The Yin and Yang of Financial Markets

It´s hard to strive for superior investment returns – many say it´s futile, because markets are too efficient.
While researching for ways to gain an edge and to exploit systematic inefficiencies in the market, I come across the same pair of principle forces in different forms again and again.


Mean Reversion and Momentum
These pervasive market forces are mean reversion and momentum, which I call the Yin and Yang of financial markets, because they are the diametrical opposite of each other. Their complimentary opposition combines different (often wrongly assumed to be mutually exclusive) investment philosophies and is the closest I have come to finding the holy grail in investing – a two-fold edge which can give clear guidelines in the evaluation and composition of assets and strategies in a portfolio.


The traditional chinese Taijitu symbolizes two contrary forces that are interdependent and give rise to each other as they interrelate to one another.


yinyang


Momentum = Market Yang
  • positive
  • active
  • trending
  • strong sentiment
  • price based
  • analytical tool: technical indicators


Mean Reversion = Market Yin
  • negative
  • passive
  • reacting
  • weak sentiment
  • valuation based
  • analytical tool: fundamentals


I think, the best explanation for these market inefficiencies is behavioral and reflects the long term market cycle:
The momentum of a move carries prices beyond reasonable valuations as more and more market participants join a freight train of positive or negative sentiment. When there are no more buyers or sellers left, mean reversion takes over and prices revert to normal valuations and often beyond – starting a momentum move in the opposite direction. Throughout this cycle we never know just how far momentum will carry prices before mean reversion takes over again.


We now have a pretty metaphor for phenomena described in countless academic papers and a general explanation that makes sense intuitively, but no clear idea how to actually use it when selecting investments. We need to distill clear guidance from the concept for it to be useful.


Value and Momentum
One of the most influential papers on the subject is “Value and Momentum Everywhere” authored by academics associated with the hedge fund AQR, combining academic thoroughness and practical implementation in a way I appreciate.
Here the concept of mean reversion is implemented through the use of a classic value factor: undervalued assets tend to outperform overvalued assets over time.
For momentum the pervasive finding is: recently (over a 3-15 months time period) outperforming assets continue to outperform in the future and vice versa.
As this, especially the value approach, can be considered common knowledge among the majority of investors, the paper´s most valuable insight lies in looking at both approaches in combination:


“The negative correlation between value and momentum strategies and their high positive expected returns implies that a simple combination of the two is much closer to the efficient frontier than either strategy alone, and exhibits less variation across markets and over time.”


This great example of diversification in action can be seen clearly in the numbers produced by the paper: The value and momentum factor raises the risk-adjusted return significantly for almost all asset classes. A global asset portfolio of value factors achieved a Sharpe ratio (a measure of risk-adjusted return) of 0.72 and the momentum factor 0.74 (1971 – 2009), but due to the negative correlation of -0.60 of the two factors the combined Sharpe ratio skyrockets to 1.59.
For comparison: single asset classes have historical Sharpe ratios of around 0.30, while a global asset portfolio will boost that to 0.5 through diversification – even this seemingly small step is a huge step up for the performance of a portfolio yielding higher returns and/or lower volatility and drawdown.
Due to trading costs and other practical issues real life performance numbers would be lower, but still at a historical Sharpe ratio between 0.8 and 1.
Such robust negative correlation between two outperforming strategies is extremely rare.


The practical difficulty for a non-multi-billion dollar investor like you and me is the implementation of such a quant strategies aiming at pure factor exposure, which involves buying and shorting hundreds of securities and high leverage. But you can make good use of both factors in a long-only approach as well. Not that that´s easy, because both strategies suffer through prolonged periods of underperformance.


The difficulty of value investing, for example, is that the timing of sentiment extremes is pretty much impossible. The irrationality “will end when it ends” as is described with great humor in a blog post by The Macro Tourist on the repeatedly desperate state of value investing – for example right now in 2017.


Warren Buffet´s and other value guru´s stoic patience in sticking with cheap assets as they get ever cheaper is not really suited to my mentality and plenty of other´s, I suspect.
It is fairly easy to built a generic deep value screen using asset classes and market sectors, but sticking with it in practice is a totally different ballgame. Meb Faber highlights a possibile approach that simply uses the number of down years in an asset as a rule of thumb without even going into fundamentals (statistical details in this blog post):


“A basic rule of thumb is that if the asset is down two, three, four, and five years in a row you can expect future two year total returns of 40%, 60%, 80%, and 100%.“


It has worked like a charm recently with great results in commodities and emerging market economies, but boy can the implementation be painful when you happen to select an asset that is in its 2nd or 3rd down year, if it is on its way to five down years as was the case with several of these commodities.
To better your odds, you can add a momentum screen to the selection process (which its what I use in part to select the global asset allocation area of my portfolio) and avoid investing in a declining asset – according to the mantra of newsletter writer Dr. Steve Sjuggerud who is a good source for these deep value ideas:



Well, it will still be difficult, because sentiment and news around deep value assets are so bad. A case in point is one of the few commodities that is still beaten down: Uranium. The value story here has been great for years (and still is) and prices for URA, the industry ETF, have been going down for an unprecedented 6th year now, hitting the same bottom(?) price three times in the last 2 years – an immense amount of frustration piling up when following this strategy while the rest of the market is on a bull run of historic proportions.


In short: it´s hard to make practical use of mean reversion in the markets – you need a mentality like a rock.


To systematically implement valuation metrics in our investing process we need a model – either a simple rule of thumb as described above or a more sophisticated valuation model for each asset class, that tells us where a security´s valuation is at and what to do about it – a complex and research intensive operation.


And similar issues have to be dealt with to systematically use momentum as described in this previous post.


Carry and Trend
I recently came across another paper that shed additional light on these market phenomena and shows a path to use them more intuitively. It is closely linked to the AQR paper mentioned above. In “Carry and Trend in Lots of Places Vineer Bhansali and co-authors link valuation to another concept that has been a source of consistent outperformance in the past: Carry. 


“Carry is defined by Koijen [2011] as the “expected return on an asset assuming that market conditions, including its price, stay the same.” Thus, carry may be thought of as a naïve, yet robust, model-free measure of the risk premium in a given asset class.“


This idea opens up a whole new range of possibilities to judge the attractiveness of an investment or strategy, especially where valuation models are difficult and complex.
The simple rule is: the less it costs (or the more you get paid) to hold an investment the better.


“Be on the right side of the trend, and don’t pay too much while you are at it.” as Bhansali puts it succinctly.


Creating a rule to put the basic probability for an investment to work out in our favor is easy:


  1. Invest only in the direction of the trend and use the break of a long term trend to scale out of an asset.
  2. Prefer the assets that pay most for just holding them and avoid paying to hold an asset unless you are insuring your portfolio.


This leads to directly actionable results, for example:
  • prefer equities with high shareholder yield (dividends + buybacks) and look at yields relative to historical averages
  • prefer bonds with high yield and look at historical yield averages to judge their general attractiveness
  • invest only in real assets with positive carry – e.g. commodities with backwardated term structure, real estate with attractive rental yield
  • compare shareholder yield, bond yield, rental yield of real estate, commodity carry, volatility term structure etc. to weight your exposure to different asset classes
  • find other strategies that have high positive carry e.g. selling options
and use trend as a filter.


  • shorting assets is ruled out because of negative carry (cost of borrowing)
  • long volatility strategies are very expensive, e.g. volatility products and buying options


Option Writing provides Positive Carry
As a practical example, let´s check out an option writing strategy through this framework.


The performance of the CBOE S&P 500 PutWrite Index (PUT) gives us insight in the basic strategy of selling monthly ATM S&P 500 cash covered puts. From 1986 to 2016 it returned 10% annually with a 10% standard deviation according to CBOE data, while buying and holding the S&P 500 Total Return Index underperformed with greater volatility: 9.9% annual return with a 15.1% standard deviation.


What is the reason for that, given that one of the main issues with option writing is that the potential gains are capped by the premiums received by the seller?


Carry can offer a good explanation: while dividends (that option sellers miss out on) yield around 2% a year, the volatility risk premium (that option sellers harvest) has been much higher at about 3.8% annually. Another difference is that option premium rises with higher volatility, typical for down markets, whereas dividends are more likely to be cut in bad economic times. Consequently harvesting premium dampens drawdowns considerably – more than making up for lost upside in strong bull markets.


Just using one part of our framework – accessing the equity market via a simple method which pays us more to hold without any price movement than traditional index investing – already yields a considerable advantage over simply buying and holding the market. But we can utilize two powerful edges simultaneously to make the strategy even more efficient and smarter: get paid for holding a position and stick with the direction of the long-term trend.


We can make the following strategy refinements following this framework (this is the core of the strategy I implement and you might come to different conclusions when thinking it through, but it´s the basic principle that´s important):
  • Trend: write puts on assets (I use options on a diversified set of ETF to avoid company and concentration risk) in an uptrend, write calls on assets in a downtrend, which will add diversification and is market direction agnostic
  • write options OTM (I use a delta of 30-35), which will generate premium even if the price moves sideways or goes against the position for a couple of percentage points
  • spread expiration across time (I use 6 to 10 weeks to expiration) so sudden market swings are less uncomfortable to tolerate
  • set a Stop Loss (I use -100%) to avoid the unlimited loss potential of call writing
additionally I found this working best for me:
  • liquidate positions if you are put the underlying
  • if using leverage (which option writing can provide at no cost in a margin account), hedge by buying further OTM options with longer expiration times – a calendar spread – to safeguard against market crashes or surges and dampen daily portfolio fluctuations (I use only a couple of different general index options e.g. SPY at a price that is a fraction of the premium taken in)
  • don´t overleverage
and finally, to address the issue of missing out on a strong run of the underlying asset by being limited to the size of premium as the maximum possible profit (FOMO carries strong psychological power), I use an easy method to enhance participation in bull or bear runs without ever owning the underlying:
  • take profits if a position reaches more then +60% within the first half of time to expiration and immediately open a new position taking in new premium at a higher strike price – this should insure participation in a strong move of the underlying


Please do your own research whenever implementing new strategies, I only describe what works for me (taking responsibility for potentially being disastrously wrong myself) and not advising anyone to use the same strategy.


I hope this gives plenty of food for thought.




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