Saturday, June 23, 2018

Tobin's separation theorem - It can be applied anywhere


One of the greater principles of investment finance is Tobin's separation theorem which is a powerful simple tool that can be used for any investment portfolio, but is especially useful when thinking about managed futures and alternative risk premiums. (Robin Powell reminded me of Tobin’s contribution in his essay, Can you really stomach the risk you’re taking?) There is a tremendous amount of useful investment advise through just applying the simplest of concepts. 


Tobin's Separation Theorem is elegant in its simplicity. Find the risky portfolio that maximizes the return to risk and then form a new portfolio that combines this risky portfolio with cash or leverage to find the level of risk that will make you comfortable. The new portfolio, set to the volatility you want, will be on the tangent line for the max return to risk. The new portfolio will be a combination of the risky portfolio and cash if you want less volatility. Similarly, the risky portfolio can be levered to a higher level of volatility. 

The Tobin Separation theorem is especially useful for thinking about managed futures portfolios or alternative risk premiums using total return swaps. Because both use margin at a low level, the risky portfolio can be set at any level desired by the investors through notional funding. 

For example, in managed futures, if the manager sets his base portfolio at a volatility target of 10%, the investor could fund a separate account for say $10 mm and set the notional exposure at twice the cash level or $20mm of notional exposure for 20% volatility on the $10 mm investment. The investor achieves the higher risk at the same return to risk trade-off. Managed futures managers understand the separation concept very well through their setting of volatility for their funds.

In the case of alternative risk premiums (ARPs), there may be a set of strategies that generate an information ratio of 2 but only has volatility of 2% and a return of 4%; however, a pension fund may have a discount rate of 7%. The ARPs may be a great investment but at a return of 4%, it will be significantly less than the expected return needed for the pension. The ARPs better be good diversifiers or there will be a return shortfall. In this case, the separation theorem tells us that we can view this as the risky portfolio that can be levered to a higher volatility that will be closer to the discount rate. Low volatility combinations of risk premiums can be levered through notional funding to a risk level more consistent with the desire of the investor.

Similarly, if an investor starts with a portfolio that has a beta of one but would like lower market exposure, it is easy to just reduce the beta exposure with an increase in cash to the level desired. It can be done through cash and the risky asset without resorting to greater complexity.

Find the best return to risk portfolio and then adjust to the volatility desired. If this can be done with investments which do not need to borrow such as swaps and futures, all the better. This approach is both elegant and simple. 

Friday, June 22, 2018

Commodity returns over the long-run - A good diversifier, so get back in with an asset allocation


Commodity index investing has not been very successful for investors as measured by leading index total returns since the Great Financial Crisis. The end of the super-cycle has been tough on most investors and only recently has there been a period of extended positive returns based on the rise in oil prices. Is there any relief for investors?

A look at long-term returns for commodity futures suggests that this period is not representative of what may happen in long run; however, long periods of negative performance are not unusual. The recent paper, "Commodities in the Long  Run", published in the Financial Analysts Journal studies commodities since almost the beginning of the Chicago Board of Trade, a period of 140 years. It finds that commodity futures indices have been significantly positive over the large time period, albeit with high volatility.

The work also shows that the key driver of commodity futures returns are the interest rate adjusted carry and not the spot price. Backwadation and contango do matter and this carry effect is different than the movement in short-term interest rates. Backwardation is a strong positive condition for commodity returns. Additionally, performance will differ on the macroeconomic conditions with high inflation and growth being two states that positively impact return performance. Notably, in an inflation up and expansion period commodity returns are positive regardless of the backwardation or contango.

Commodities will add value as a diversifier to a portfolio especially during certain economic states like higher inflation. Given the low correlation to stocks and bonds, volatility will be lowered with even a small allocation to commodities and there will be an increase in Sharpe ratio. The benefits from commodities can be achieved either through a long position or a long-short position through backwardation and contango.

Our view is that commodities should be incorporated as a core allocation for a well-diversified portfolio but this allocation should be dynamic. Periods of sharp economic downturn should call for lower allocations or exposure through long-short carry positions. More importantly, asset allocation decisions should not be skewed by the recent post financial crisis return performance but should be based on a longer-term view consistent with the data.

Thursday, June 21, 2018

Decision noise reduction - This is the one thing investment managers should get right


"There's a lot of noise when making a decision. Not in the decision itself, but in the making of the decision. It is possible that an algorithm, and even an unsophisticated algorithm, will do better because the main characteristic of algorithms is they're noise-free. You give them the same problem twice, you get the same result. People don't." 

- Daniel Kahneman keynote at the Morningstar Investment Conference in Chicago 2018



What is the one thing that investors want from a manager? Consistency in performance. There is value in the "smoothness" of returns. Smoothness is not the same as volatility. A manager can be volatile but still be consistent in that it applies the same reasoning to the same set of facts or market conditions. The smoothness comes from the fact that returns will match a set of factors that can describe the investment decision process.

Decision consistency or decision noise reduction is important across all professions. We want a radiologist to reach the same diagnosis for the same x-ray. We want a judge to rule in the same way for a similar crime. And, we want a money manager to behave the same when faced with the same economic conditions. 

Return consistency is achieved through the same application of decision-making. Having the same process for decisions should reduce performance noise in that the performance pattern will be similar given the same set of price behavior. It will not ensure protection from loses, but consistency may allow for longer-term success. Of course, if the wrong process is applied consistently, there will be a problem.

Of course, some will say all decisions are situational and cannot be placed into a neat framework. No situation is exactly the same, but we believe the odds are more favorable when a disciplined approach is applied. Consistency should be a fundamental issue for discussion during a due diligence.

Wednesday, June 20, 2018

The "Hedgehog and the Fox" revisited - Find managers with big ideas, but diversify





The Greek poet Archilochus wrote, "The fox knows many things, but the hedgehog knows one big thing."

The Oxford philosopher Isaiah Berlin used the fable of the hedgehog and fox as a metaphor for the writing of Leo Tolstoy in War and Peace. In "The Hedgehog and the Fox”. Berlin used the fable as a way to describe thinkers and writers. There are two types, those who define the world through a single idea versus those that have a variety of experiences and cannot be defined by a single idea but by many. Some writers are hedgehogs while others are like foxes. In the case of Tolstoy, he thought like fox and wrote about many ideas but desired to have one big idea. He could not be classified as a hedgehog or fox and this was a source of conflict, a "fox by nature but a hedgehog by conviction".  

Since the writing of Berlin in the 1950’s, the hedgehog and fox analogy has gone from a description of thinking to a more negative view on forecasting. Phil Tetlock used the fable to describe types of forecasters. The fox uses many sources of information and thinking to develop a prediction versus the hedgehog who has only a single idea that is less effective at explaining a dynamic or uncertain future.

We think that the original idea of Berlin coupled with the thinking of Tetlock is a useful for describing the thinking of hedge fund managers. There are those that have a single big idea or philosophy for how the investment world may work. The hedgehog could be the systematic trend-follower, the value manager, or the short specialist. The fox is the manager who is the diversifier. He does not have a guiding or unifying philosophy but rather is willing to combine different ideas to find the best strategy or idea to implement. There is no philosophy other than to use what works.

We respect the hedgehog that has the one big idea or can articulate the well-defined strategy but we also realize that a fox may protect us from the failure of the big idea through its flexibility. A key choice of the investor is to either find the fox manager or diversify across a set of hedgehogs. In either case, the single big idea can be costly, so there is value with running with the foxes of Tetlock or bundle a set of big ideas to stay diversified. Big ideas are critical, but it is important to have more than one of them in an uncertain world.

Wednesday, June 13, 2018

Go back to basics with the efficient market hypothesis – Think of it as a base or prior


The Efficient Market Hypothesis… has two components that I like to refer to with the terms No Free Lunch and The Price Is Right. The No Free Lunch component says that it is impossible to predict future stock prices and earn excess returns except by bearing more risk. The Price Is Right component says that asset prices are equal to their “intrinsic value,” somehow defined. 


Times have changed. Bashing the efficient market hypothesis has become a pastime within the academic and hedge fund communities. What was once a foundational principle in finance has been has been cut down to size by behavioral finance. In the marketplace, the premise of all hedge fund investing is that markets are inefficient and can be exploited by a manager's unique skill and edge. 

Nevertheless, the efficient markets hypothesis (EMH) should still be a starting point for any discussion about market behavior or the ability of managers to make money. The EMH should be an investor's base case or prior from which he look for exceptions or alternatives.    Start with the premise that there is no skill or edge and ask to be proved otherwise.

Richard Thaler does a nice job of providing a simple updated definition of EMH and how his thinking fits within this hypothesis in his Noble Prize lecture in 2017. For his two-part definition, the "no free lunch" component is simple. In a competitive market with no barriers to entry, it is hard to earn excess returns.  Any better "mousetrap" for finding profits will not be able to last before the market takes away the edge. Normal profits are zero beyond the return for bearing risk. Anyone who looks at the structure of markets should believe there are a lot of smart people trying to gain an edge and it is not easy. Information processing is very quick, so prices respond immediately to new information. The second part states that prices represent true value. All that competition is able to generate the intrinsic price. Prices have to equal intrinsic value otherwise excess returns can be exploited. Markets are able to process information efficiently. His career work finds that there are exceptions to these rules.

While this is a good working prior, it does not mean that markets are efficient at all times and prices will also equal intrinsic value. There can be free lunches and deviations from intrinsic value because of the limits of arbitrage and from behavior that does not process information effectively and makes errors in judgment. 

Our ability to define intrinsic value is compromised because the concept of value is hard to measure. There are simple example where investors are not able to do simple math for finding relative value and deeper example where value is just elusive.  Similarly, our behavior may generate consistent mistakes which can be exploited. There may exist an ebb and flow between true rationality and actual behavior. Markets will move away from intrinsic value only to return after being stretched to an extreme.

So how should an investor behave given this changing concept of efficiency?


  • Accept that markets are competitive, so an edge is hard to find.
  • It is difficult to generate excess returns after accounting for risk.
  • Accept that any manager skill like an edge is rare.  
  • If there is skill or edge, it may not last. 
  • Use the EMH as a prior or base case, but accept that anomalies can exist. However, these exceptions may only be identifiable ex post.
  • Behavioral biases exist which can generate repeatable opportunities. Competition may not drive out all of the investors who have biases and the biases that dominate may change over time.
  • Price will deviate from intrinsic value because there are limits to arbitrage. 
  • There will be noise around intrinsic value 
  • Prices may deviate from intrinsic value because there is not always agreement on value or beliefs. Price are weighting of opinions. 
  • Price deviations from intrinsic value may not last, but any closure of deviation may not be immediate.
The efficient market hypothesis may be out of fashion and has been proven not to hold as tightly as believed. Thaler and others have proved that market behavior is more complex than described by EMH, but the EMH should still be a good foundational guide for what can possibly be achieved through active management.  












Tuesday, June 12, 2018

Risk preferences are not stable - The major take-aways

An important problem in finance is trying to properly incorporate risk preferences when forming portfolios. This is especially true if risk preferences are not stable. Yet, we have increasing evidence that risk preferences do change over time. (See article "Are risk preferences stable?" by Hannah Schildberg-Horisch in the Journal of Economic Perspectives Spring 2018 and illustration below.)

First, individuals become more risk averse as they age. Older investors become more cautious and conservative. Second, there is an increase in risk aversion during an economic crisis or downturn. Risk aversion is countercyclical which can explain why the equity risk premium is higher in recessions. This can also explain why investors who lived through economic crises, like a depression, act more conservative than investors in the same age category who did not experience a depression. Third, stress, fear and cognitive load will elevate temporarily risk aversion. 

Risk aversion may not be stable through time, but it may be stable when measured by traits which is consistent with how psychology looks at risk aversion.

This idea of changing risk preferences can be very useful at explaining both investor and manager behavior. The change in risk aversion as we age is consistent with the target date products that become more conservative through time. The risk aversion from economic crisis suggests that many avoid holding risk portfolios at times when upset is best. The fear factor suggests that portfolios will become more conservative during stress. The impact of risk aversion on investors seems acceptable to our understanding of market behavior, but we should also accept that risk aversion impacts manager behavior.

Managers are likely to become more risk averse as they age. The gunslinger of yesterday will become more conservative with his grey hair. Managers are not immune to a crisis will become more conservative during a recession. Managers will increase their risk aversion when there is more stress. 

Given this time-varying pattern, there is a good reason to hold systematic strategies that will not show changing risk aversion. Disciplined rules-based approach can eliminate this behavior in managers. 

Monday, June 11, 2018

The power law and hedge funds - Power law in size may not equal power law in returns


The four biggest hedge fund launches of 2018 have attracted more than $17bn, according to figures compiled by the FT. That compares with the $13.7bn investors have put in existing funds, according to data from eVestment.  from FT 
Hedge fund stars rake in billions for new funds



Many may know the 80/20 rule-of-thumb for economics, the Pareto Principle. In businesses, 80% of the profits are generated from 20% of the customers. The power law is everywhere and the hedge fund industry is no different. A few firms hold a majority of the money.   The performance of managers is often positively skewed because poor performer close. Most firms fail.


Most new money goes to a few firms, as is the case in 2018. Behaviorally, investors want to be with smart money which is naturally supposed to be with new big start-ups. Money flows create a herding effect, which perpetuate the power law.

However, data on performance suggest that small firms do better than large firms. The power law with size or launches may not match the fat tails or power law in performance. This shows the complexity or non-linearity within the hedge fund industry. Following the flow or size crowd will not lead to riches in return. A power law in one dimension, size, does not strongly correlated with another dimension, return

Nevertheless, the dynamic nature of the hedge fund industry means there are constant launches and liquidations so that picking hedge funds is like venture capital investing.  A few winners are offset by a larger number of losers. A key process for due diligence and investing is finding the potential size/return trade-off maximum. Using managers that are too small, while potentially generating higher returns, may increase the exposure to firm failure. Using managers that are too large may reduce firm risk but may place a drag on performance. The power law in size may not signal quality.

Wednesday, June 6, 2018

Hedge fund performance - Not providing the investor benefits expected


Hedge fund indices, in general, showed positive albeit muted gains for the month. The biggest losers were EM and systematic CTAs on the sell-off in emerging market stocks and bonds and the large bond reversal. The largest gainer was fundamental growth which was consistent with growth indices. 

Hedge fund performance for the first five months of the year is tilted to the negative with event, distressed, and special situations underperforming. The largest winners are the relative value and multi-strategy indices. 

Investors should be underwhelmed with average hedge fund behavior this year. Volatility spikes, some country specific risks, and some choppy markets conditions served not as trading opportunities but as drags on performance. Some of these events could be viewed as true surprises, but the benefit from holding hedge funds has been limited for the year even though the markets have not been directional.

Tuesday, June 5, 2018

What affects my sleep this week - DB, Brazil, and CMBS

Historian Deirdre McCloskey says, “For reasons I have never understood, people like to hear that the world is going to hell.”
John Stuart Mill wrote in the 1840s: “I have observed that not the man who hopes when others despair, but the man who despairs when others hope, is admired by a large class of persons as a sage.” from Morgan Housel "The Psychology of Money"

Yet, here I am talking about what may cause me to lose sleep. Am I falling into the same trap described in the quotes above? Yes, but I would like to believe that focusing on the possible extremes or dangers help protection wealth. The cost of complacency is high. A lose of principal requires more future return to reach breakeven. This is the drag of volatility. 

This week here are three issues of concern. One, Deutsche Bank. The decline in a global bank has systemic risks which are hard to unravel. Reduction in lending for one bank cannot be immediately replaced with another bank. Governments do get involved, and financial plumbing is important. Second, the Brazil turmoil is can lead to unintended future policy consequences with a election coming up. Forecasts have actually increased growth for 2018 to 2.0% from 1.6%, but the strike impact looks to be more far-reaching. It should cause concern for any EM investing. Third, the quality of loan portfolios in CMBS should be a concern. Interest only loans never are a good sign of quality.

Nevertheless, good macro data in the US lifts the global boat. With employment still improving, it is harder to bring any localized negative concerns forward in time as global issues 

Monday, June 4, 2018

Trends dominated by bond reversal but not clear the shock rally will continue

I have always thought that the simple physics analogy that a market at rest will stay at rest and a market in motion will stay in motion is apt for trend-following. Trends will change when there is a shock or catalyst that will change the underlying fundamentals. Trend-following does not require knowing all of the reasons for why a trend is happening or why it may stop. Trend-following only requires that a signal is extracted and followed until price dynamics tell you otherwise. The success with trend-following is driven by the fact that trends last longer than expected. They last longer because most new information is trend reinforcing. Fundamentals do not generally change quickly. Nevertheless, loses will occur when new information causes an expectations reversal. Expectations may change more frequently than fundamentals. 

Bond markets faced a large reversal from their rising rate trend when markets switched to risk-off over the forming of the new government in Italy. EU exit risk is back. This causes revisions in equity, bond, and rate trends. The shocks were strong, but it is not clear whether this change in sentiment will be reinforced by additional new information. Political risk is hard to handicap and even harder to exploit as a trend-follower. 

While we have seen trends change in a number of sectors, currencies and energy sectors have continued to follow existing market price action. Our view of sector trend behavior is that June will offer good return opportunities albeit the size of the gains may be muted. 

Managed futures hurt by bond reversals - Surprises shock major trend-followers

Managed futures performance for May was driven by one sector, global bonds. The surprise events in Italian politics led to a flight to quality move into safe bonds around the world. This sharp reversal caught most short trend-follower flat-footed. The commitment of traders reports have shown a strong short tilt in managed money. The size of the move over less than 10 trading days ensured stops would be hit and positions changed. The question was just how much pain managers took in this sector. Notably, the markets sold-off on the good economic employments numbers to further hurt managers who switched to longs earlier in the week. A similar set of events followed the rates markets. Expectations for fewer Fed hikes given the political turmoil only reversed again after the US employment number.

Stock index performance was mixed on shallow trends or reversals in stock markets. Trading increased in difficultly with a spike in market volatility. Nevertheless, a bright spot for many traders were continued sell-off in many currencies. The dollar rally has continued with well-developed trends. Energy markets moved higher, yet there has been an increase in volatility based on discussion of production increases. Gold has sold-off like currencies; however, there were more limited opportunities in base metals. Commodity markets were mixed with grains starting to trend lower now that US planting is done for corn and soybeans. Sugar and coffee, while showing trends, offered limited opportunities given the size of positioning for most managers.

Managed futures have been hurt by the February volatility shock and now the May bond shock from political risks. Economic surprises generally hurt managed futures especially if it comes in global bond market sector which is usually the largest sector of risk exposure. 

Sunday, June 3, 2018

Painful May performance for international equity and bond investing requires more caution with diversification


May saw a set of return reversals with bonds posting gains on flight to quality while international markets saw strong return declines. Selected country equity declines were very strong based on increased political risks. It was a good month for those cautious and focused on US smaller cap names.


The style gainers for the month were in US centric names, small cap, growth and value. International and emerging market performance declined on dollar strength and capital flight away from political risks focused in specific EU and Latin American countries.

The finance sector declined with the higher rate uncertainty. Rate sensitive sectors like utilities and real estate continue to lag other market sectors. Consumer stables declined again with double digit loses for the year. Technology continues to be the strong sector winner for the year.


Selected country ETFs were strong losers with double digit loses in Mexico and Brazil. Mexico is facing an important presidential election which may significantly change the business climate regardless of any trade issues with the US. Brazil has been facing strikes that have crippled the economy. Strong declines were posted in Spain and Italy. Italy is facing the problems of forming a coalition government while Spain has dropped on Italy contagion given the poor macroeconomic position of the country.


Bonds saw a strong reversal from the flight to quality associated with the Italian problem; however, a strong employment report reversed some of this positive bond euphoria. Sector loses were concentrated in the international and emerging market bonds. Bonds are still negative for the year across sectors.

Our moving average and break-out models point to a few key trends. First, hold US stocks and avoid international sectors. Second, avoid international and emerging market bonds. Third, avoid poor performing countries that are facing political uncertainty. Fourth, maintain or increase real estate, technology and consumer durable sectors. In general, while volatility has fallen since the February shock, there is still significant uncertainty that should mitigate excessive risk-taking.

Friday, June 1, 2018

Monthly performance does not follow an expected return script - Improvisation in value, growth, and small cap indices

One way to measure market uncertainty is to run a simple thought experiment. A well-behaved market should match performance with events in a well-defined manner. An uncertain complex market environment would behave in an ill-defined manner. Close your eyes and assume you have knowledge of the news highlights for the month of May. For example:

  • Political turmoil in Italy and the EU
  • Off-again/on-again North Korea talks 
  • Good economic data albeit with lower momentum
  • EM problems in Turkey and Argentina 
  • Trade war discussions

What would you expect?

The results for May were quite different from what many would expect for some asset classes. A flight to quality and a Treasury rally seems consistent with the news. Similarly, a decline in developed equity and emerging markets also seem consistent. However, the strong showing with small cap, value, and growth are out of character in the current environment.

Small cap, growth, and value indices all had gains of over 5 percent for the month even with higher volatility in the last week. Core domestic equities did better than global, emerging, and large cap stocks. These numbers are inconsistent with a flight to quality or risk-off behavior by some international investors. Unfortunately, the key drivers for May are political headline risks which are difficult to handicap. There is little evidence that can be used to provide likelihood for further momentum or mean reversion.


Thursday, May 31, 2018

The systematic trend trading fallout from Italy - Political shock impacts returns


Political shocks have market consequences. An examination of current financial markets against simple trend and momentum indicators suggests that the trading around the Italian political news was not pretty for systematic trend-followers. In the US bond markets, prices have rallied through 20, 40, and 80-day moving averages in just a few trading dates. This same pattern can be seen in Europe. Short-term rate changes like the Fed Funds and Eurodollars futures one year out have shown an even more exaggerated pattern on a relative basis.



What has the Italian government uncertainty done in the last ten trading days:
  • It reversed the major themes in financial markets.
  • It was a shock and not anticipated by markets 
  • It created a global contagion regardless of what some may have said by many pundits.
  • It is not a crisis, but has generated an adjustment in expectations. 
  • The price impact has shows an over-reaction with some reversal as expected with events generating high uncertainty which have not been resolved but pushed forward.
  • It is expected to have a longer-lasting effect as measured by one-year Eurodollar and Fed funds. 
This is a classic non-countable, non-measurable event that will harm trend-following managers which focus on measurable, countable, and repeatable events that evolve over time. Systematic funds were caught wrong-footed as measured by the reaction in '40 Act fund performance which provides daily return information. A representative sample shows similar return pattern for the month of May. Gains from trends earlier in the month were reversed in the last two weeks as financial markets rallied on fear and a flight to quality.

What can investors do? The only viable option is style and time diversification. Shorter-term traders may have been able to exploit the reversal. Non-Trend style investors were less impacted by the shock, albeit there was enough spread dislocation to hurt all but the most prescient traders. 



Tuesday, May 29, 2018

What keeps me up at night - "The glaringly evident that we have decided not to see"

"The hardest thing to explain is the glaringly evident which everybody has decided not to see." Ayn Rand 



The table is a short list of issues that should cause concern for any investor. A growing problem is that many are not focusing on the broader return implications for these risks, the chance for contagion and second order effects.  Perhaps we have not had the right catalysts to create focus. Perhaps we are being too dramatic in the current risk-on environment, or maybe these are just not really big problems. 

Nevertheless, these issues are keeping me up at night and they have not been given enough weight when measuring the potential return to risk for even diversified portfolios.

Monday, May 28, 2018

You may not want to be bound to an algorithm - so use a dashboard as a decision support tool

The benefits from using algorithms are well documented, yet they are still not used for many decision-making situations. The reasons for this lack of use are varied. It could be self-interest. It could be algorithms anxiety. It could be a lack of confidence in the modeling process. If there is a high level of uncertainty concerning the most effective model, there may be fear of being wrong. 

What we do know is that the more structure to the problem, the less noise or error there will be with any decision. Dan Kahneman discusses the problem when he wanted to use algorithms with a group he was advising on soldier selection in the Israeli army. There was significant pushback from his client, so he came up with a compromise solution of using the set of factors involved with the decisions as a scorecard. The scoreboard of key success factors would be filled out with the final decision in the hands of the client given the factor information. The scorecard or checklist always led to decision improvement that was better than no checklist and almost as good as the algorithm.

There may be an effective middle ground approach for any decision-making that would work well for those who do not want to turnover decision-making to an algorithm - a decision information dashboard.

Dashboards are being used more frequently in businesses across a wide number of fields. They are generally focused on providing up-to-date information on constantly changing data. This tool is perfect for investment management and can be more informative than a checklist. Bloomberg terminals have been tricked out as dashboards for years, but with new visual displays of information and flexible business analytics tools, dashboards have taken on greater usefulness and timeliness. The dashboards can incorporate the process of an algorithm in an easy to read format.

A dashboard can focused on specific decision-making through using graphics and scoring of key variables employed in a specific decision. For example, a simple scorecard on fixed income could include state of the overall economy, shape of the yield curve, momentum, carry, expected inflation, and Fed policy. These scorecard factors could be set to flash red or green based on the score. The set of signals can be aggregated to a fixed income buy/sell score. 

The decision can still be placed in the hands of the trader, but the likelihood of a noisy decision is reduced since the decision-maker would have to act against the factors that he believes are important for the decision. Mistakes will be made and the dashboard may signal false positives, but the chance of misdirected actions will be reduced. The dashboard could be set actually signal what multiple algorithms would do. The decision-making problem could then focus on disagreement with these algorithm assessments. A feedback loop can be established for any set of decisions, so that the decision-maker's action can be matched with the dashboard score.

Dashboards can force discipline on investment decision-makers. There is a problem if the dashboard advice is not taken or proves to be inaccurate, but it is a good way to impose algorithm-lite structure on decision-making. 




Sunday, May 27, 2018

Noise versus bias - We focus on biases but it is the noise that hurts us


"We have too much emphasis on bias and not enough emphasis on random noise"
- Dan Kahneman Speaking at the Kahneman-Treisman Center for Behavioral Science and Public Policy

There has been extensive discussions about behavioral biases in decision-making. The academic and popular articles on the bias topic are endless and there is a huge cottage industry of finding and cataloguing biases, but are biases the core enemy of good decision-making? 

Perhaps the bigger issue is noise - the random errors that create decision risk and uncertainty. The spread and inconsistency of noise can actual be more harmful with making good decision. Noisy decision errors are pervasive, but can be reduced. This is the conclusion of Dan Kahneman who certainly has been one of the leaders of the field of behavioral economics. 

We usually think of noise as measurement error and bias as judgment error but that is an inappropriate dichotomy. Noise is created with our judgment when we don't behave the same for similar decisions. Noise is an invisible problem because we don't believe we can create it. Noise is random, yet it is persistent when we don't follow an algorithm. Algorithms will shrink the noise both for your own decision-making and the across any set of analysts looking at the same problem.





There is measurement noise within us. If we are presented the same problem, say rating a wine, our current assessment may not agree with our judgment from a prior evaluation. If we use a panel of wine judges we would not get the same assessment cross-sectionally. There is noise because everyone cannot agree on what is quality. Just think of the noise that is possible if the judgment needed is for something that is especially complex.

Kahneman is very direct on the issue of noise. If there is judgment, there will be noise. The noise can come from any number of sources, but it will exist. The core value of an algorithm is its bland sameness when facing a judgment. There will be less noise when we approach a judgment in the same way. We can identify behavioral biases, but the core problem of noise while subtle is actually simpler. Use repeatable tools to drop judgment error.

Saturday, May 26, 2018

Kahneman on silence - Turn down the noise through turning up the algorithms


"An algorithm could really do better than humans, because it filters out noise. If you present an algorithm the same problem twice, you'll get the same output. That's just not true of people." 

"But humans are not very good at integrating information in a  reliable and robust way. And that's what algorithms are designed to do." 

- Daniel Kahneman interview "Where Humans Meet Machines: Intuition, Expertise and Learning" MIT IDE 


In a recent interview Dan Kahneman talks about the problem of decision noise. When a group of decision-makers are given the same set of repeatable tasks or problems, you would like for them to generate the same answer, yet that is not the case. There is limited consistency with decision-making.

Kahneman discusses a research test done with a set of insurance underwriters who are given six sample problems. He believed that there was a surprising amount of noise given the controlled experiment with disagreement about 56% of time. Professionals with the same training and facing the same stylized problem should generate the same answer. That is not the case. 

Investors may face the same problem. There seems to be a significant amount of noise around decisions that are facing similar sets of facts. Take any economic announcement as a simple case. There is a significant amount of trading volume and thus disagreement on how to interpret the new facts. Perhaps investors always think this time is different. More precisely, investors may be using different models or have different believes that will lead to different conclusions. Reality is only revealed later. This may not be a bias but just dispersion around reality. Investors may be facing too much information that creates a situation for decision noise to exist, (see Pump down the noise - Decision silence).

An algorithm will allow for similar reactions to a repeatable set of facts. There will still be error but a repeatable process will shrink the noise and allow for feedback on what may have gone wrong. Ending randomness with decision-making is a positive that can be achieved through using models.


Friday, May 25, 2018

What is beta for commodities? There are big differences



An investor may want to increase his commodity beta exposure to meet his strategic allocation target for this asset class.  Unfortunately, all betas are not created equal in the commodity space. There is a wide difference in the choices that are available and this chasm is much greater than anything found in other asset classes.

Investor may not be able to get to smart beta because there is little agreement on just plain beta. If you ask someone what is the beta benchmark for equities, the answer is easy, the SP 500 index. For bonds, the answer is the Barclays Aggregate Index. An investor may choose a different benchmark, but there is almost universal agreement on a base index. This is not the case for commodities. Given investor luck, whatever benchmark is chosen, it is likely that another will do better. 


The chart above shows the range of returns for commodity beta based on the broad definition used by Bloomberg. This range includes a fair number of what may be called smart beta approaches to commodity investing; nevertheless, we highlighted four basic passive long-only commodity indices that have been actively used by investors. The BCOM and GSCI would be the most popular. The GSCI will have a higher energy allocation than the BCOM. 

For 2018, the differential between the two leading indices is over 700 bps while the difference for the last year is over 14%! Picking the wrong benchmark will have a significant performance difference for that asset class bucket. There is no simple solution to this problem. Averaging more than one index is possible but does seem to be a satisfying alternative. Hence, making the simple decision to have some commodity exposure is actually much more difficult than would be the case in other asset classes.

Wednesday, May 23, 2018

Using scenario analysis to help with asset allocation - A simple solution to a complex problem


The reason for asset allocation scenario analysis is simple. There is a whole crowd of investors who do use or are uncomfortable with formal decision-making employing optimization. Quantitative asset allocation models like Black-Litterman, while elegant in theory, have not caught-on with many who are on the frontline of asset allocation work. Running scenario analysis provides a useful thought experiments tool to help refine asset allocation choices.

Many large Wall Street sell-side and buy-side firms will provide long-term excess return forecasts for clients. These will usually be a combination of a number of simple factors like growth, inflation, valuation, earnings and dividend yield. These factors are rolled-up to a point estimate for the long-term expectation that can be used to help with long-term asset allocation decisions.

There are ways to extract more value from these forecasts through using scenarios analysis with confidence assessments on the component factors to generate alternative asset allocations. Scenario analysis provides a quick way to assess alternatives.

An asset allocator can compare his underlying factor expectations and confidence against the market's estimates and form alternative allocation choices for different scenarios. Factor inputs for your long-term expectations can be given different weights or level of confidence than the market view. These differences in estimates for the underlying factors can then be incorporated into different asset allocations which can be given some likelihood. 

Running comparisons of your own subjective market forecasts against the market's view is not novel, but it can be an extremely useful exercise for identifying risks and reasons for portfolio tilts. 

For example, 

  • What would be your bond return expectations if long-term inflation were greater than the market consensus of 2%? 
  • How much confidence do you have in a greater than 2% inflation forecast?
  • If you believe there will be a higher inflation number, what would be the portfolio you would create relative to a current benchmark? 
  • Do you believe current stock valuations will continue? If stock valuations normalize, what will do you believe will be the impact on expected equity returns? 
  • How will you adjust your portfolios relative to a benchmark or the market consensus for valuation?





Scenario analysis can show the impact on asset return and risk from your subjective views versus the market's view. If this is done on a factors basis with confidence weights, investors can generate the overall impact of their views on potential return and risk.

We have found that there is an effective middle ground between optimization and ad hoc use of point estimates for asset allocation decisions. Albeit a second best solution, scenario analysis, if done right with some measure of likelihood with respect to alternatives can be a useful informative tool for investors.