Thursday, May 30, 2019

Pierre Wack and deeper thinking about scenario analysis

“Scenarios deal with two worlds; the world of facts and the world of perceptions. They explore for facts but they aim at perceptions inside the heads of decision-makers. Their purpose is to gather and transform information of strategic significance into fresh perceptions. This transformation process is not trivial—more often than not it does not happen. When it works, it is a creative experience that generates a heartfelt ‘Aha' … and leads to strategic insights beyond the mind's reach.”
- Pierre Wack 

Building scenarios is a key creative process for investment management. You can get a quant to run an optimizer, and you can get a good analyst to tell a strong narrative with supporting documentation, but building alternatives for future market performance is much more difficult. Many simplify this process by just providing three scenarios, an optimistic, pessimistic, and a base or status quo. That is a form of scenario analysis, but it is not effective scenario building. It may not provide the deep thinking of how changes in the economy, adaptive expectations, and capital flows interact to create new return worlds.

The classic scenario is usually just built around expected return or price estimates. A portfolio manager will run a likely case based on his best guess of what may happen across a set of asset classes. There may be a narrative attached based on a set of assumptions with how markets respond to news. From this base case, there will be a positive (good news) scenario that will have higher returns for riskier assets and a negative (bad news) scenario where risky assets fall in value. Each scenario is given a probability and the portfolio upside, downside, and likely scenario are assessed to determine risks. This is not a bad way of looking at alternatives and is consistent with the method taught in most business schools. but it is not an effective way for conducting deep portfolio planning.

Pierre Wack was the leading scenario planner for Royal Dutch Shell and revolutionized thinking about scenario thinking in the 70's. Unfortunately, he has not been studied extensively in more recent history and never gained any traction in the world of finance. The processes of running scenarios for a large corporation are different than for an investment portfolio. Corporate risks are greater because capital investment decisions need to be made with long lead times. The costs of being wrong are also higher given there is less diversification with focused industrial company.  Nevertheless, the deeper operational thinking and examination done by our best corporation should be applied to investment portfolio construction. 

Wack did not come out of the quantitative world so his thinking did not fit with normal optimization and scenario analysis. A focus on perceptions has never been a normal part of investment thinking. Hence, he is an obscure figure for money managers. Nonetheless, he can teach us how to make better decisions by embracing an uncertain world.  

The premise of good scenario analysis is that managers have to be engaged with the relationship between facts and alternative perceptions. It is not using the same thinking with a good or bad state of the world, but developing thoughts on alternative models of thinking.

For example, the normal view is that larger debt supply should lead to higher rates, yet the facts suggest that larger deficits have been consistent with lower rates. The perception of many for how the world works does not fit the facts, so we have to think through alternative perceptions of reality, or alternative model of how markets operate. 

Another instance of changing reality is thinking about modern monetary theory (MMT) and the cost of financing deficits with money. Few would have thought just two years ago that MMT would be given much deep thinking, yet politicians, policy-makers, and investors are all now discussing it as an alternative for running fiscal and monetary policy. 

A similar story could be told about trade wars. The role of China in the world economy and how trading partners work with China have changed radically in the last year. Scenarios for how countries will engage with trade will truly impact return profiles with both winners and losers that cannot be described in good and bad scenarios.

Perceptions change and those alternative realities have to be considered. Once we form alternative perceptions, we can discuss what will happen with new disruptions of shocks to markets and the implications across assets. Investors can then think through a set of alternative investment choices. 

The market disruptions in 2008 were a failure to think through how shocks may promulgate through markets. It was a failure of broadening our perception on risk, liquidity, and market reactions. In the post crisis period, no one would have perceived that there would be $11 trillion of negative yielding bonds. 

Deep scenario thinking asks those engaged in the process to walk through the implications of whether their assumptions of market behavior are wrong or at least how they should be weighted relative to the thinking of others. There is no optimization model for a good scenario process and it cannot be structured as set of rules. Scenarios require thinking about new investment worlds.

Tuesday, May 28, 2019

How alternative risk premia are built - The devil is in the details

What generates a return difference between similar alternative risk premia - the construction details. Alternative risk premia have to be defined and constructed to isolate a specific risk factor. Institutions can define a risk premium differently because there is no standard definition for most. Alternative risk premia can be described in generalities but the actual construction is based on a set of specific criteria and definitions. These criteria can be used as a short-hand for what you need to know to understand the performance differences between risks premia. 

For example, in the case of a commodity backwardation risk premium strategy, the criteria for making the strategy index can be useful construction checklist. 

  • First, what is the universe of testing. How many commodities are included in the analysis? There can be a limited set of very liquid markets or a broad list of all commodity futures markets. Some backwardation strategies use less than 20 markets and make specific exclusions. Others may consist of a broader basket.
  • Second, the definition of the factor also critically affects return. For example, the backwardation could be measured by the difference between the first and second nearby contract, or it could be the maximum backwardation over a longer time to maturity. It could also include some exclusion for seasonality. 
  • Third, the scoring method serves as the basis for measuring the high and low for backwardation. 
  • Fourth, the selection classification may be that the top and bottom 20 percent of the scored universe.  It could also be a set number like the top and bottom three markets.
  • Fifth, the portfolio construction selection criteria will determine how the commodities will be weighted in the portfolio. For example, the three highest backwardated commodities may have equal risk contribution or an equal dollar weight.  
  • Sixth, the long/short method determines what will be the net exposure in the portfolio. This method could be dollar neutral or beta neutral. The net exposure may still have beta exposure that is not desired. 
  • Finally, there is the leverage associated with the total portfolio. This factor can be affected by the earlier choices of risk exposure. 

We can go though the same exercise for a currency carry alternative risk premia. If these are delivered through a bank swap, all of the rules for constructing an index will have to be defined so the swap can be priced on a daily basis  

While we have provided simple framework and example, the construction and analysis will generate a deeper analysis. The key point is that two alternative risk premia may be called the same but may have differences in performance based on the method of construction.

Better define asset categories and cut alpha - New Morningstar core and core plus bonds

Morningstar changed the definition of core bonds last month by breaking the category into two, core and core plus. The core definition is an intermediate bond fund that includes government, corporates, securitized debt, and less than 5 percent in other categories. The core plus category includes high yield, bank loans, emerging markets, and non-US bonds. Clearly, the old definition allowed for a significant amount of gaming through taking on more risk is assets not usually included in investment grade bond benchmarks. 

Alpha was created by loading up on the things that were not in the benchmark and including more assets that are not usually expected in core bond investment. Hence, there may have been significant hidden risks in these funds. The new categories change the Morningstar rating for many well-rated funds since they are now in a new peer group. A graph of the difference between core and core plus over different horizons shows that the average excess return for core plus is positive. This would have given these funds a ranking advantage in the old broader category. 

These more detailed or restrictive definitions are good for investors, regardless of what you think of Morningstar ratings, but it again focuses attention on what alpha means. Is alpha skill the ability to choose assets not in a benchmark that may have higher risk? This portfolio composition is a skill, but most think of alpha as the ability to choose weights based on timing of excess return and not by overweighting non-benchmark assets.  Better definition leads to an incredible shrinking alpha.

Monday, May 27, 2019

Corporate credit risk not just a US thing - It is a global issue

The Bank of England in their Bank Underground blog, commented on the growing risks with corporate bonds. Their risk concerns are the same as has been voiced in the US. First, the percent of BBB-rated sterling bonds are on the rise.  Second, the market structure makes for more risk through a mismatch between assets and liquidity needs of investors. In the case of sterling bonds, there are  increased risks from BREXIT.

It is interesting that central banks are sounding an alarm about the growth of riskier credit around the globe when this was exactly what they wanted with lower interest rates. High quality credits can always borrow and in many cases do not need the money. Lower quality firms are more sensitive to lower interest rates and will respond to cheap financing. Lower rates will also create the demand for riskier bonds as investors chase yield. Should we be surprised?

Since equities have softened this month, it is notable that BBB-rates spreads have increased by about 10 percent. This may not be enough to scare investors, but it is a sign that investor desire for risk is sensitive to this asset class. 

Friday, May 24, 2019

Trends are everywhere - Don't give-up on times series momentum

Discussions with investors suggest that there is frustration with trend-following returns, yet the evidence continues to grow that if there is one consistent style risk premia to buy, it is time series momentum. If you are a style betting man, this is the place to put your money if you follow the odds across time and asset classes. This is the conclusion if you follow the research conclusions from the research paper, "Trends Everywhere" which will be forthcoming in the Journal of Investment Management and written by the folks at AQR.

One of the tests for measuring the quality of an investment strategy is out of sample testing using a new dataset. The researchers in this working paper looked EM equity index futures, fixed income swaps, volatility futures, and long-short equity factors, a total of 82 new securities and 16 long-short equity factors that add to the 58 assets they have been analyzed in past research. Across traditional, alternative and long-short factors, the researchers find a gross Sharpe ratio of 1.60. 

The testing approach is as simple as you can get through looking at time series momentum over some past look-back period updated monthly. There are no frills or risk management and volatility is normalized. Within different asset groups, the returns are averaged. The calculated trend alpha relative to passive volatility scaled beta regressions are significant and economically meaningful. 

The alpha production is significant across all groupings except for credit indices. The value increases when diversified across a broad set of markets because there is little correlation across these markets. 

The gross Sharpe ratios are consistently positive although the Sharpe ratio for any one market may be vary greatly. Clearly, for any market or time period there will be performance variation, but a long-term investment in trend-following will be rewarded. 

Across all of these markets using time series momentum the benefits of positive convexity are measurable. The combination of being able to go long or short will allow downside protection without a change in strategy. 

There will be a difference in net performance once transactions costs and fees are added to this analysis. Execution costs will change with market conditions. These costs impact returns but not volatility so the Sharpe ratios will decline. However, the overall investment story will not be significantly different. Trend following returns will change with market conditions, but history and the data are on your side if you engage with this strategy.  

Thursday, May 23, 2019

Correlation in the tails - You will be surprised at the limited convexity

For some, the devil is in the details - for investors, the devil is in the tails!

The only free lunch is diversification except if you are in the distribution tails.

An investor will look at buying assets that have lower correlation with their main equity holdings; however, it is critical to look the conditional correlations in the tails. Investors need diversification the most in the left-hand tail of equity market extremes. We try to visualize the problem through looking at the left and right tail correlation for a wide set of assets, hedge fund styles, and factor. As a first pass, we use the data appendix from the Financial Analyst Journal article "When Diversification Fails" from December 2018. 

We look at a map of right and left tail correlations divided into a 2x2 grid. In a perfect world, investors would like an asset that has positive correlation in up markets and a negative correlation in down markets. This is represented by quadrant III. If correlations are the same in both up and down markets, the values will be on the 45-degree straight line. 

Most assets fall above the 45 degree line and in quadrant I and II. These tells us the correlation in the left-tail (5th percentile) is higher than the right-tail (95th percentile) of the equity return distribution. The only notable exception is with Treasuries in quadrant I where the right-tail correlation is positive and the left-tail is negative. This suggests that investors should always hold Treasuries as their diversifier; however, the relationship has not held during periods of higher inflation and has not always been stable.

Looking at this differently, we created a simple measure of correlation convexity by taking the difference between the right-tail and left-tail correlations, (correlations in the 95th minus 5th percentiles of the equity return distribution). If correlations are the same, the value will be zero. If an investor receives more downside diversification, the value of the index will be positive. Most assets have negative values or worsening diversification in market downturns.

Investor should look at correlation risks; the fact that the unconditional correlation is not the same as the conditional correlations in the extremes. If you have to hold this correlation risk, you should be compensated with higher returns. More time should be focused on these correlation risks and their impact on portfolio hedging and diversification.

Wednesday, May 22, 2019

Secular changes that will negatively impact bond investors

Market structures change. These changes impact the risks that investors face, so the crisis of tomorrow may not be the same crisis of yesterday. If you are a good risk manager, you have to be an institutional economist. The institutional setting changes how risks channel through markets and you have to know the details. The new paper "This Time Is Different, but It Will End the Same Way: Unrecognized Secular Changes in the Bond Market Since the 2008 Crisis That May Precipitate the Next Crisis" by Daniel Zwirn, Jim Kyung-Soo Liew, and Ahmad Ajakh does a good job describing some of the key institutional or secular changes in bond markets over the last decade. We may not know which of these changes will be important during the next crisis, but we can say that the they will create surprises for investors and regulators who think they have solve the problems of the past.

The main thematic change is liquidity. Innovation through ETFs, changes in profitability for market makers, the mix of financial intermediaries, and the incentives to take risk will all affect liquidity. While following institutional changes is helpful, theory is unwavering. If the cost of liquidity increases, the price for immediacy will rise. Liquidity will not be present when you need it, so investors have to preemptively prepare for a crisis and potential pay the price of waiting for the next crisis to occur. 

Tuesday, May 21, 2019

BAML survey - Risk concerns focus on trade wars and tech

The BAML Global Fund Manager Survey provides good insights on where are the major concerns for investors through its biggest tail risk and crowded trade charts. Risk represents the unexpected downside from surprise events or news, but risk can also be right in front of us as measured by investor perception and crowding. We may fully recognize risks, but still not be ready for when the shock occurs. 

However, the risks from a focused tail risk and crowdedness are fundamentally different. Crowdedness is focused on the reversal of expectations.  The tail risk  survey often focuses on not knowing what will be the market response.  Expectations are unclear.

The BAML survey puts trade wars as the key investor risk, but if you ask investors how this will play out in markets or how markets will react to a change in trade negotiations, the results are less clear. The impact channels of a trade war through economy are hard to measure. What does it mean to have a trade deal? Yes, uncertainty will be reduced and there may be some obvious market responses for specific companies and sectors, but overall market direction is not immediately obvious. Will tariffs be lifted? Will intellectual property be protected? Will China increase imports significantly? Will there be a surge in China exports to the US? Will other US-China geopolitical tensions decline?  The answers to these questions are not clear Alternatively, if there is no trade deal, what is the next move by each player? Again, the right bets or reactions are not clear. The right hedge may be to just reduce risk.

For the crowded trades, the response is more obvious. Crowds turn on new information as one-sided expectations change. Here the bet is on reversal and the cost of waiting for the change. We know that crowd changes can lead to momentum crashes. Protective trades can be constructed because the potential risks are clearer. 

The key with using this survey information is to have a plan on taking advantage of the focus of other investors. Are you ready for changes in what is important to your fellow investors?

JP Morgan hedge fund survey - What is hot and what is not

The top reason for investing in hedge funds is again very straightforward, alpha generation. The percentage may vary between investor types, but the answer is always the same. This is especially true after 2018 when many hedge fund managers underperformed relative to expected returns. The expectations for return are consistently targeted around 5 and 9 percent with expected volatility in the 5-7 percent range. Investors are expecting for risk less than equities but slightly more than bonds with a return to risk ratio above one.

Investors are looking to add to four major asset class and style areas: credit, fixed income relative value, global macro, and volatility arbitrage. This is an interesting combination. Credit spreads are again tight after the January reversal, and there is continued concern with leverage. It seems that investors want to take advantage of dislocations in these markets if there is a sell-off. The volatility arbitrage is odd given the poor performance of these strategies during the last February volatility spike. There is high potential for negative skew events. Fixed income relative value is a variation on the credit story. Investors are looking for alternatives to duration risk. Finally, there is the strong interest in global macro. This may represent the desire for a defensive global strategy different from managed futures.

Investors still have demand for hedge funds as an alternative to traditional assets.  They have concerns about fees, but are willing to commit to finding sources of alpha. The specific demands change with market conditions. 2019 is a reflection of overall asset allocation changes; caution on equities and a desire for relative value in other asset classes. 

Monday, May 20, 2019

Econometric teaching is not focusing on new tools for financial data analysis

I was recently asked to review a new book on financial econometrics for a investment journal. I was disappointed with the direction of the book. It is well-written, detailed, and covers all the important finance topics researched over the last three decades. Unfortunately, it is missing many of the advances in data analytics that are changing how current research is conducted. The old or traditional thinking about econometrics is not serving the investment world well. It has not helped practitioners of finance.

This issue of not focusing on cutting edge techniques and research was further reinforced after reading the notes “The 7 reasons most econometric investments fail” by Marcos Lopez de Prado. 

The greatest advances in data science are occurring in fields outside of finance. Machine learning is being used in finance; however, it is not being taught as foundational for use in econometrics or finance. In more simple terms, there are broad techniques in statistical work that are largely ignored by finance in an attempt to maintain the focus on well-defined linear models. Theory is critical to good science, but given the large amount of data, there also needs to be a broadening of fundamental work in analysis. 

Some of the issues and topics that should be addressed in a new financial econometrics book:

  • the high number of false positives with any analysis and the over-reliance on p-values and statistical significance, this has caused the factor zoo we currently face;
  • the overuse of the multivariate linear regression model;
  • the avoidance of clustering and classification methods;
  • an effective introduction to machine learning techniques and neural networks; 
  • an increased emphasis on forecasting and model overfitting and specification bias;
  • a discussion of unstructured data, hierarchical relations, and sparse datasets;
  • a focus on conditional correlation, outliers, and nonlinearities. 
These topics are practical and useful for many finance problems today, yet there is limited time spent on looking outside the traditional econometric toolbox. Of course, there have been significant advancements and greater sophistication of testing today relative to two decades ago. However, my point is increase the focus on using the right tools for the right problem and a linear stable world is not what investors face. 

Saturday, May 18, 2019

Tiger 21 investors are getting defensive - Cash may not be king but certainly a prince

What is smart money doing?  It is often assumed that smart money is rich, and everyone wants to know what they are doing. Tiger 21 is a loose club or network of wealthy individuals who share investment idea. It is hard to say they represent the elusive smart money, but their allocation decisions provide some data on what is happening to wealthy portfolios. 

The Tiger 21 latest survey for the second quarter shows a relatively large increase in cash holdings from 10 to 12%. This is the highest level in years. Cash yields on Treasury bills are also at multi-year highs and the yield curve is slightly inverted so the cost of holding cash is low. 

Investors are acting rational. If there is a high degree of investor uncertainty and cash rates are attractive, increasing cash levels makes sense. If this allocation is representative what other smart money may be doing, demand for risky assets will decline. Without new money flows, it is harder for risk-on assets to move higher.

Friday, May 17, 2019

Changing the dynamics of enhanced cash - Switch from credit to alternative risk premia

Investors are always looking for ways to enhance cash returns - higher yield with liquidity and limited principal risk. The timing for using different enhanced cash techniques changes with market conditions. Widening the choice set through investing in alternative risk premia may be a way to meet enhanced cash goals without significantly increasing risk.

There are only a limited number of ways to generate enhanced cash returns: duration, term premium, roll and credit carry, and credit premia. An investor can move out the yield curve to take duration risk. This will help the potential total return but at the expense of higher volatility. The investor may move out the yield curve to capture the higher yields associated with the term premium. Roll carry is associated with buying longer duration debt instruments when the curve is downward sloping and capturing the gain from selling their bond at the lower yields at lower maturity. This is diminished if the yield curve is flat or inverted.  Finally, there are credit spreads as compensation for buying riskier debt. There is roll value as duration falls. Money market investors will increase their demand. 

At different times, these yield improvement propositions will be enhanced or diminished. A steep yield curve is a credit time for enhanced cash. Wide credit spreads are also a good time to move out the curve. Similarly, tight spreads and a flat curve is a better time for shortening duration in the front-end of the curve. 

Given the changing conditions for fixed income in front-end of the curve, it may make sense to determine when to breakout of traditional thinking and investing in other types of risk premia. There is a broad set of alternative risk premia across asset classes and styles. Investors can move beyond the rate curve and credit premia choice set. First, these other risk premia have low correlation with credit. Second, these alternative risk premia can be delivered through total return swaps. Hence, these risk premia can be an overlay against a Treasury portfolio. A credit portfolio is a combination of Treasuries plus credit spreads. An alternative risk premia portfolio is a combination of Treasuries plus alternative risk premia. The investor can choose the "spread" or alternative risk to Treasuries. The amount of downside risk can be adjusted based on types of risk premia and the level of exposure or leverage. 

Appreciating the value of diversification as choice improvement tool is a key principle of finance. Anytime there is in increase in the set of alternative opportunities there is improvement in the return to risk choices. Using risk premia beyond rates and credit can improve return opportunities. It may take investors out of their normal comfort zone, but it will help when traditional opportunities are limited.

Thursday, May 16, 2019

"The Emeril Lagrasse Theory" - Practical knowledge and culture is not often transferable

After hundreds of discussions with hedge fund managers, I am still surprised that there is a fear of revealing investment processes under the assumption that someone will steal their ideas and intellectual capital. There are few investment styles that are truly unique and special. What is special is still strategy execution - the practical process of delivering returns. Skill is with the decision-making execution of information and strategy.  

I often use the analogy of the cookbook written by a famous chef. Walk down the cooking aisle of any bookstore and you will see all of these books that explain in great detail the "secrets" of famous chefs. These cookbooks will tell you all of the ingredients. They will walk you through every step in the process. They will provide color pictures of what the dish should look like and will also provide pictures of intermediate steps. Why would these chefs give up their secrets? 

They provide transparency because they know that their practical knowledge cannot be replicated. The reader's attempt to replicate the meal often fail. Once readers see the complexity of the cooking process, they will often just go to the restaurant and enjoy their meal at a high price. Transparency creates value. We discussed this in our previous post -"Technical and practical knowledge - You need both for asset management"

Mike Lombardi in his book Gridiron Genius discusses "The Emeril Lagrasse Theory" as applied to coaching which is also applicable for money management. There are many who have studied and worked for a truly great coach like Bill Belichick or Bill Walsh, but they are often not able to replicate the success of the coaching mastermind. There are many who have studied with Emeril but have not replicated the quality of his cooking. They cannot replicate their mentor's practical knowledge, drive, or culture. These are Emiril's true skills.

We see the same thing with hedge fund start-ups where a junior manager decides to start his own firm. Some are successful, but many are not able to match the success of their mentors. There is intangible practical knowledge and culture that is not easily transferable to others. Investment skills such as culture and drive, whether associated with quantitative or discretionary managers, are not always transferable. Investment managers do not have to hide their investment strategy. The strategy does not make them unique. Implementation skills make them unique. For investors, once strategy is understood, due diligence has to focus on a manager's practical knowledge. Investor should allocate to strategies but back managers with practical skills.

Monday, May 13, 2019

Inflation - Where do we go from here?

Don't worry about inflation - the Fed isn't. Or, the Fed believes there is no value is trying to get ahead of any inflation increase given the relatively tight range for inflation.  The market penalized any fixed income investor that acted on inflation fears.  Any Fed objective function has a higher weight on growth.

The Cleveland Fed has been producing the median inflation rate for years. It provides a different perspective on inflation. It is moving higher, yet that is not a focus by the market.  The fact that the compounded effect of inflation in the 21st century has been substantial for those who do not have indexed wages seems to be missed by our central bankers. While there is talk of inequality by the Fed, the cost of low rates and inflation hurt the poor more than the rich. 

The current bias is that Fed will under-react to any inflation increase. The PCE showing an extended period above 2% lasting for months and CPI close to 3% seems to be necessary conditions. All verbal signals say that the cost of inflation is low relative to any slowdown in growth or decline in financial assets. This may seem obvious for many investors, but an implication is that any Fed behavior different from this current consensus will be disruptive. Any surprise in 2019 will be associated with tightening.

Saturday, May 11, 2019

Mike Lombardi, football coaching and investing

I am not a football fanatic, but I picked up this book on a recommendation and was amazed by Lombardi's insights on leadership and management. Mike Lombardi is long-time football executive and media analyst. The book focuses on Bill Belichick and the New England Patriots, but his conclusions could apply to any money management firm. A good money management firm is successful because it acts like a well-disciplined organization with a common purpose. That is no different than a competitively run sports organization. Lombardi finishes his book with five key recommendations for firm success that are worth presenting in bold.

I would employ these five recommendations to any hedge fund or money management firm. The idea that culture beats strategy has been a key insight from Peter Drucker. Always use any edge you have because you will never know when it will be useful. A good money management firm that wants to generate alpha always has to think about their edge. The system should always be dominant over a star. A star system can never be sustainable and never effectively uses the entire organization. If the smartest person in the room is always the same person, the firm better switch its hiring practices. There is no such thing as short-term leadership. Leadership is hard work that takes time.  Leaders do not think about the short-run but are always playing a long game. Finally, always try to get better. This is a variation on the Japanese management principle of kaizan, incremental improvement. 

I have often focused on management and decision-making with some of my posts for the simple reason that process is more important than any single market viewpoint or recommendation.

Friday, May 10, 2019

Endowments need help - Performance not strong versus balanced fund

Endowments are supposed to be the smart money, yet if you review the recent exhaustive paper on return performance, you will get a different impression. Large endowments do better than small endowments but when you compare with a simple 60/40 stock bond balanced fund there is not a lot of alpha generated. See "Investment Returns and Distribution Policies of Non-Profit Endowment Funds" from ECGI.

I was shocked by the results given that endowments can be patient money with broad mandates. They have often been at the forefront of hedge funds, alternative investing, and private equity. Now, this could a result of the way the authors partitioned the data. A $100 mm large fund cut-off is fairly low. 

An analysis of the endowments using a four-factor model shows that all alphas are negative but the smaller endowments are slightly less negative. The fraction of endowments with negative alpha is just under 60 percent. The odds of creating positive alpha are less than a flip of a coin.

However, the deeper dive into alpha using a four-factor model suggests the top 20 universities at best generating no alpha. This is better than the other partitions, but this does not mean that the large endowments should be patting themselves on the back.

The take-away from this study should not be surprising. Markets are competitive and it is hard to produce added return versus a benchmark or a simple factor analysis. There may be successful firms but it is not easy to consistently add value.  Endowments do not seem to have any special investment skill.

The current approaches to investment management by endowments are not effective at generating excess return. The processes in place for strategic and tactical asset allocation are not working. Endowments need to improve their investment behavior and do have a choice. They can move to a strategy of low cost passive investing, or change the current active return-generating model. 

By passive investing, we mean a structured approach to holding strategic asset class allocation or risk factors. A low cost passive approach finds low cost benchmark replicators and forms a well-diversified portfolio that is rebalanced through a set of rules. Be diversified at low cost. 

Changing the current return model may include moving away from a classic approach of adjusting asset class allocations and looking for successful active managers, and moving to a factor risk approach that allocates to a diversified pool of risk premia. The risk premia diversification will be adjusted based business cycle risks. There is a change in focus from security and asset class selection to factor management.

The choice of which approach will be based on whether an investment committee believes it has an information edge in the market. A candid review will likely conclude that a low cost passive approach may be a safe and effective investment approach. Yet, a factor-based approach can be coupled with low fees to create a viable alternative.

Thursday, May 9, 2019

Time-varying correlation - Diversification benefits are dynamic

What is the correlation between two assets? The correlation is critical because it is the driver for any diversification decision. The better question is, "What is the correlation now, and what can it be in the future?". Correlations are often time varying and regime specific. In bad times, correlations rise, so the diversification expected is not present when you need it. This phenomenon requires more thinking about tail risks and how to best address them.

It is not clear that investors fully appreciate the magnitude of the tail problem. Of course, investors have felt the impact in their portfolio returns but visualization clarifies the point. We are using the figures from the Financial Analyst Journal, "When Diversification Fails" by Sébastien Page, CFA, and Robert A. Panariello, CFA which compares the equity left and right tail extremes for traditional assets, hedge fund assets, and investment factors. 

What is truly surprising is the for traditional assets is the magnitude of the differences between the left and right tail. In the case of hedge funds, there is limited diversification safety in the left-hand tail. For many strategies the correlation is as high as what would be expected for a traditional asset. Alternatively, there is much better diversification benefit from investing in factors. A balanced portfolio of factors that can be generated from alternative risk premia is likely to provide a more stable diversified portfolio. 

Market extremes are usually associated with common factor like an economic downturn. For long-only benchmarks, correlations will rise in response to these shocks to market beta. Factor investing identifies and isolates risks which may not be driven by phenomena like growth shocks in the same way. There will still be dynamic changes in correlations across factors during extremes, but these changes may be muted or more independent. By simply changing the type of risks taken, investors can change the diversification outcomes.