Fixed Income Factor Investing - Part III - The Factor Model

 

Fixed income factor investing has been extensively tested, so investor have a good idea of the key risk relationships across, value, carry, volatility, momentum, and size. The risk factors measured are statistically significant, but the amount of variation that is left unexplained is high and there is room for skill to improve long/short investing.  

Different risk factors variations such as value, momentum, volatility, quality, and carry all show significant return to risk and positive Sharpe ratios for buying the best quartiles across several studies covering different time periods and factor representations. Long/short portfolios show strongly positive Sharpe ratios often above 1.

The risk factors are sensitive to increasing and decreasing macro variables such as growth, inflation, real rates, volatility and illiquidity so that adding macro tilts will improve return potential. While trading in credit is more difficult than equities, the framework for measuring risk and return opportunities provides value for investors.      

Fixed Income Factor-based Investing - Part II - The New Versus Tradition Approach

 

Fixed income factor investing has changed how bond managers look at and measure risk. However, it is not a replacement to traditional approaches which have served as a core framework for classification. There is a place for both with factor investing providing a common framework that links fixed income with other asset classes.

Factor investing applied across asset classes allow for a unified framework for the discussion of risks. Whether equity, currency, bonds, or commodities, there are common factor approaches that can drive discussion, measurement, and assessment of risk. Value, quality, size, momentum, carry, and volatility as well as other factors are measurable everywhere, so there is no need to think of bonds as special relative to other asset classes. Of course, a bond is a different contract for cash flows; nevertheless, a traditional approach to bond investing offer ways to classify bonds which will improve risk factorization. 

The traditional framework broke fixed income into three parts, interest rate risks associated with duration, creditworthiness as measured as spread compensation for default risk, and liquidity-based measures for trading in an OTC dealer market. The credit analyst focuses on spread analysis after controlling for underlying Treasury benchmark risk. The traditional approach is tied to risk assessment relative to ratings and liquidity cost scoring measured by individual, common, and group classification: 

• Individual bond characteristics: size, age, time to maturity, coupon, carry, and premium
• Common characteristics: size of issuer sector, size of country, credit rating
• Group characteristics: Treasury, IG, HY, inflation-linked, subordination, zero coupon, currency, financial, supranational, Agency (government-related) 

The factor approach does not break this connection with ratings but focuses on enhancing the measurement of risk characteristics using the power of cross-sectional risk premium sorts. The power of cross-sectional analysis with more effective bond databases makes for effective risk sorting in a manner consistent with equity markets.  

Factor Based Investing for Fixed Income - Part I

Risk factor investing is being applied to all asset classes. The application to fixed income has changed how fixed income managers think about risk and how they build their portfolios. This move to risk factor investing links bonds and stock through common factor definition and measurement.

At some level, the risk factor approach is not significantly different from more traditional bond investing; however, using risk factors allows for codification and commonality of thinking about across asset classes.

There is a size effect associated with total debt outstanding which is a proxy liquidity effect. Value is tied to price variation such as option-adjusted spread. Momentum is based on past return behavior. A low volatility effect associated standard deviation, and an interest rate and liquidity effect.

The strong advantage of risk factor investing is that it can effectively characterize the risks faced with holding any bond.

 

9, 7, 6, 4 - what is the right number for Fed rate increases?

There has been a new rate hike forecast from JP Morgan that there will be nine straight Fed hikes. This new forecast is greater than the Goldman Sachs 7 hikes, Morgan Stanley 6 hikes and the many forecasts for at least 4 hikes. The forecast targets are increasing quickly, but there seems to be a growing consensus for a hike at every Fed meeting in 2022. There are Fed meetings in March, May, June, July, September, November, and December with four Summary of Economic Projection meetings on the March quarterly cycle. 

Treasury 2-year rates are hovering around 150 bps, about 50 bps higher than 1-year Treasuries. End of the year Fed funds futures are at 150 bps while eurodollar futures to March 2023 are at 200 bps and 175 bps for year end. Hence, the 9 and 7 forecasts are aggressive versus current market discounting.  

These hike at every meeting forecasts seems aggressive even though the Fed is behind the inflation reality. Economic numbers will vary through the year and there does not seem to be a consensus to solve the inflation problem especially if growth starts to wane. The core Fed secret is that higher rates to tame inflation are also supposed to slow economic growth. Any success on the inflation front coupled with slower growth is likely to be met with Fed caution to delay action. The go-no-go Fed action will be the market trades driving fixed income.

International diversification - Depends on the business cycle

There has generally been the view that as global markets have become more globally integrated the gains from international diversification have diminished. The evidence supports higher beta from global integration, but data also suggest that there is still benefit from international diversification. (See "To diversify or not to diversify internationally".) The correlations are highly variable and business cycle dependent. The pairwise correlations will increase during global recessions and then move back to their older long-term relationships when the business cycle stabilizes. Hence, there will be breaks in the correlation relationships through time.

This relationship is consistent with a single global shock having a common effect on all risk equity markets. As the importance of a common shock declines, correlations will fall. 

The correlation across country indices will also be related to the composition of the country index. When there are similar industry weights, there will be higher correlation. Generally, industry correlations are lower than country correlations and will provide greater diversification especially for less integrated EM markets.

While international diversification benefits have declined with market integration there are still opportunities to exploit differences for return and risk management. 

Goods versus services inflation and the transitory problem

 

Fed and market behavior is closely tied with the issue of whether inflation is transitory or not. The Fed does not like to use the word transitory since it has been burned by their poor inflation forecasts. Instead of inflation declining, it has continued to move higher. The supply chain story has unraveled. The return to normalcy story has been shredded. The measurement problem between pre- and post-pandemic inflation is suspect now that we are in 2022.

Inflation is likely to go down in the second half of the year given the excessive increase in goods prices and the reduction in stimulus. Of course, this is unlikely to happen immediately if producer prices continue to increase at a higher rate than consumer inflation. 

However, the issue of further service inflation increases seems likely if there is a need to pay higher wages to workers. The lower services inflation has been dampening the overall inflation rate. 

Employment costs are running higher albeit with higher measurement volatility. If higher wages are necessary to entice workers into the labor force or to convince them to come to the office, we will see a change in the inflation mix - lower goods and higher service inflation. The overall mix may be lower than current prints but above the target level.

The dirty secret is that inflation will come down sharply if there is a decrease in aggregate demand. For this to happen the Fed must switch from a growth bias to an inflation control bias. 

Flows and bond ETFs - Derisking before the Fed

What has been happening with fixed income investing now that the Fed is ready to raise rates and inflation as continued to move higher? As expected there has been a flight out of nominal assets that cannot adjust to higher inflation and will decline in value with rate increases. Since the beginning of the year, billions have flowed out of LQD (the investment grade benchmark), HYG (the high yield benchmark), and EMB (the EM bond benchmark). The outflows have been a significant percentage of assets under management. Trading volume is higher and put option volume has also increased. 

The somewhat odd investor behavior is that equity inflows have moved above trend while the cumulative bond flow peaked earlier in January. The Fed may be increasing discount rates, but investors believe that earnings may increase and or corporations will be able to control product prices in the face of inflation. 

Market message - Fed behind the curve and needs to play catch-up

The market has given the Fed a message, but it is not clear the Fed has heard it. The U-shaped 2-year Treasury yield tells the story - strong decline as a response to COVID in March 2020 and now a complete reversal before the Fed has taken any action. The curve tightening before any Fed action again sends a market message.

Nonetheless, with a Fed action expected in March and some economists forecasting up to 7 rate hikes in 2020, the question is whether the market has gotten ahead of the Fed and is being too aggressive. The macro opportunity is learning to play the change in market expectations against policy reality. This is something that has been missing from fixed income macro trading for most of the post GFC period.

 

Credit performance masked by duration

 

Spreads for high yield and investment grade bond indices are starting to move higher, yet the overall levels are still around pre-COVID levels. Debt risk will increase from higher inflation uncertainty and a move by the Fed to start raising rates, but portfolio risks are still limited. Nevertheless, a more uncertain earnings and equity environment will spillover to credit markets.

Any spread widening for high yield indices will have a lower total return impact. The investment grade ETF benchmark LQD has a modified duration of 9.66 while the benchmark HYG has a modified duration of 4.24 years. The ICE BAML high yield benchmark has a modified duration of 3.78 and the investment grade index modified duration is at 8.7 years. Lower rates bonds rated CCC have even lower duration. A rate rise will have less of an impact on these lower-rated debtors; however, the high yield issuers will have to roll their debt sooner, so there are heightened financing risks.

Quality factor variables as diverse proxies

 

Looking beyond value risk factor requires more digging into financial accounting. The quality factor is a unique alternative to value and provides another effective way to sort firm, but it comes at a price of more work and interpretation.

There has been significant work to extend the 3-factor Fama-French (value, size, market risk) framework to broader 5-factor and 6-factor frameworks that adds (profitability, investment, and momentum). Others have tested and employed momentum, quality, and volatility as additional core risk factors. We have discussed how different factors have different degrees of complexity, see "Which investment factors are hard to measure? Risk factor measurement as art". 

Quality is one of the more difficult factors to measure because it has several characteristics used for its description: profitability, financial strength, and stability. Hence, quality is harder to measure than a simple factor like momentum, volatility, or market risk. The proxies or ratios employed to describe quality include profitability, ROE, ROA, net income, asset growth, payout ratio, debt to equity, and sustainable growth. These are measured for current data or for some rolling average period like five years. 

In all cases, since there is not clear agreement on what is quality, there can be different sorts for any set of stocks and different return results when the quality risk factor effect is presented. While the quality factor is a way to "split the difference" between value and growth, there is significant room for interpretation on this risk factor. Nonetheless, the quality factors needs to be explored more deeply as a way to breakout of the value/growth discussion.

"Never bring data to a story fight..."

"Never bring data to a story fight..." - Prof Peter Dodds expert on narratives 

This quote is a great commentary on the power of narrative and the buzz kill that data can do to disagreement across narratives. A significant amount of time and effort with investing is associated with telling good narratives. The narrative attempts to provide a clear mental and emotional story. Narrative drives sentiment and interest in stocks and other investments. Narrative serves as a means of condensing a large amount of information into a clear picture as simple as a few words or a long written commentary. 

Phrases like "bear market", "correction", "tech rally", or "Fed behind the curve" are the simplest narratives that tries to convey a lot of information without any data. Data eliminate simple stories and closes discussions. Facts don't have feelings, so narratives are debated through alternative stories.

For the quant, data is more powerful in the fight because it is so precise and often without ambiguity. Of course, it needs interpretation which flows back to the issue of narrative, but facts are clarifying. Many would like to ignore the facts and keep the narrative, but in the precise world of quantitative investing, data remains supreme. 

“Science is the belief in the ignorance of experts.”

 “Science is the belief in the ignorance of experts.” -- Richard P. Feynman 

Macro investing is the belief in the ignorance of central bankers and policymakers...

I have always liked the quotes of Prof Feynman. His quotes have a universal quality and do not just apply to physics which is why I have taken liberties and applied his quote to macro investing. The great macro opportunity is not based on central bankers having the right monetary glide path, but bankers have ignorance with the facts surrounding them. 

From the Fed's FOMC minutes we find there is no consensus on policy choices nor on the facts presented. The Fed has not ended their emergency QE4. It is only slowing and soon to end, so liquidity is still being added to the economy. Given all their staff economists there is no agreement on when or how much QT should be undertaken to return to normal. 

There is not even agreement on the raising of rates. Is the economy so fragile that it cannot withstand a 50 bps hike? Is the economy so fragile that cutting $40 billion from their balance sheet each month for the next year will lead to instability? $480 billion from a $9 trillion balance sheet or approximately 5% of the total and 10% of the liquidity added since March 2020.

Assuming policy ignorance is what will allow many macro investors a chance at big money.

Moscow Rules - Good for traders

 

With all the current tensions surrounding Ukraine and Russia, it is clear the Cold War is back. Perhaps it never ended. That older period reminds me of the rules that CIA operatives employed when stationed in Moscow. Their tradecraft was known as the "Moscow Rules" and is the staple of many spy movies. 

Here are the Moscow Rules from a CIA operative who lived in that most dangerous city during the Cold War: 

• Assume nothing.
• Never go against your gut.
• Everyone is potentially under opposition control.
• Don't look back; you are never completely alone.
• Go with the flow, blend in.
• Vary your pattern and stay within your cover.
• Lull them into a sense of complacency.
• Don't harass the opposition.
• Pick the time and place for action.
• Keep your options open.

If you look at the rules closely, you could say that they would be appropriate to follow if you are a trader. You can still have a quant strategy but follow the Moscow rules with your trading and business behavior. Nothing wrong with having good relations with competitors and the street, but always remember that everyone is looking for an edge.

There is no question that brokers, competitors, and quants all want your information to pattern your behavior and front-run your activities. Your flow data is important. Wy do you think firms pay for it? Looking for patterns with big and or smart traders is critical if you are on the other side of the market, and you don't want to be picked-off or steam-rolled. 

The Moscow Rules are just another variation of the great book Only the Paranoid Survive by Andy Grove of Intel. That book was published in 1994, yet it is still fresh. Andy Grove focuses on the day that big changes arrive. Moscow Rules focuses on the tactics to be ready for the daily challenges in a competitive market.

Which investment factors are hard to measure? Risk factor measurement as art

I remember a discuss with one boss who asked for the beta of an investment in our portfolio. He told me to look it up as if there was a book of betas. I told him we would have calculate it. There was no single number that is used for beta. I still remember the odd look of frustration he gave me; you have got to be kidding me. 

The same frustration can be applied with risk factors. There are Fama-French factors that are "standardized", but there are also several proxies and alternative ways of calculating these factors. Some are easier than others, so investors must ask about the specifics for calculating any factor. 

Size may be the easiest to measure since it focused on market capitalization. Momentum also is an easy factor to measure with the lookback and delay being the key features. History has proved that the momentum look-back is stable. Volatility is another factor that is intuitively easy to measure and only has a limited number of choice variables. Investors can decide on standard deviation, beta, or risk after accounting for beta. Dividend yield can be as easy as a sort of high dividend; however, there are variations on risk-adjustments. 

Complexities increase on when or how rebalancing is conducted for these factors. This structuring can add significant transaction costs.

The more difficult factors to measure are value and quality. While originally these were simple measurements, the level of complexity or sophistication with calculating value and quality through accounting number proxies has increased significantly. 

For value, price to book and earnings to price are the standard measures, but there are also value measures with sales, earnings, net profits, dividends, and cash flows. There has been value measurement proliferation especially during these periods of value under-performance. 

Quality cannot be measure directly, so there has been a growing number of alternative measures including ROA, ROE, earnings stability, growth, strength of balance sheet, accruals, and cash flows. There is a lot of room for quality interpretations. 

So, like the old question of asking about beta, remember that all factor measurements are not the same.   

Source:Quality Factor in Sector Investing

Is this a molecule crisis? Commodities continue to surge with backwardated futures

“I’ve been doing this for 30 years and I’ve never seen markets like this. This is a molecule crisis. We’re out of everything, I don’t care if it’s oil, gas, coal, copper, aluminum, you name it we’re out of it." - Jeff Currie Goldman Sachs commodity analysts

These markets can be described as super-backwardated with textbook shortages. If you cannot get inventory or believe there is a threat to your normal levels, you will pay a premium for convenience - the convenience yield with current prices higher that back month futures. There is no normal carry with these markets in the front month futures.  

We have referred to this as the switch from just-in-time to just-in-case inventory management. (See "From just-in-time to just-in-case commodity markets") It makes even more sense if price trends are going higher - a positive feedback loop. Hold inventory based on the threat of stock-outs and receive a gain from higher trends.

The cost of holding inventory is also insanely cheap if there are negative real interest rates. I don't want to use the word hoarding, but everyone who needs commodities want to stockpile in this environment which is one of the problems in an inflationary world - expectation start to adapt to a new environment.

Note that the commodities have underperformed over the last five years. The stockpiling mentality has taken hold in the last year. The upward trend accelerated with the surprise increases in inflation. Geopolitical uncertainty associated with Russia has only added to the stockpiling mentality.

These price increases are not likely going away in the current macro environment. Real rates are at extremes and a set of 25 bps Fed increases is not going to change this environment. While China is not on the same high growth path of the last two years, it is being offset with the potential for better growth in the rest of the world. Of course, this is more of a hope than reality given the declining growth estimates of the IMF last month (4.4% from 4.9% for global growth). 

A greater long-term problem is the capital expenditures in extractive industries. These are not good industries in an ESG world. Traditional agriculture is also on the list of less ESG friendly investing. Commodity super-cycles are based on less capital expenditures in key commodity sectors. 

"History is particular, economics is general."

"History is particular, economics is general."

- Charles Kindleberger 

Economists love to generalize even if at the extreme when the sample size is one. Take any event and an economist will try and find some commonality with theory and past events. It is what they do. Behavior repeats and the job of the economist is to find the repetition and suggest predictions about future events.

Historians often look to the particular and unique facts about an event. Generalizations can be boring. Being able to find the unique catalysts is the exciting part of history. There is generalization but the focus is on getting the details right. 

Some investors are generalists while others look for uniqueness. Quants are like economists who generalize to find repeatable patterns in past events to make predictions on the future. Deep value investors will act like the historians that are focused on the particular that cannot be generalized. 

Playing the likelihoods during Fed changes

One of the big problems of macro investing is determining the odds when there are only a limited number of events. Macro investors often must make judgments when the sample set is well below the number thought appropriate by a statistician, the magic N=30. 

It may not always be pretty, but you must extrapolate with what is available based on some theoretical foundation. Investors form rational beliefs, not rational expectations. Beliefs can differ based on the same data, but only one can be correct as events unfold. 

Quantitative easing and tightening are a perfect example of the sample problem. We have four easing, two QE taperings, one quantitative tightening, and one QT tapering. This is little to work with, so reality has to be coupled with theory. Nevertheless, JP Morgan has provided a good visual as a guide. A single sample requires our theoretical intuition.

The general view is that stock returns will be weak and 10-2yr spreads will decline. The past is not destiny, but the market is already following a pattern of the past from the sample of one. 

 

Cryptocurrencies - What are factors are they related to?

Determining what are the factors that are related to cryptocurrencies is not easy because most of the evidence suggest that cryptos are independent of other assets, risk factors, and macro-variables. This asset class has a mind of its own. The most exhaustive study shows very little relationship with independent variables that impact other asset classes, see "Risks and Returns of Cryptocurrency"

The table below summarizes the research. Perhaps some of the results are related to the high crypto volatility and will change as the market matures. One year in the life of crypto currencies may match years for other asset classes; nevertheless, there is little evidence supporting the idea that traditional risk factors can explain crypto behavior.

The complex ecosystem for gaining crypto exposure

The landscape for cryptocurrencies is getting more complex not simpler. Complexity comes from the process of experimentation with how to employ blockchains and the development of new ways to enhance the usage of cryptocurrencies as a store of value and medium of change. Like many industries, growth will lead to winners and loser. There have been significant failures, hacking, and fraud. There has been significant adoption my many major corporations and new payments experimentation. There will be creative destruction as users and usage sort out how to best exploit this technology. 

However, growth and maturity also lead to financial innovation and complexity on how to access, finance, and trade cryptocurrencies. Innovation will attempt to reduce the cost of trading and gaining exposure. Some of these developments are related to the regulatory environment. Innovation will also occur in an effort to reduce the cost of regulation and avoid market impediments for usage. At the same time, regulators will attempt to serve in a role of facilitating the common good through helping to form standards for usage to protect investors. The goals between investors and regulators should be aligned; however, in a rapidly changing market, regulator may be perceived as slow moving versus the crypto innovation crowd.

A simple financial map (from CAIA blog) for accessing crypto exposure shows the market broadening. There is direct, traditional, and futures markets available for investors; however, not all are the same and there exists inefficiencies in pricing across these marketplaces. Investors must focus on these cost and pricing differences. 

Is Bitcoin (BTC) "digital gold"? Ethereum (ETH) "digital oil"?

Bitcoin is beginning to be referred to as "digital gold" while Ethereum (Ether) is referred to as "digital oil". These are strong commodity metaphors that can be useful for investors. These turns of the phrase are based on their fundamental use and provides a framework for where their growth may be headed. Of course, metaphors are not perfect, but they do provide a point for discussion.

Bitcoin is mainly a store of value and has taken on the features of gold for many investors. Gold has been the alternative to fiat currencies. For many, the limited supply relative to fiat currencies make bitcoin a worthy substitute. It also has the characteristics of gold in that it is not easy and cheap to use as a medium of exchange. It can fill this exchange role given its dominance in the marketplace; however, other cryptocurrencies may do it better. The metaphor breaks down when the volatility of Bitcoin is compared with gold. A chart of the differences makes gold look like it has flat-lined over the last few years.

Ethereum is general purpose blockchain developed for smart contracts and Decentralized apps. As a network and platform, it allows for innovation and other alternative uses within the crypto ecosystem, smart coins; consequently, it has characteristics of a "fuel". The platform allows for conversions at low cost. This ability to be used as a platform for other medium of exchange activities suggest that it may surpass BTC as tool for crypto growth. 

To further push this metaphor, holding BTC and ETH is like holding a basket of commodities. Both have unique value. 

Crypto correlation - no clear relationship with hedge funds and equities

 

Cryptocurrencies and crypto hedge funds have a return performance life independent of other asset classes and strategies. This is one of their clear benefits but also the reason for why many investors have a problem with crypto. It is not clear what are the drivers for return. Certainly, crypto has moved higher with the stock market and has gained from the excess liquidity across global markets; however, finding independent drivers for price has not been easy.  Some simple analysis from FactorResearch tells the story. 

The correlation between crypto hedge funds, the S&P 500 and the top 50 hedge fund index shows both negative and positive correlation over the last six years. The correlation has ranged between -.6 and .8 with more recent numbers again closing in on zero. 

However, the returns for crypto hedge funds seem to be driven by Bitcoin beta. These hedge funds have the feel of long-only investments with limited downside protection. 

Applying known investment strategies to crypto asset makes sense, but it cannot be expected to have the same return patterns.

The continued search for yield - You cannot have everything

 

I’ve never heard such a chorus of repeated phrases such as “fixed income replacement” and the “new 40.”  - John Bowman CAIA comments at Miami hedge fund conferences

The drumbeat continues for changes in the 40% of the classic 60/40 stock/bond mix. Dump the fixed income and get some alternative investments. This alternative theme has been around for years but has increased in intensity - don't think of hedge funds as high-performance strategies but as substitutes for the low performance bond portion of an asset allocation. 

Some have taken this anti-bond view to an extreme, see "Endowments and equity factor - Just too much exposure?", yet there is still an inertia with many concerning fixed income. It has been a good hedge and many think it will continue to be a good hedge. The facts suggest otherwise as the stock/bond correlation has turned positive.

The problem is that investors cannot have everything with their fixed income. Real rates are negative and there is little near-term improvement. Inflation may revert from current highs, but without a significant increase in nominal yields, real yields especially for short maturities will be unattractive. 

A combination of low yields, negative returns, and a positive correlation to stocks make alternatives much more attractive, but there still needs to be a focus on the switching of risks. 

Hedge funds need to show positive real returns if they are to be an effective alternative. Right now, there is a five percent inflation hurdle for alternatives. This seems like an easy threshold to beat; however, alternatives still must deliver. If there needs to be a real return as compensation for risk, the nominal returns should be well north of the 5% level. 

Fixed income Treasuries are usually a liquid investment. That assumption has been tested in March 2020, but generally it still holds. Moving to alternative investments will have a liquidity cost that needs compensation.

By most definitions, moving out of Treasuries or liquid bonds will require taken on more volatility and increase investor risk. Anything other than Treasuries will require taking credit risk. 

There is a continued search for yield, but investors should not just look for close substitutes. The search for yield must include appropriate compensation for risk and liquidity.

Equity duration and the current sell-off - all about timing and discounting cash flows

 

There has been some compelling research work that focuses on the timing of equity cash flows, or equity duration, to explain some of the recent movement in cross-sectional stock behavior. The basic investment idea is that the concept of bond duration can be applied to equity cash flow timing. If cash flows are backloaded, an equity will have a longer duration from stocks that have cash flows more certain and clearly defined in the near-term. The implications are clear from the classic formula for duration which accounts for the timing of cash flows. 

The equity that has longer duration will be more sensitive to changes in the discount rate and changes in the distant cash flows. Hence, if there are rising rates, these equities will see a greater negative impact. Of course, these stocks have benefitted more from low rates in the post GFC period and during the most recent decline in rates.  (See "Equity Duration" for a recent example. The equity duration idea has been kicking arounds for more than two decades but has recently been given new focus.) Nevertheless, there is compelling evidence that low duration stocks should do better than long duration stocks.

Determining the timing of cash flows for equities is not an easy problem. Equity duration can be measured through several unique but justifiable models: cash flows, growth forecasts, and bond-beta approaches. It certainly is more difficult than any calculation of a bond's duration where the cash flows are well-defined. The idea of an equity duration can be contrasted with other risk factors, but the true value comes from the primal nature of focusing on cash flows. 

Equity duration can account for the wild swings in price of growth stocks that will be affected by expectations of long-term cash flows. Long duration will be more sensitive to cash flows volatility and changes in the business cycle and will be more susceptible to stock mispricing.

The low duration stocks have the same characteristics as value, high profitability, low investment, and low risk stocks; however, the link between duration and value is not one for one. Both have value for measuring differences in stock risk.

Equity duration is intuitive and can provide another way to look at factor risks that are helpful with explaining some of the differences cross-sectional stock behavior.

Factor performance in bull and bear markets - Diversification in bear market is valuable

 

Consumption-based models predict that risk factors should be less profitable in bear markets than in bull markets; however, recent research shows that value (HML), profitability (RMW), investment (CMA), and momentum (UMD) factors are more profitable in bear markets than in bull markets. The size (SMB) and market (MKTRF) factors show the expected performance in bear markets. (See "Where is the risk in risk factors?".)

A risk factor may proxy for a consumption state and generate lower returns in a bad state. A lower return in a bad state requires a premium to be held. This research shows better returns in a bad state and low returns in a good state.

This strong behavior in bear markets has important implication for portfolio construction and asset allocation to factors. The poorer performance during the market recovery after the GFC is also given some better context. The long recovery was not good for factor risk versus market exposure.

The authors find that equity cash flow duration can explain this bear market behavior for the value, profitability, and investment factors and to a lesser extent momentum. Financial constraints can explain the profitability factor in bear markets. Constraints and duration are more important for those risk factors that seem to be more cash flow dependent.

Factor diversification can add value especially when the market turns bearish.