Illiquidity premium and asset allocation - Mistakes in management even when paid a premium

If you have an asset that has an illiquidity premium, an optimizer will love it as a choice. An illiquidity premium is a dangerous area for investing. First, are you getting paid enough for illiquid? Second, is there a good way to measure illiquidity? Third, do you really know your liquidity needs?

There are two assets, one liquid and the other illiquid, for consideration. The illiquid asset has a slightly higher yield, a premium for less liquidity. An optimizer will choose the illiquid investment, all else being equal. The illiquid asset will have a smoother volatility. The optimizer will again prefer it versus a liquid alternative. An illiquid investment will not react as quickly to new information and will be less correlated to other assets. The optimizer will again prefer it. An optimizer will love an illiquid asset, and that is a problem.

Now, we have been extreme with our view of a two assets, but the point should be clear. There will be allocation distortions if you do not properly account for illiquidity.  Liquidity will never be available when you want it. Illiquidity will never improve from what was sold to you.

So how do you address the illiquidity problem? There are two simple solutions. First, rough-up the data by using a volatility that may be closer to the volatility of the asset class associated with the illiquid asset. This will downgrade the smoothness of the illiquid asset and will also increase the correlation with other assets in the asset class. Second, cut the returns that will represent the risk premia associated with liquidity. An optimizer does not think about liquidity. An investor should account for these factors.

What is PMI telling us about the stock/bond mix?

A big problem with macro fundamental investing is getting timely data on the economy and then translating that information to effective investment signals. Government issued data generally are out of date and old information for forward looking forecasts. Hence, there is greater value on macro data that is current and prospective. 

The PMI forecasts, which are announced monthly, are a good macro candidate given they are measured across a broad number of countries, have significant history, and are forward-looking expectations of economic activity. 

A graphically analysis of PMI explains the major sell-off in European equities relative to the US. It can also explain the decline in EM equity valuation. Similarly the PMI forecasts can tell us something about the broad trends in bonds. If the PMI is declining (increasing), there should be a bond rally (decline). Rates fall during declines economic activity. Investors just have to get an early signal. The current reading suggest that any switch away form equities should focus on bonds not cash. 

Categorization and classification - Fundamental to finance and investing

"Categorization is not a matter to be taken lightly. There is nothing more basic than categorization to our thought, perception, action, and speech. Every time we see something as a kind of thing... we are categorizing."   
- linguist George Lakoff
from The Geometry of Wealth by Brian Portnoy

Most investment work is about forming categories. We divide securities into asset classes. We make subcategories within an asset classes. We make industry classifications. We divide risks into different types of premia. There are value classifications. There are categories and classifications based on macro factors like inflation. Investors like to group. All scientists like to make groups and form clusters of similar things to find commonality.

The basics of science have always been about categorization. Whether animals, plants, or rocks, the basic work of observation and classification has been a core principle of observational science. Before there is theory, there is observation and the observation lends itself to systems of classification. Before we can offer explanation, there is a need for categorization and search for sameness and differences. Providing taxonomies helps us understand the world around us. 

Categorization is part of the narrative of science and a normal part of the storytelling of finance. The categorization is a heuristic for finding or describing correlation and similarity. The theory of finance attempts to look beyond classifications or categorization and in order to find first principles of what is an asset separate from any naming convention.

There can be a distinction between categorization and classification because most things do not fit into simple boxes. Classification is more formal and systematic based on rules. Categorization uses boundaries for similarities. See Elin K Jacob "Classification and Categorization: A Difference That Makes A Difference". The structure of categories and classification are not often discussed and just assumed, yet the choices are important.

By grouping stuff, we can find commonality and outliers that may suggest opportunity. The convention of what is a stock or bond or the distinction of what is an industry matters. The classification of an asset, which at times is seemingly arbitrary, has structural implications. Whether rated investment grade or high yield or whether included in an index or excluded, the category placement will have real return impact. How a manager is classified by the Morningstar service, or even how a hedge fund identifies itself matters for relative performance. 

So when building a portfolio and discussing allocation decisions across asset class, managers or risk premia styles, think about the implication of your categorization. The breakdown of asset classes or subclasses will impact investment decisions and return.

Equity risk allocation - No change in exposure reduction view

It not a matter of like or dislike the fundamentals of equities in the current environment. When sentiment changes and volatility increases, reassessment of current exposures is warranted. However, concern about the macro environment should be increasing. Maintaining lower market risk exposure by more than half of core allocation from 60% to 30% or half equity beta exposure is appropriate. (The darker red signifies a stronger trend.)

Growth - While recession risks are still limited by any probability-based model, economic growth will be tempered in 2019 both in the US and rest of world. Earnings have not yet been significantly affected by growth, but forward expectations are now slightly biased downward.

Liquidity - Continued Fed tightening and expectations of tightening around the rest of the world serve as a negative for fixed income. High rates are starting to impact higher levered firms and lending. Make no mistake this is what central banks want. 

Risk Appetite - Higher volatility with changes in sentiment suggest market is moving to risk-off environment. Financial condition trends are pointed lower. With risk-off, harder to buy on dips so more downside follow-through.

Structural - Gridlock in government will negatively affect further tax reform and regulatory changes. Fiscal deficit is now pro-cyclical which will further affect rates.

Technical - There have been some key periods of divergence between equity style sectors. International and EM have actually been a place to hide in the near-term 

Looking over year-to-date, six-month, and three-month returns shows three distinct differences: The divergence between US and rest of world, the dislocation between large-cap and value, growth, and small cap equities, and the reversal of the earlier international underperformance. 

Can you improve on the 60/40 stock/bond allocation without changing the 60/40 allocation?

The classic 60/40 stock bond mix has proven to be a good core asset allocation. When in doubt, employing the simple 60/40 (SPY/AGG) asset mix as a base case has been an allocation that has performed well versus other diversification strategies. This allocation bias may be coming to an end. 

The gains from holding a US focused large cap equity and diversified bond allocation and not being further diversified across investment risk premia styles and international equity and bonds is a function of the recent performance and not special characteristics. Performance for both stocks and bonds is now off from the norms of the last decade. The correlation between stocks and bonds is moving higher. Volatility across equities and bonds is also trending higher. Something more defensive may be helpful.

Nevertheless, many investors are looking for a way to get defensive without a significant change to the asset allocation. There are simple defensive changes that can stick to a 60 percent domestic equity allocation and receive significant diversification benefit. Using the advantages of alternative index construction or smart beta can be a helpful simple strategy. (See Defense Beyond Bonds: Defensive Strategy Indices from SPGlobal.)

Smart beta strategies have performed well over a long period, but a better testimony of their current value will be with their ability to provide defensive benefit in a downturn. For those that want to maintain asset allocation and are not believers of active discretionary manager in any regime, the smart beta choices can offer some equity risk protection. First, the smart beta choices will change the mix of equity exposure, generally broadening the exposure away from large firms with momentum. Second, smart beta can focus on preferred characteristics like quality or low volatility that should provide defensive benefits.  

A tilt to long-only risk premia and away from market cap indices can preserve risk allocation while providing defensive characteristics. The same can be done with fixed income through reducing duration while maintaining credit exposure. A traditional 60/40 asset mix can be converted into a defensive 60/40 allocation. 

Fixed income choices - Move to further underweight

Current views on asset allocation in fixed income and credit are generally negative. The focus should be on holding shorter duration and cash investments. 

Credits spreads are widening because of both increased economic and financial risks. International bonds both DM and EM are facing dollar funding risks and slower growth. Long duration Treasury bonds show high risk even with recent rally. Underweight market allocation and risk weighing in fixed income and credit.

Spread widening can be costly - All is not well in credit land

It does not take much for an investor to have a losing credit trade on long duration bonds. The average duration on a long-term 10-year corporate is around 8 and current OAS spreads for triple-B corporates are 160 over Treasuries up from 120 earlier in the year. Half this move will take investors  back to levels seen in 2016 and wipeout all of the spread compensation for a year. This is not an extreme bet if we have any further erosion of equity prices or change in credit risk expectations, (See Corporate debt growth has exploded - The added macro shock sensitivity creates real risks.) Shorter duration corporates will be at less risk given their lower duration but the stocking up of credit for yield reaching can be painful if credit risks increase.  

Even if investors hold the bonds for the longer-run, the marking to market will impact portfolio values. Holding less risk and moving to cash is a valid alternative, but this will place any investor at a severe disadvantage of reaching return targets. 

Portfolio protection is critical, so holding alternative defensive strategies need to be replenished. Any futures or derivative swap product may still allow investors to receive the risk free rate with excess returns associated with other risk premia beyond credit. The amount of excess returns from alternative risk premia can be dialed to a level of volatility that can match bond risk. 

Credit investing was an effective investment choice when rates were headed lower, spreads were higher, and the economy was improving. A new environment of late business cycle risks, falling equity values, Fed tightening, and spread widening requires different thinking.

No diversification in Mudville - Time to try different risk premia styles

Diversification is usually thought of as a longer-term concept. Don’t worry if it seems like you are not receiving diversification in a given month or quarter. Think about diversification across a longer horizon.  Diversification also does not guarantee better returns for a portfolio. Negative diversification does mean that your losers will be offset with winners.

Yet, investors often look for diversification protection over short periods. If stocks are going down this month, they are looking for an offset this month. If stocks have had a bad quarter, investors are looking for something good this quarter. That is wishful thinking. Correlations change and the measure is about co-movement relative to mean values.

This year has not been good for diversifying assets like fixed income. Our simple chart shows returns for equities and some of the leading fixed income alternatives: the Barclay Aggregate, mortgages, long duration Treasuries, investment grade credit, and high yield. None have worked well at portfolio protection even though fixed income volatility with the exception of long duration Treasuries is less than half of equities. Investors are taking on a high degree of credit and rate risk during Fed tightening late in the business cycle. 

An alternative form of diversification is to breakout of asset class risk and switch to style risk that is focused on alternative risk premia. The concept of alternative risk premia is to isolate the risk within an asset class to some constituent components like value, carry, or momentum. This diversifies risk on another level beyond asset class or beta exposure. When blended across a number of premia, this diversification can be done with or without making a focused class decision.

Evolution and adaption: Trend-followers are constantly changing

Hedge funds styles, strategies, and firms evolve over time. The behavior of a hedge fund today is not the same as yesterday. These behavior changes are not because a manager has changed his style but because the environment, the tools, the regulations, and the ideas surrounding finance are different. 

Of course, many of the guiding principles for a hedge fund are the same. Value managers attempt to find cheap assets. Trend-followers attempt to find trends. The evolution is generated through changes in technology, the structure of markets, and the implementation of strategy ideas.  Technology implementation allows for cutting costs, enhancing skill, and gaining scale. The structure of markets requires managers to evolve. New ideas and knowledge help generate or improve skills.  

Managers who are not thinking how to adapt will see their returns deteriorate and ultimately fail. Technology not used is a lost opportunity or places a manager at a competitive disadvantage. Ideas not employed hampers skills. Avoiding adaption reduces opportunities and increases costs. Adaption is core to good hedge fund management, yet being adaptive to changes may not lead to higher returns. Competitors are doing the same thing. Adaption may be required just to stay even with other managers in the sector. Some structural changes may lead to lower returns

We have discussed the evolution of trend-following in the past, (see The evolution of trend-following firms to alternative risk premiums and quant shops), but the current environment requires more thought about firm evolution. Limited crises over the last ten years and greater competition means trend-following has seen a more constrained opportunity set. Managers have to adapt to exploit or enhance these existing opportunities and prepare for changes as we move further away from the last crisis.

The evolution of trend-following has followed a set of three intersecting paths: technology, structure, and idea generation. These intersect because some ideas can only be implemented if the technology is available, and some technology can only be used if there is a structural environment that allowed implementation. Investors need to ask how firms are addressing these intersections.

Technological improvements from computing power have been especially relevant for quant strategies like trend-following. The computing power has been directed into four areas: 

• The use of speed to test new strategies through back-testing - any idea is quickly testable.
• The low price for storage - any amount of data is easily stored and available for review.
• The ability to electronically trade and parse orders to reduce transaction costs.
• The ability to process operations and manage risk - process and overhead can be reduced and position knowledge is readily available.

Idea evolution has allowed for better return opportunities and risk management; however, the broad use of new ideas diminishes the marginal edge given to any one manager. The major ideas that have affected trend-following include:

• The risk management revolution including VaR modeling.
• The improvement of portfolio management including volatility targeting and equal risk contribution.
• The use of new statistical tools for teasing out time series behavior.
• The ability to engage in complex non-linear thinking like machine learning.   

Structural changes have reshaped the set of opportunities for managers:

• The introduction of new derivatives markets - Trend-followers have more markets to trade than before.
• Changes regulation that allows new products  - Regulation has allowed for new fund structures that change the investor base.
• Changes in policy affect price behavior - Changes in monetary policy has affected the behavior of rates which impacts trends. Changes in capital regulation opens new markets. 
• Changes in industrial structure - The concentration and behavior within industries affect price opportunities.

An assessment of how firms are dealing with change may provide answers on which firms will be able to come out on top in a changing investment world. Unfortunately, firm adaptation is not a guarantee for higher returns when we are in a competitive environment.

Blending risk premia and generating craftsman alpha

Alpha generation will fall when it is measured correctly through an appropriate benchmark. Alpha shrinkage over the last ten years is a measurement problem. Returns for hedge funds are a combination of the underlying risk premia styles employed and the skill of the manager. 

This shrinkage seems to suggest that managers generate little extra return through their skill, but there are other forms of alpha associated with forming a portfolio. This has been called "Craftsman Alpha" (See Craftsman Alpha: An Application to Style Investing). The crafting or forming of a hedge fund portfolio is a unique skill and can provide value no different than security selection.

The definition of craftsman alpha is still somewhat vague, but it will include all of the activities associated with portfolio management after a style choice is determined. Craftsman alpha will be the value-added from bundling and managing a portfolio of risk premia. 

We break craftsman alpha into four categories or parts:

• Risk premia style choices -
• Implementation of styles: Given any risk premia style, there are a number of implementation choices, asset restrictions, inclusions and exclusions, and definition differences, which determine how a style is generated. For example, a FX carry strategy has to determine the currencies to include, the rate to determine carry, weight constraints, and rebalancing to name a view. These choices, all under the name FX carry, can have appreciable return differs and can be classified as skill. 
• Portfolio management choices -
• Volatility targets; determining the overall risk of the portfolio 
• Rebalancing timing; determining when to reset the weights of the portfolio. 
• Sector and name constraints; determining maximum allowable exposures.
• Weighting scheme; determining the weights of exposure such as equal volatility weights vs equal risk contributions. 
• Execution choices -
• Mechanisms for minimizing transaction and trading impact.
• Dynamic Adjustment choices -
• If there are multiple risk premia in the portfolio, the decision process or mechanism for adjusting the portfolio weights.

A craftsman alpha discussion changes the focus from picking securities or risk premia to the process of managing a portfolio of risks; the strategy and tactical decisions of running a portfolio. Given there are no well-defined rules on how to create craftsman alpha, there can be significant variation across managers. These construction choices are the decisions of a craftsman and not scientist. 

  

Alpha production - As we get better at beta measurement, alpha will decline

A growing investment management theme over the last few years has been the incredible shrinking alpha. As investors gain more information on risk premia, there seems to be less alpha produced by managers. In reality, alpha production has likely not changed, but our measure of alpha has gotten more sophisticated so the skill associated with any manager seems to have declined or at least changed over the last decade. We can now tie what was previously thought of as alpha to specific risk factors. If alpha is tied to systematic risk factors, then it really is not alpha.

The measurement of shrinking alpha can be described in an alpha pyramid. As investors better define portfolio risks, the skill of the manager will shrink. It is harder to prove skill when we account for risk premia correctly. (See our previous post, The incredible shrinking alpha - Falling skill or alternative definitions?) It is hard to get to the rarified place of skill after accounting for risk factor premia. 

It can be affective to think through the process of moving up the alpha/beta pyramid. A stronger beta filter will reduce the number of managers who are special alpha producers. As we enhance our skill at measurement, the manager alpha skill has been more difficult to find.

If the majority of returns are associated with risk factors, there will be less room for alpha. If this is true, then building risk premia portfolios may better serve the diversification and return needs of investors. Find the betas that will enhance the return to risk of the portfolio and don't worry about finding that special skill manager. Of course, if you can find the high level manager hold onto him; that manager can indeed be very special. However, the search should be on finding the best risk premia mix.

25 years after Jegadeesh and Titman - The Momentum Revolution

Trend-following and momentum has always been an important part of hedge funds and alternative investing but it would be hard to say that trend-following was mainstream thinking prior to the early 90's. This was the high water period of the of market efficiency, but that thinking started to take a major change with the "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency", published in the leading Journal of Finance. There were other papers that discussed similar topics and the behavioral finance paradigm shift had already begun, but this was the one paper that many academics started to quote with increasing frequency about momentum effects. 

The paper was elegance was its simplicity. It showed that if you followed a strategy of buying past positive performers against a portfolio of losers, there would be significant excess returns. The tests were done using past returns not trend but the results transfer. It was not a paper about technical signals or moving averages. It just looked at past returns with significant look back.

We are now 25 years away from this path breaking work albeit it is unlikely that most academics or traders will hoist a beer to the authors in celebration. For core followers of trend, this is no big deal. The celebration of trend-following is much older, but for the mainstream this is as good as any place to mark a change in investment paradigm.

25 years later, momentum and trend-following are a core part of investment thinking. These are not just considered investment strategies but fundamental risk premia. The discussion has moved from thinking about ways to dismiss these risk premia to offering reasons for their existence. What trend-followers knew but may mot have clearly articulated is that behavior creates slower reaction to news. Biases drive trends. 

Nevertheless, some of the terms and language has changed to suit academics over older practitioners. Academics like to use the word momentum and askew trend. There is now a clear distinction between cross-sectional and times series momentum. The classic trend-follower will think the cross sectional approach is a form of ordering trend preference. No one uses the words technical analysis. Preference is for quantitative analysis and algos.

25 years into momentum and trend style acceptance, researchers have looked at an ever-increasing set of data over markets and time to show that trends exist. Of course, there is an ebb and flow with returns associated with these strategies but over the long run, you can go to the bank that the risk premia is present.

Can there be too many following this risk premia? That is, can popularity kill the golden goose of momentum? From a theoretical level, as long as there are trends in fundamentals, behavioral biases, limits to arbitrage, and uncertainty, there will be frictions that allow for trends. From a practical side, trend behavior and returns will change with the time length of trends, speed of reaction, differences in crowding, congestion, and liquidity. Momentum/trend returns will grow and decline which will force some to leave the strategy and others to jump in. There is a dynamic environment which will ensure that everyone cannot be a winner at all times, but for the patient, momentum/trend should work over the next 25 years.

Where do we stand after the October repricing?

The losses in October are well known. Now the question is whether these down moves will continue across styles, sectors, country indices, and bonds. The answer with few exceptions is the same. Market trends are pointed down and volatility is higher. For equity styles, short, medium and long-term trends are all pointing down. For market sectors, the only positive trend is with consumer stables, utilities, and real estate; the more defensive sectors. For country equity indices, the only strong positive standout was Brazil in reaction to their presidential election.  For bonds, short-term Treasuries offer some protection, but the longer-term trends are all down. 

In this world, cash is now something special. 

Managed futures beat both stocks and bonds over short-run, yet many are not feeling good

The investor pain from low correlation; you can be diversified and lose money. An investment can have a low correlation with equities and still have a bad month when equities decline. Low correlation is no guarantee of protection when markets reprice. Investor may believe in the diversification "free lunch" and it does exist, but it may not exist in the short-run or mean that loses will be avoided in down markets. 

Many are saying that the managed futures hedge fund style did not do its job, yet everything depends on your time perspective and what you expect from diversification.

Take a look at a comparison of recent performance. The equity markets sold off and there was limited protection from fixed income. Managed futures, as measured by a pure trend fund (CSAIX), provided diversification and positive returns over the last three months. The more diversified SG CTA index which includes a broad set of strategies called managed futures showed similar return behavior, albeit lower. Over the longer run for this year, managed futures subtracted value. 

The timeframe matters for performance review. One month tells us little about a strategy. One year is better, but not convincing of strategy value, yet every investor is forced to pass judgment as quickly as possible. For the month, managed futures may not seem that bad. For the year, a different conclusion is reached. Placing too much weight on either time frame is dangerous. 

Expectations for correlation also matter. Correlations change through time and are different based on the time frame reviewed. The benefits of diversification are time dependent. An investor's feeling about the quality of an investment is very much dependent on the time frame used for comparison and these factors can be subjective.

October reinforces the not often discussed problem of determining how much time is necessary to measure success or failure for diversification. Good investment time perception means being a patient investor, and patience cannot be found in one month of performance, but how long is enough?  

Hedge fund performance - Limited risk protection for the month and year

All asset classes were hurt with October performance. There is not much investors could have done to protect themselves during the month, yet there is a feeling that hedge fund managers should have done better for the month and the year. There is a nagging question of whether hedge funds met performance expectations. Investors could form benchmarks for all managers, but finding the right benchmark is not easy, so a simple rules of thumb may be helpful. 

A simple rule could be ask whether the hedge funds were in what I call the zone of diversification. An increase in hedge fund exposure usually comes from a decrease in equity or fixed income allocations, so a simple performance rule should be that hedge fund returns should fall somewhere between equity and fixed income index returns. Hedge funds will have an equity beta that will be less than one, but should be able to outperform a portfolio of bonds. Volatility will be less than equities and likely greater than an intermediate bond portfolio and the correlation with equities will likely be higher than bonds but lower than other equity alternatives.

When we look at performance for a given month or for the year, the loose rule of thumb is that performance should be between stocks and bond returns. For October, hedge funds did better than equities (SPX), but generally did worse than the Barclay Aggregate. Performance was negative across the board but returns were better than holding an equity index. For the year, hedge funds have underperformed bonds except for fixed income relative value and the HFR absolute return index. For pensions trying to hit return targets, this has been a difficult year. While not perfect, this form a bracketing provides a quick judgment on hedge fund performance. 

The October repricing causes low signal to noise, limited trends

When markets reprice risk, it is not fun being a trend-follower. Long equity indices were a crowded trade and few made money when the early October reversal hit the markets. Fast traders were able to exploit the move, but a bounce off the lows hurt intermediate traders. Bonds were hit with the cross-currents of flight to safety against the continued threat of growth and Fed action. Currencies were hit with this repricing and not a place of profit able trends. 

Commodities were not immune to this repricing of risk. Precious metals moved higher on the safety factor but the base metals are not pricing in slower economic growth. The energy complex is actually in a greater free fall than equities and caught many by surprise.

The spike in volatility, while not as strong as February, has a major impact on trend-followers. Many now position size on volatility and target portfolio volatility. The result is that higher vol will mean smaller positions and less chance at performance recovery in the short-run. A ten percent down move followed by a 10 percent up move will generate a negative gain. This problem is compounded if higher volatility leads to smaller positions during the recovery phase.

Our sector trend analysis sees some opportunities, but the low signal to noise level suggests that at this date, return upside will be limited.

Managed futures - No crisis alpha in the short-run

Past performance is not indicative of future results

Market performance for October was sobering. Investors were complacent to volatility and the fact that markets correct. The speed of adjustment hurt the average managed futures manager who was not able to get out of markets which repriced at the beginning of the month. Although the month ended with some improvement from return lows, there is little to celebrate. 

Managed futures, on average, performed better than equity markets but this is little consolation when returns were still negative. The combination of trading all major asset classes and being able to go both long and short provides a high degree of diversification, but crowded long equity trades dominated performance. Additionally, all major asset classes repriced risk, so there were no clear trends to exploit. 

Investor expectations for managed futures were not realized, which is a problem. So what should be the right expectations for momentum/trend during equity reversal months? Generally, in the short-run it is unlikely that trend-following returns will be negatively correlated with equity returns. Negative correlation between equities and managed futures only comes over time with sustained declines. Managed futures are generally uncorrelated with equities. Investors will gain diversification, but the form is unclear.