Friday, July 10, 2020

Keeping it simple with downside protection


Rule #1 Don't Lose Money 
Rule #2 Don't Forget Rule #1 
-Warren Buffet 


I was recently reviewing a presentation and having an investment discussion with a hedge fund manager. The strategy was thoughtful and well researched, but the language used to describe it was fairly complex. This complex language cluttered the manager's objective and did not clarify his strategy. The average pension trustee would have a hard time understanding repeating to someone else what the manager would be doing to add value. Simplicity and directness would cut through all of the excess verbiage. At least for an opener, the Buffet Rules serves that purpose.

The Buffet Rules prioritize manager goals and are a good start to expressing simplicity; however, there needs to be some structure on how to implement the "don't lose money" rule. A deeper discussion can be broken into four questions:
1. What is the strategy for preserving money? 
2. What will be the tactics employed for protection?
3. How is downside risk measured?
4. How do you measure the cost of protection?



Any manager should be able to answer these short questions. There can be added complexities with how this is done but first the four questions have to be answered.







Tuesday, July 7, 2020

Regression, "Oh so 20th century"; Machine learning, "Oh so 21st century"


The movement from regression or attribution statistics to prediction algorithms is not just a fad but a significant change in focus associated with how we use information and the purpose of data analysis. Appreciating the change in perspective is important for all investors looking at systematic managers and quantitative analysis.

Regression is the framework of choice for most older quants who were trained in the 20th century. This world focuses on the formulation of what could be called "surface plus noise" with the surface describing the model or scientific truths we wish to learn, and the noise representing what obscures the truth hidden in the model. The emphasis is on model estimation and less on prediction. Develop a good estimated model, find factors, and the prediction will take care of itself.

Pure prediction algorithms are 21st century analysis and  include neural nets, deep learning,  and random forests. These algorithms have moved to the center analysis attention given the increase in computing power and the explosion of large data sets. These are important advancements on existing statistical analysis, but it also is a change in orientation. The pure prediction algorithms focus on prediction with less emphasis on estimation and attribution. Don't worry about the model estimation. There is no focus on significance. It is all about accuracy and error reduction. The connection between prediction and attribution is not relevant.

The table and a deeper discussion are available in "Prediction, Estimation, and Attribution" by Bradley Efron in the 2020 Journal of American Statistical Association

Data analysis cultures are changing. A challenge is for the old guard to learn new tricks and the new culture to appreciate the power of traditional estimation. Right now, the link between these two cultures is stilted and needs to be bridged. Estimation may not work for all data, and the pure prediction culture may need to temper their use of complex algorithms. However, the old guard is going to have to accept the prediction algorithms to be part of the 21st century. 

Monday, July 6, 2020

I want my CTA diversified but not too diversified


"I want my trend-follower diversified to smooth returns, but not too diversified..."

Diversification for trend-followers works at smoothing returns and increasing the Sharpe ratio. Diversification, through increasing the number of markets, increases the set of potential opportunities; however, diversification causes a drag on performance when only a limited number of markets trend. 

Some of the wide dispersion across trend-followers in 2020 is related to the market selection skill of the manager. Managers who traded too many markets, some of which did not see strong trends, may not have performed as well as those that had more concentrated risk. Similarly, focused managers may have missed the best opportunities of the year.

One secret to effective trend-following is the strong benefit from market sectors being correlated.  Global bonds and rates moving together, equity indices trending together, currencies tied to a dollar move, and the energy sector facing a common shock. The full value from trend-following comes when there is a common trend within a sector (allocation breath) or strong trend amplitude. A strong market trend is profitable but there is a limit based on the size of market exposure.

Following the fundamental law of active management, the information ratio = skill * sqrt(breath). A manager has to see an increase the number of bets or an increase is skill. For  any trend-follower, there are three trade buckets: the winners, scratch trades, and losers which are capped by stop-loss. The size and number of winners have to offset the scratch and loser trades.

The winners are associated with identifying the trend and the amplitude of the price move which may be out of their control. Skill or the information coefficient is identified as the correlation between forecasted and actual returns, but this can be restated at the win to loss ratio for trades times the probability of success. This success ratio can be multiplied by the number of trades to obtain the winners. 

Trading more markets allows the trend-followers to find more trends, yet if there the number of trends decline, there will a larger performance drag. Adding markets has to be based on the assumption that the marginal addition will increase the potential number of trends. For example, adding another commodity market with a risk allocation taken from other markets may not add to the return potential of the program. It will add to diversification. 

Investor to ask some simple question of their trend-followers. How do you determine the number of markets traded? Why would you add another market to the program? Would you ever drop markets from the program? Do you rank order and select trades from a broader universe of markets? 

Just as the trend model is critical, the choice and mix of markets for any trend-follower is an important part of the manager skill. Selecting trends and markets and sizing exposures are complex issues that serve to differentiate managers. Finding the right amount of diversification is an important portfolio selection issue.



  

Sunday, July 5, 2020

Biggest long-term threat in 2020 - Deglobalization


Everyone talks about the economic wall of worry, and the wall seems to be getting taller. Pandemic. Recession. Credit issues. Lockdowns. Nevertheless, these worries will pass. They are cycles, shocks, and bumps. They do not define our global system of trade and benefits. Policy-makers can see the immediate harm and are using their set of policy tools to dampen and reverse the negative effects.

Unfortunately, the longer-term worry that will stick with all economies is our trend to cut connectedness, globalization. This worry does not have a set of voices or policy prescriptions to offer as solutions. There are no current advocates against deglobalization, yet trade and the broader term of globalization has been the key generator for world economic growth. 


The free movement of labor, capital, ideas, goods, and services across time and space has created enhanced economics opportunities for most and explosion of a middle class in emerging markets. These flows have driven global growth in spite of the financial excesses and shocks over the last few decades. 

If the current globalization era ends, all economies will suffer, and no localized or national policy will solve the problem. There is a need for worry because globalization is not something that just happens. It is not inevitable. It takes work. Mercantilism is often viewed as a natural policy when countries think trade is a zero-sum game.

History has shown surges in world economic growth when there has been more freedom of global trade and financial flows. The great globalization surges include the pre-WWI period, the Bretton Woods period, and the China-WTO period. All were associated with national and global structures open to international flows, technology that allowed for low flow costs, and organizations that could coordinate economic activity. 

Globalization has been under assault for some time. Some of the arguments against globalization are relevant, should be heard, and require adaptation, but the fundamental premise of globalization is being questioned. This generalized globalization assault is misplaced. Globalization is disruptive and will thus create both winners and losers. The wins will often be dispersed while loses will be focused. Hence, reaffirming the benefits of globalization requires constant reinforcement, yet also requires an appreciation that competitive trade may need localized support for those most disrupted 


Barriers to trade are being erected with tariff growing as a normal tool. Pandemic has restricted travel and the flow of labor. Regulations impeded the flow of capital. The global institutions of cooperation have failed at their mission. New and longer-term geopolitical tensions further erode the desire for cooperation and increased national competition. 

None of these trends toward deglobalization will be reversed without a conscience choice for global integration and cooperation. There needs to be champions for globalization that provide advocacy with candor; however, there first needs to be a recognition that deglobalization is a problem that needs to be solving.