows, the positive outlooks are high and the balanced outlooks are positive for the first time.  The balance has improved markedly across regions but especially in Europe and the Middle East. The chance of default risks has fallen given credit quality is improving.

Nevertheless, the pricing of credit is still tight. The upside potential for spread widening relative to spread tightening is still high, but investors may have to wait for the credit-widening event. With growth strong, risk-on sentiment still high, and credit/liquidity not biting into behavior, there still is a reason to hold credit exposures. Carry-on.

Saturday, January 20, 2018

Complexity Bias and Trend-following -We have a bias towards complexity yet simplicity should be preferred.

Faced with two competing hypotheses, we are likely to choose the most complex one. That’s usually the option with the most assumptions and regressions. As a result, when we need to solve a problem, we may ignore simple solutions — thinking “that will never work” — and instead favor complex ones. Complexity Bias: Why We Prefer Complicated to Simple

Most of the behavior biases that have been used to explain investment decision frictions have focused on the idea that mistakes are made because investors engage in fast thinking. Rules of thumb are employed in order to make decision shortcuts, but simplified decisions lead to mistakes.  

Yet, there is such a thing as complexity bias. With complexity bias, if someone can choose between the simplest answer and the most complex, there may be a bias for something that is more complex. Many have a fascination with stories that seem to have a high-level of complexity. We seem to prefer explanations that are more complex. We often associate complex language with higher level thinking. The idea that we often try to find patterns in random events could be attributed to the idea that we like complexity.

I have reviewed the literature on this bias and am not persuaded on whether this will supplant the classic rules of thumb bias thinking, but I can see how this bias can have an impact on behavior. The richness of our human biases is truly fascinating.

I will, however, use my experience in the trend-following  space to conclude that the complexity bias is alive. There seems to be a bias toward complexity in model building. Investors can have a choice between a manager that has a simple model and one that uses "state-of-the-art"  statistics and requires a Ph.D. and many investors will go for the complex. A manager comes into an office and talks about his use of complex tools for extract unique and special signals and many will be jumping across the table to invest. Another manager in the extreme says, "I don't try to predict, I follow trends and buy what is going up and sell what is falling" and it is a short meeting as you usher him to the elevator. Investor need to focus on why complexity is needed and if a manager cannot explain the need, lean toward the simple. If two managers have similar returns, choose the simple strategy.

Using better techniques to find improved signals is a worthy goal. Difficult problems may require better tools. Nevertheless, there should be a premium on the combination of results and simplicity; no more rules or techniques than what is necessary. The Occam's Razor of model-building should apply; just the right amount of rules to do what is required, just the most direct technique to find a solution.

Bitcoin price moves and networking effects - The difference between social and financial networks is important

Crypto-currencies are in strong market downturn with a 40% decline in the last month and more than 20% in a single day earlier in the week only to be followed by  strong gain of more than 30%. There has been a wide amount of buzz about bitcoins, yet this decline has not really impacted other financial markets. What is clear is that bitcoins are not integrated at this time with other financial markets so there are limited network effects.

It is important to start to think about network effects and  social networking is not the same as networking of financial markets. What separated the Great Financial Crisis was the networking of leverage, financial institutions, and product distribution. When networking of financial markets is high, there will be spill-over effects that impact multiple markets. A bank that is stressed can impact a broad range of financial markets based on their lending arrangements. A shock in one commodity can affect lending and risk-taking across all commodity markets.

A financial shock that is not networked across markets will have limited impact outside of the immediate participants. In the case of crypto-currencies, there are strong social networks with talk on social media, but there is limited leverage and connection to financial institutions. Hence, a bitcoin shock will make news but will not impact the financial wealth process. 

This is important because I believe the "new global macro" thinking is more focused on understanding network effects and how they may affect cross-market price relationships. Understand the networks and you can exploit changes in correlation.