"Execution is god!" - So the focus should be on process

Perhaps the comment by Andy Grove, the driver behind Intel, is extreme even from the man who said, "Only the paranoid survive." However,  a focus on process or strategy execution is critical for good money management. It is often overlooked by managers and investors making fund investments.  You have to sweat the details.

By strategy execution, I mean the implementation of the investment approach to generate returns. Due diligence focuses on knowing strategy and reviewing operations, but does not often know how to frame questions on process engineering, or the work taking the strategy and generating a repeatable set of steps that will lead to success.

Good execution is usually just classified as good performance. If there are two managers who follow the same strategy, the one who has high returns must be executing their ideas better. That does not really account for strategy execution. Unfortunately, there are no standards for execution. Operational due diligence will ask about back office, compliance, and IT, but may not spend a long time on the step-by-step process of how ideas or trades are generated and then added to the portfolio. The combination of research, strategy, trading, back office, and IT are not linked as an execution process.

The devil is always in the details for execution. The analogy I often use is from cooking. There is a big difference in the end result of a prepared meal between two chefs even if they are following the same recipe and have the same ingredients. That difference is execution.

So how is strategy execution measured for a money management firm? Good execution may be measured through four parts:

• Defined steps - Good execution occurs when there is no "hand-waving" Every step in the investment process is defined and can be described by those who engage in the process. This can be as simple as the data collection and scrubbing process to how reports are generated. Execution is about effective trading to get the ideas in the portfolio. The investment process may identify trades and size them correctly, but the trades have to be made in an effective manner. If you can measure it, you can manage it. If you cannot, then execution will be sloppy.
• Exception analysis and preparation - If there is a process in place for handling normal activities, exceptions can be dealt with easily. Good execution can deal with those situations which are abnormal and can lead to significant errors. Good execution can handle exceptions.
• Performance review - Execution can run smoothly if there is a review of performance so attribution and contribution of returns can be measured. Contribution is measuring what made money and attribution is how the money was made. Both are critical for good execution.
• Feedback loop -  There has to be a clear process for learning. Learning requires feedback from information to change. If information is collected but does lead to change, there is no learning. The question should be clear, "How do you learn?"

The value of sitting with a manager for a day is that the execution of the strategy can be analyzed in real time. It is not enough to hear that a manager has a value focus. You have to watch and discuss how value is discovered and then converted to dollar exposures and placed within the portfolio. How this position is discussed and reviewed once it is established tells you how performance feedback is given. This discussion is deep and digs at what are the root causes for a gain or loss.

Andy Grove had execution intensity with Intel and it showed in the results. His type of intensity is required for success in the competitive money management industry. 

Portfolio concentration works - those who concentrate are rewarded

Diversification is called the only free lunch in finance. Any investor is constantly reminded that diversification is the one thing you should always do, but what is the evidence that diversification works against an alternative? The alternative would be to concentrate, have a less diversified portfolio. Well, now we have some evidence across a broad set of investors.

A recent study looked at 10,771 institutional investors from 72 different countries to determine whether concentration leads to abnormal returns. See "Portfolio Concentration and Performance of Institutional Investors Worldwide". This is an interesting study that takes a novel approach to seeing if concentration by home country, foreign country, or industry will lead to abnormal returns versus a diversified portfolio. The devil is in the details of how these concentration measures are constructed, but the authors provide some good food for thought. The results are clear - concentration will lead to higher returns. 

Of course, this does not mean that everyone should go out and buy a concentrated portfolio. Concentration is a function of having a perceived information advantage. If you have skill or learn in one area, it is likely that you will be able to generate abnormal returns. Those who specialize in local markets may have an information advantage over others. This information advantage will cause concentrations which manifest in abnormal return. Concentration is driven by perceived advantage, but all concentration does not mean an advantage exists. This study, however, shows abnormal returns are present for a broad group of institutional investors.

This work does tell us is that diversification may not be a completely free lunch. There is some cost because there is the opportunity for higher returns from not concentrating.  Find good managers and allow for concentration.

Granularity, predictions, and accuracy - Do you have a scale?

Ask for precision and you get better forecasts - even in an uncertain world. Greater granularity with predictions leads to better thinking. Judgments made on a seven point scale will be better than a five  point scale. Asking for likelihood is better than just asking opinions. Research has found that when forecasters are forced to provide more granularity on their point of view, they will do a better job. (See Superforecasting by Tetlock and Gardner.)

It is always important to get the direction right. One extreme would be trend-followers who focus on direction and not the degree of a price move. However, you should demand more from analysts to better the forecasting process. If given the opportunity, do not let analysts off on ambiguous or imprecise forecasts. If an analyst says bond market yields are going higher, then force a number and level of precision with the forecast. Asking for details will mean more work, but a better forecast in the end. Of course, this does not have to be taken to extremes.

For example, here is a simple scale.

The National Intelligence Council uses either a five or seven point scale for judgements.

The five point scale:
REMOTE - UNLIKELY  - EVEN CHANCE  - PROBABLY, LIKELY  - ALMOST CERTAIN 

The seven point scale:
REMOTE - VERY UNLIKELY  - UNLIKELY  - EVEN CHANCE - LIKELY - VERY LIKELY -ALMOST CERTAIN 


Just by asking for a more refined scale will require more thinking and a better piece of work. So the next time you hear someone say the market is going higher, ask him to give some probability estimate or likelihood to that comment.

Superforecasters - what does it take to be great?

If there is one new book to read for investment management, Superforecasting: The Art and Science of Prediction by Philip Tetlock and Dan Gardner is the one. They never mention investment management or finance, but the insights from their work on "superforecasters" is extremely useful and will help anyone who has to make predictions for a living. Professor Tetlock has had one of the more interesting research careers with a focus on how well forecasters actually perform with real questions of high uncertainty. His conclusion in earlier work is that most are poor forecasters. 

The current book talks about a long term project which uses volunteers to make tournament forecasts on a wide range of topics. It was part of a large government project to see if superforecasters could be found, analyzed, and natured. It is a deep work that has been ongoing for years, but tells us that good forecasting can be made and the characteristics of the forecasters can be measured. Unfortunately, the number of great forecasters is small. The good news is that forecaster who work at can get better and there are a set of characteristics for those who are good.

The heart of the work is finding and analyzing those individuals who have good skills. The authors were able to identify these key skills for forecasting through grouping those who have done well in the tournaments. Some of these skills may be very intuitive yet the combination across four major areas tells us what we should be looking for in forecasters. 

Good forecasters have these skills or traits:

Philosophical outlook - They have an overall philosophical outlook to the problem of forecasting.

• Cautious  - The good forecasters are cautious and not quick to reach conclusions. They realize that nothing is certain.
• Humble  - They are humble and understand that they are likely to fail and that they do have limitations. The world is complex and hard to know.
• Non-deterministic - The forecasters have a strong sense that events may not be easily understood through simple cause and effect. Things happen.

Abilities and thinking styles - There is a specific style of thinking that makes for better forecasting.

• Actively open-minded - Everything should be tested. There are no strongly held beliefs.
• Intelligent and knowledgeable -The good forecasters are naturally curious.
• Reflective -The good forecasters are their own worst critics. They will second guess and challenge themselves. 
• Numerate -They may not be quants, but they are comfortable with numbers.

Methods of forecasting - Good forecasters follow a structure for making their bets.

• Pragmatic -They are not ideologues and not wedded to an agenda or view.
• Analytical -They can hold and measure other points of view.
• Dragon-eyed -They have the ability to take other views and synthesize to a new perspective.
• Probabilistic -They can think in terms of odds or degrees of maybe.
• Thoughtful updaters  - When provided new evidence and data, they will change their view.
• Good intuitive psychologists -Good forecasters can check for biases and discount emotional point of view.

Work Ethic -

• A growth mindset - Good forecasters believe that hard work will make hem better forecasters.
• Grit - There is a determination to seek the truth and the answer to problems.

Superforecasting is easy to read but filled with useful information. It takes complex issues and make them easy to understand and show that great forecasting is not innate but can be learned and developed like other skills.