Tuesday, March 19, 2019

Risk premia investing versus hedge funds - Worth a look

As we better understand the return generation process, we are able to dissect any set of money manager or hedge fund returns into its component parts. At a high level, any money manager can be divided into a set of risk factors or premia and alpha or skill. As a general conclusion, researchers have found that as investors get better at identifying risk factors, the size of alpha declines. We are able to attribute more returns to specific risks so the amount that is leftover as skill declines. 

Additionally, as we find that hedge funds returns are associated with specific identifiable and repeatable risk premia, there is a greater desire to change the fee model based on the risks taken. If the majority of hedge fund returns are associated with compensation for specific risks taken, the idea of paying incentive fees seems odd. The incentive fee eats into the return compensation for risk. The incentive fees should be paid on alpha or the uniqueness of return generation and not on the risk exposures. 

Investors should pay for and celebrate alpha skill, but pay a different price for specific risk exposures. We are not arguing that money management for specific risk premia should be free, nor should the dynamic management of risk premia be dismissed as easy work, but there should be a better awareness of the different types of work associated with fund generation.

There is now a wide-range of alternative risk premia (ARP) that can be obtained at relatively low cost through the swaps market. A close look at some of these risk premia portfolios suggests that they provide similar and in many cases better returns than what can be received from hedge funds. These risk premia can be structured as a rules-based investing at a price that should be lower than the normal fee schedule.

We compared the average return of ARP indices across asset classes and multi-strategies for asset class as well as an average of these two HFR ARP categories against some broad-based HFR hedge fund index categories. While not an extensive time series analysis, the recent returns show that ARP average returns are comparable and in many cases better than average hedge fund returns. The mapping between the hedge fund indices and ARPs has not been done through regression, but the general concept shows that bundled risk premia can give the same return profiles as hedge funds. 

ARPs can be used as a core strategy for liquid alternative investing and hedge funds with specialized skills, or unique strategies that cannot be easily replicated through rules can serve as satellites. Invest in the best hedge funds, but if they cannot be found, use alternative risk premia delivered through total return index swaps.

Monday, March 18, 2019

Get out of the binary world - Focus on probabilities, baby!

One of the key problems with decision-making is that it is often simplified into either/or choices. "Yes/no", "Go/No-Go", is how we often focus our attention and make decisions. Life is easy when problems are framed as either black or white. For example, the Fed will either tighten or not tighten. Employment will either increase or decrease. The stock market will either rise or fall. These are phrased, in the end, as binary actions. Seldom will you hear a market pundit provide anything other than a binary choice problem. Forecasting is often viewed as being so hard that getting just the direction right may be more than enough to be successful. Unfortunately, framing uncertain forecasts as a binary problem is both near-sighted and flawed. 

Thinking in a binary world does not allow for a richness of details and choice in forecasting. Thinking about forecasting in terms of probability is more important. Don't frame the problem as, "I think the Fed will be on hold." Think or believe in something like, "The probability of a Fed "no change" at its next meeting is 70 percent." Placing the forecast in terms of probabilities changes what action can and should be taken. This is even more critical when looking at questions that can have a range of possibilities. You could say, "The change of employment growth being below 180,000 and the market expectations is X% and above 180,000, (1-X)%. Probability estimates can be done for a range of employment numbers to form a distribution of forecasts. This is harder but it allows for more investment insight.  

The response to a forecast that is a flip of a coin is very different from a belief that the chance is 70% favorable. In the first case, it may not be worth taking a bet. In the second case, the size of the bet may be large because the odds are favorable. By thinking in probabilities, the size of the bet will be more effectively managed. This applies even to what may seem like a yes or no question. It takes time and effort to think outside a binary decision world; however, once a pattern of thinking is established, the process becomes easier.

Many argue that being right more than 50 percent is not the measure of a good trader. Good traders can have a success rate below 50% and still make money. That is absolutely the case. Good risk management can offset forecasting errors. Holding winners and cutting losers can allow for lower forecasting skill, but increasing forecasting skill will only improve and not detract from performance.  The best way to improve this skill is to focus on the odds of forecasting. As you receive new information, there is a shift in the probabilities, not just a shift to either yes or no. Stop binary thinking and focus on the odds.  

Tuesday, March 12, 2019

Naturalistic decision-making permeates investment world

Gary Klein is one of the great researchers in practical decision-making; however, he has been overshadowed by the behavioral bias revolution and the more popular work of Nobel prize winner Dan Kahneman. That is unfortunate and should be rectified. Klein focuses on naturalistic decision-making; the fact that decision-making in real life is significantly different than anything in a controlled environment.

In the natural world, there is value with shortcuts and intuition that would be scoffed at as biases by those who work in controlled research environment. Biases may exist, but some are a response to settings in the real world. Experience from the past exercise of judgment is useful for making more efficient and quick decision when time and uncertainty are critical factors. For those interested, Klein synthesizes natural decision making in a short article

Natural decision-making is often representative of those who are either discretionary or systematic traders. A natural decision-maker is flexible and fluid with his decision and does not fit a theoretic foundation like maximizing expected utility based on assessing all probabilities. The discretionary trade is a natural decision-maker who uses his set of experiences to drive action when faced with new situations. Many investment decisions may not easily lend themselves to traditional decision analysis. Hence, intuition is valuable. We make the distinction between countable and non-countable decisions. A problem that can apply large amounts of countable data is more efficiently solved using quantitative techniques. Problems that are not able to use countable data require different skills and decision-making.  For example, reacting and profiting from central bank commentary is more art than science and requires an ability to connect events with future responses differently.

Nevertheless, even systematic traders may have to use experience, rules of thumb, and some shortcuts in order to effectively react to fast moving uncertain events. Any model building may require throwing out some information and limited the analysis to a manageable process.

Building models is a complex process that requires speed to offset uncertainty. Assumptions have to be made. Shortcuts taken. This is based not on expediency, but on a desire to get things right. Take the simple example of a trend-follower who is faced with limited information, volatile markets, and a requirement to control risk. It may be more effective to focus on analysis of price over trying to incorporate all alternatives. This is especially the case when the fundamental information is not readily available or provided with a lag.

While some have viewed natural decision-making at odds with behavioral biases, we argue that reality by be more nuanced. In a complex and uncertain world, there is a necessity to find useful shortcuts based on experience to increase decision efficiency. These approaches need to be scrutinized for their effectiveness but should not be dismissed as inappropriate solely because it does not fit the steps outlined for formalistic decision-making.

Monday, March 11, 2019

Market Tilt or Timing - Is there a difference in forecasting?

At a recent conference, I heard a large money manager say the following, "We do not market time, but we do take market tilts." Unfortunately, no one was able to ask the manager to clarify the difference between tilts and timing. Aren't they both forecasts?

I have used the phrase market tilts, but I am not sure that investors make or understand the distinction between the two concepts, timing and tilts. Although there are subtle differences, clarification of these terms is important. 

Market timing is the adjustment of exposures in a portfolio based on forward-looking expectations. It is a time series forecast. Market tilts will be an adjustment of weightings or exposures based on the characteristics of the asset, strategy, or premia. It can also be a change in weightings based on the market environment regime. Market timing is analogous to trend-following while market tilts are associates with cross-sectional analysis. Both may require some view past behavior repeating itself.

A portfolio of alternative risk premia may start with the assumption of equal volatility or equal risk contribution. There is no view about the risk premia other than they may have different volatilities. A tilt suggests that the weighting of the portfolio may differ from some volatility equalization.

--> The characteristics of an alternative risk premium may suggest higher returns or risk. These underlying characteristics may suggest a tilt. For example, some risk premia may underperform during different stages of the business cycle. Other risk premia such as FX carry will underperform when all global rates are compressed or there is a significant dislocation in global markets. Still other risk premia may be sensitive to spikes in volatility. Some ARP are more defensive and will do better during economic "bad times". 
These conditional views may be considered forecast but should be grouped differently than a times series performance forecast. Nevertheless, we view that tilts are forecasts and should be give the same level of care and any timing decision.