If your goal is to outperform passive index investing, you need an edge (i.e. some kind of advantage over the rest of the market) to succeed. This long post goes from theory to a wide range of practical ideas – many of which form the core of different portfolio strategies I currently use myself.
The logical argument for the need of an edge is this: the return of all market participants (investors, traders, hedgers and so on) put together equals the return of the market. Therefore an outperforming trader needs to have an advantage over other market participants, who must underperform. If you add trading costs into the calculation you will reach the inevitable conclusion, that the average active trader underperforms the market by the amount of fees he pays.
To be successful in the quest for outperformance you need to search, find and capitalize on inefficiencies in the market – to exploit an edge.
Moreover from the many possible edges you need to put together an investment process fitting your personality, skill and commitment – strategies you can stick with.
This process should enable you to systematically harvest an excess return above your cost of implementation to be worthwhile in practice.
To stand a realistic chance you need to know what you are doing, because, in an analogy to a poker game: If you don’t know your edge, the fish at the table is most likely to be you.
The financial markets are made up of people (and their algorithms) with a myriad of different goals, risk appetites, levels of knowledge, behavioral biases, constraints and motivations, who use different assets and operate over different time horizons.
As many of these investors and traders constantly strive to find and exploit new inefficiencies, the search for an edge will always stay a moving target in an evolving market.
I believe, the best edges – the ones that last longest – can be found by analyzing the core characteristics of large groups of market participants and then looking at the available data to see where this actually plays out as a usable advantage. Often the reverse course is taken, which leads to data mining problems and often a less sustainable edge.
In the title of a recent paper Michael Mauboussin, one of the thinkers on the subject who combines theory and practical application best, poses the key question to ask, if you want to start this endeavor with a high probability for success: “Who Is On The Other Side?”
An edge in theory
Mauboussin breaks down the possible sources of edges into four types:
- Behavioral inefficiencies may be at once the most persistent source of opportunity and the most difficult to capture. At the extremes of fear and greed over-extrapolation is rampant and few investors have the courage to differ from the crowd and the rigorous process necessary to avoid chasing performance at market highs and to refrain from selling in a panic near the bottom of a crash. Both medium-term momentum and long-term mean-reversion inefficiencies are the result – these are broadly studied and exploitable.
- Analytical edges arise from weighing available information differently or updating views more effectively. This tends to give institutions with greater access to resources an advantage over individual investors, but other areas of analysis, e.g. operating on a different time scale or anticipating a change in the market’s narrative, may give smart individuals the upper hand as they are less constrained by rules or career risks when they think differently.
- Information: bigger institutional firms profit from their capacity to buy and process data to gain an informational advantage, but for the individual interesting aspects are the possibility to unconventionally piece together different kind of information or to pay attention to information that most other investors ignore.
- Technical edges exploit repeatable mechanisms that play out in the market, because of investor preferences unrelated to the value of a security, influenced by institutional constraints, fund flows etc.
Many edges combine several of these sources, but all share a common property: the advantage they provide is time-varying rather than constant. To outperform one needs to be different from the market and take the risk to significantly underperform at times (an example is how value investing sometimes underperforms for decades at a time as it has for the last). This difficult and painful experience is necessary for an edge to be sustainable – if it is easy more and more people flock to it and the advantage goes away. No pain – no gain.
It pays to always look at limits to arbitrage away the edge: are there behaviors, constraints, costs, entrenched beliefs, risks or other strong reasons for an advantage to continue to exist in the future?
A closer look at institutions
Large institutional players play a big role in the market place and warrant closer scrutinity as they often trump individual investors on informational and analytical resources at their disposal, leading to a general advantage.
Chart from “Who Is On The Other Side?” a paper by Michael Mauboussin
On the other hand analyzing institutional investors can lead to significant edges, because they are often constrained in their action by rules and motivations that have nothing to do with an effort to outperform. Lot´s of sustainable ideas are hidden in places where institutions are forced to do something, where they are unwillig to differ from their colleagues (failing conventionally may be preferable to succeeding unconventionally, because this entails the risk to fail unconventionally which will possibly cause the manager to lose his job) or areas where they do not tend to go (e.g. size constraints, time horizons they are not judged on).
I believe, a good rule of thumb is, that institutions seek outperformance with a low tracking error to the market – the opportunities here may be very hard to exploit because of the massive competition. In other areas, that are not targeted or even underperformed in by institutions, individuals may more easily gain an advantage.
These theoretical ideas will surface again and again when we look at some practical examples of investing and trading edges.
An edge in practice
Even more interesting for constructing a strategy or a portfolio of strategies than the theoretical base of an edge, are a list of practical sources of outperformance, that I have come across in my investing career. Many edges turn out to be fleeting, because they are based on ideas or patterns that do not correspond to a strong market structure, risk premium, behavioral bias or investor motivation. These have no strong underlying reason to exist and are easily arbitraged away as soon as a critical number of traders notices them – in the age of algorithms this can happen very quickly.
My main focus has always been reliability – the stronger the reason for an edge to exist the better. My list is filtered by this focus and, of course, by the limits of my knowledge (many edges are well guarded secrets).
Strategic betting on relatively simple, robust ideas has brought me better results than complex, convoluted systems – these often trade on noise as most market fluctuations are simply random. And even once such reliable advantages have been found, they need to be researched and updated as the market continually evolves and changes.
In general it pays to always trade with the most basic probabilities available – when the base rate is in your favor.
For example US equities show a strong long-term historic probability to be up year over year (around 73%) with the strongest average return of all asset classes – the equity risk premium. Any strategy that favors the long side will have a much higher chance of success than a short strategy because of this immense tailwind.
I pay close attention to the appropriate time horizon an edge plays out over – often different, even opposing, forces are dominant at different time frames. Random noise gets stronger the shorter the time frame becomes and I found this extremely difficult to overcome beyond a certain threshold (below one week).
One of the most comprehensive resources on the historical risk and returns of different asset classes, factors and strategies is “Expected Returns: An Investor’s Guide to Harvesting Market Rewards” by AQR´s Antti Ilmanen – easily one of the most useful investing books out there when looking for a long term edge backed by statistical data.
Buy-and-hold investment edges
The simplest edge, let´s call it the stoic or passive edge, is the market average and it is easily underestimated – both in its power to deliver returns (through steady compounding) and how rarely it is actually achieved by investors in practice. All too many distractions and behavioral biases lead to very few individuals sticking with it over the long term.
This will likely remain an edge that is mechanically simple to harvest (it is very easy to automate and then to simply let run), because it is so painful and hard to stick with at times. Numerous studies have shown that most investors (retail and professional alike) underperform the market, because we instinctively chase good performance and panic-sell when the pain of losing becomes too strong – causing a behavior gap by effectively buying high and selling low. A lot of this underperformance is caused by being under-invested for a long time after being scared out of stocks.
I think, this is the best opportunity for the stoic individual, who doesn’t really want to bother with all this investing fuss. Simple, automated rules can enable anyone to participate in economic growth, if he manages to ignore the market and the path his investments take in the short run. Inattention can be an edge.
The widespread underperformance implies, that not only does a small minority actually achieve average market returns, but also that a select few investors must capture the remaining outperformance.
Diversification is often called the only free lunch in investing and is the next step to take when looking at a muddy term like „the market“. Public financial markets are made up of different asset classes and spreading your investments across them can help to reduce the downside while keeping returns steady – risk-adjusted returns are higher. An international mix of stocks, bonds and real asset forms a global asset allocation portfolio.
A diversified global asset allocation portfolio as a benchmark for “the market“ – from Meb Faber´s paper “The Trinity Portfolio“.
Factor edges have become all the rage under the buzzword „Smart Beta“ and try to combine a buy-and-hold investment approach with a tilt towards certain return factors that have shown outperformance historically. The basic factors are value, momentum, carry, low beta, liquidity, quality and size.
Factors are intensely studied academically and widely used in practice – they can easily be accessed through exchange traded funds (ETF). Because they also fit the exact profile of large institutions – to seek outperformance with a low tracking error to the market – I am fairly skeptical whether there is much to be had there in the future. At the very least long, painful periods of underperformance (just look at the value factor) will likely be the norm for simple factor exposure. Factors that are hard to access (e.g. because they have high turnover) show greater persistence even after they become widely known and used – the momentum factor is the strongest among those.
Pure, market neutral factor exposure remains the domain of specialized hedge funds, because it involves shorting large numbers of stocks (the ones showing the worst factor characteristics) and employing high levels of leverage in addition to the long exposure to stocks showing the best factor characteristics (which is what smart beta ETF do – combining market exposure with a long-only factor tilt).
Successful factor strategies may have to be more complex in the future and look at the popularity, valuation or momentum of the factors themselves to gain additional insights. A combination of factors can lead to a very different return profile as diversification dampens periods of underperformance, when different factors outperform at different times. The strongest combinations may be factors from opposite ends of the spectrum (with very low correlation) as, for example, combing value with momentum. Entrenched beliefs keep many investors from being able to subscribe to such opposing philosophies simultaneously – creating an edge for those who are able to do that.
Global Asset Allocation Plus depicts the historical outperformance of a diversified portfolio tilted towards value and momentum factors – from Meb Faber´s paper “The Trinity Portfolio“.
Active investment and trading edges
Market timing edges are widely disputed and often discouraged in financial theory and education. They are not easy to achieve, but in certain instances the evidence that they actually work is strong and the implementation not all that difficult – recently tactical asset allocation strategies using timing have gained more and more traction.
I like seeing such resistance from influential market participants paired with strong empirical evidence for a variety of timing strategies as it implies that only a minority actually uses market timing edges and the advantage is not easily competed away. Systematic timing strategies play a major role in the day to day management of my own portfolio.
Again it is important to be clear: over which time horizon do we want to time the market? Momentum and mean-reversion both are strong phenomena, but, like shifting tides, they play a role over different time frames – the idea that a strategy works the same over all time horizons does not hold in practice.
Academic studies agree on a distribution of these effects over time (e.g. in the classic momentum paper back in 1993):
- around 1 month: mean reversion dominates
- 2-15 months: momentum works
- 3-5 years: mean reversion is strong again
As these studies are necessarily based on historic data, the question remains: are these distributions stable or will they shift over time? For the moment these time periods have held up and are a solid playbook to build strategies on opposing principles that both work.
Long term market timing
Trend following is based solely on the price of a security and has become a cornerstone of many tactical asset allocation strategies.
Based on empirical features of markets (momentum effects, clustered volatility and fat tails) trend has been quite powerful in reducing downside volatility, when using look-back periods between 6 and 12 months and frequent rebalancing (e.g. monthly). This is a significant edge, because lower drawdowns enable greater behavioral discipline and/or responsible use of leverage to boost returns.
A long-term trend strategy avoids the deep drawdowns of major bear markets while posting similar returns to buy-and-hold (6,92% annually vs the S&P´s 7,7% since 1950 for this long-only moving average crossover strategy).
Fundamental market timing tries to adjust portfolio exposure to the economic regimes of expansion and contraction and the corresponding long term market cycles.
The majority of macro commentators and investors focus on a predicting turning points in the future economic development – a very competitive environment where very few (if any) analysts show a consistent predictive ability over several market cycles. Usually recessionary dangers are vastly over-predicted because they make good news – it is a daily deluge of extremely noisy information aimed primarily at catching your attention rather than providing useful advantages. The edge, in my opinion, lies in largely ignoring these attempts at prediction, unless you are exceptionally skilled in your own analysis.
Some of the most successful investors excel at the puzzle of macro investing, where everything is interconnected in complex patterns. There must be many specialized macro edges these investors use, but you have to know: where is your analytical edge, in comparison to these world class players?
Rather than trying to compete in this arena, I see an edge in integrating fundamental analysis in my own investment process by looking at the trend of economic development: slowing growth heightens the dangers of a recession, but unless it actually turns negative, the strong upward bias of the stocks market usually prevails.
Leading economic indicators paint a nuanced picture of this trajectory and can be used systematically to reach similar results as a technical trend model.
Using the 6 month average of the Conference Board Leading Economic Index LEI (holding the S&P 500 only when LEI is in an uptrend) managed to avoid the main decline of all major bear markets – effectively reducing maximum drawdowns while keeping overall returns similar to buy-and-hold (6,37% annually vs the S&P´s 6,61% since 1959).
Because I see little overlap between technically and fundamentally oriented investors (entrenched beliefs again), I developed my particular edge for timing the market over the long term by combining technical and fundamental insights in my Meta Strategy model.
In depth background reading on these ideas (including independent backtesting over a variety of methods and parameters) is widely available and I especially like a series of articles by Philosophical Economics.
Fundamental value investing at the asset class level takes an even longer view, because it capitalizes on the mean-reverting tendencies the market displays over 3 to 5 year periods.
It is a very popular approach, but in practice needs an extraordinarily patient investor – it certainly isn’t for everyone. Buying value uses a market timing advantage that materializes over very long periods of time. Value is not very predictive for time periods below three years as the correlation between the stock market’s valuation and 1-2 year forward returns is weak. The market can stay irrational for longer than we anticipate.
For a diligent buy-and hold investor who wants to spend little time on his portfolio, but is prepared to do in-depth analysis once a year, annual (over-)rebalancing towards value and away from expensive areas of the market may prove to be a suitable edge.
Short term market timing
The world of short term trading is vast, highly competitive (including an increasing number of trading algorithms) and very difficult to navigate successfully. The greatest motivation here is the potential to earn a sustainable income from a relatively small capital base, because you can bet on your edge more frequently – in most cases this turns out to be unrealistic and a majority of short term traders fails.
I went down that rabbit hole myself many times and wrote about how the experience usually plays out here. The few remaining short to medium term strategies with a convincing edge, that I still use, gravitated through trial and error to the mean-reversion tendencies around one month and are based on structural edges described below (an overview of the main edges, that I personally use can be found at the end of the post).
Just a few of myriads of ideas (few of which hold water) are:
- Mean reversion after extremes: The strongest manifestation of such short term mean-reversion often occurs after parabolic moves, which are hard to fade because – by definition – they move beyond any reasonable expectation. Rates for borrowing stock to short and option premia sky-rocket – selling these premia under extreme circumstances may be a lucrative strategy: an edge lies in the fact that options become overpriced due to abnormally high volatility and sky-rocketing demand.
- Technical market patterns: I found it hard to create a systematic strategy that actually makes money from short term market patterns – a lot of the popular technical analysis is not stringent enough to systematize or doesn’t hold up to backtests. The question “Who Is On The Other Side?” often has no clear answer. There is no real reason why an edge should persist once it is discovered by enough traders.
I describe a popular intraday edge and my experience in implementing it in detail in “The Opening Gap and other Intraday Patterns around the Market Opening“ – the post also includes a number of reasons that speak against intraday strategies in general.
An alignment with the long-term trend shows more promises: random pullbacks can be used to enter at better prices to participate in the momentum effect.
Structural or technical edges
One of the most convincing ideas, when searching for a robust edge, is to look at investors who are forced to do something or willingly / mechanically do something, that causes underperformance over the long term – for example:
- Fund flows create momentum and mean reversion effects, for example flows into and out of stocks that enter or leave a popular index: After a new index constituent is bid up artificially in price by index funds buying up the stock mechanically, mean-reversion takes place. The stocks that left the index (green line at the right side of graph below) on average massively outperform the new entries over the next couple of months.
Data from the Research Affiliates 2017 article: “Buy High and Sell Low with Index Funds!”
- Downgraded corporate bonds: forced institutional selling depresses prices artificially and makes bonds after they were recently downgraded to junk status an outperforming investment on average. The lowest rung on the investment grade ladder is BBB. When a corporate bond with a BBB rating gets downgraded, it’s moved into non-investment grade or junk status (BB or lower). When that happens, big institutional investors are forced to sell their positions.
- Forced selling and buying in general: many other instances exist that contain such structural edges, e.g. fire sales (liquidity squeezes and margin calls through pro-cyclical use of leverage); investors buying overvalued securities or selling undervalued securities against their better judgment because of career risk (doing what everybody else does is often the safer choice, even if the manager believes that it makes no sense), etc.
- Hedgers willingly overpay for insurance to protect against outsized losses. This large and reliable volatility risk premium can be earned by investors taking on this extra risk – here the same mechanism is at work that makes a good insurance business a very profitable one.
Several option selling strategies harvest the volatility risk premium and contain an edge over the market: the CBOE indices PUT (systematic writing of put options on the S&P 500), BXY and BXM (both systematic writing of covered call options on the S&P 500) all outperformed the S&P 500 with lower volatility.
- Carry is another interesting characteristic to filter for – inertia often trumps over-extrapolation for superior returns. Carry often flies below the radar, because it works like an invisible force below the surface: gains are made, if nothing changes. Interest, dividends, roll yield or option premia are areas where one can earn a return when things stand still or – the reverse idea – one can exclude strategies that have to pay to hold positions (e.g. buying options, holding certain commodities) with time working against them.
Looking at an edge from a different angle – the investor´s side not the market´s – investor psychology plays a role in each of the ideas described above. Patience and stoicism have already been singled out, others are:
- Risk tolerance: risk and return are largely two sides of the same coin – simply by accepting higher volatility longer term returns for a solid edge have a good chance to be higher as well. Going too far will increase the risk of blowing up an investment account, though. Using the Kelly Criterion conservatively is a sound mathematical way to balance risk and return in an optimal way for your personal risk tolerance.
- Discipline and commitment to process: above all judging the quality of your decision making by the probabilistic quality of the process and not by the individual outcome.
- Willingness to be different: opportunities lie in unconventional strategies, unfashionable ideas and over different time horizons, if investors are willing to tolerate intermediate, prolonged underperformance at different times than the market.
- Favoring the boring over the exciting: pay attention to information that most other investors ignore. Look for boring repetitive processes – a lot of traders subconsciously want to play an exciting game as an end to itself, making money is not really the objective for them.
- Big-picture “Edge”: stepping back from the daily noise for a rational overview of yourself and your strategy implementation. This includes evaluating your mental state, analyzing the biases that play out in your own mind (knowing about a behavioral bias won’t make you immune to it), taking care of a balanced body and psyche (eating well, exercise, meditation, etc.).
Risk and return profiles of edges
On a practical level it is also important to know how the exploitation of an edge plays out in the implementation of a strategy on a day to day basis and to be aware of the risks lurking beneath its surface (e.g. if your edge is to insure catastrophic risks) – know what to expect.
Most strategies fall into one of two camps when you take a closer look at their return distribution:
- Convergent, negative skew strategies are usually based on mean-reversion where many small gains are interspersed by few, but large losses. Here the main risk are infrequent crashes. Many regular small gains can easily lead to complacency and over-leverage – an unexpected crash can suddenly blow up your account, if you are ill prepared.
- Divergent, positive skew strategies are mostly based on momentum and trend. Here you have to tolerate many small losses while the profit is made by few, but large gains. Here the biggest risk lies in abandoning your strategy in the middle of a long drawdown and never realizing its potential gain. Like a death by a thousand cuts, long and frequent drawdowns are very hard to tolerate.
Last but not least, the easiest way to succeed in the quest for an edge may often lie in simply avoiding the worst securities or in scrutinizing where the search may use up immense resources without a strong likelihood to actually gain an advantage. Is a potential edge worth pursuing or does it go into the „just too hard – pile”? Warren Buffet and Charlie Munger say that the best way to achieve success is by avoiding failures. They imply (a bit tongue in cheek) that it is not brilliance that made Berkshire Hathaway succeed – they just consistently avoided stupidity.
The key maxim is to always invert your idea and look at it from the other side. The best tools I found for this are: look closely at your competition – the number of PhDs on the other side of your trade. And, best of all, the base rate: how are basic probabilities in a given area distributed?
- Trying to pick individual stocks is one of my pet peeves. I think by and large it is a huge waste of time and resources. The commentators, who have been pounding the table on indexing for years, have simply been right. Nonetheless countless investment advisors, newsletters, etc. are doing nothing but advising on stock picks. Recent studies have pointed out the inherent fallacy, lead by Hendrik Bessembinder´s “Do Global Stocks Outperform US Treasury Bills?“. Key findings include, that “in all 42 countries we examine, returns to the majority of global stocks fall short of returns to one-month US Treasury bills. The best performing 811 firms (1.33% of total) accounted for all net global wealth creation.“ It is just very unlikely to be able to pick those extreme outperformers consistently.
- Factor investing: Often success is more easily achieved by avoiding losers than by picking winners. Value investing can work by simply avoiding the most expensive securities, a quality factor can be realized by avoiding the worst junk.
- Being selective, ignoring mediocre ideas and only investing in the best opportunities at the best times is something many professional investors cannot do, but individuals can. The pros cannot choose to be in cash or a passive index for a majority of the time and seldom become active.
- Avoiding mistakes in execution can be the detail that decides whether a real edge actually makes money. I find the nitty gritty details one of the hardest parts in running a portfolio – all too often something goes wrong or the urge to override a systematic process wins and causes an unnecessary drag on performance.
- Being immune to gibberish: a great edge can lie in figuring out what information not to listen to. Filtering for relevant ideas by screening out the noise can be a real game changer, because a lot of the information flow is designed to capture your attention and/or to sell you stuff (subscriptions, magic systems, etc.) and not intended to be useful in your quest for outperformance. The default mind set should be: be very skeptical when encountering return promises beyond reasonable expectations, unreasonably certain predictions or trading lore about advantages based on hearsay, unsupported by statistical data.
Make sure your „edge” actually is an edge!
How I use these edges
This has been a long article distilling a lot of useful ideas and I just want to quickly recap how I strategically use different edges (in italics) in my own portfolio.
The Meta Strategy
At the core of my portfolio I run an active long-term strategy, that is invested in stock index ETF as a default and switches to safe or alternative assets systematically only when the danger of a prolonged bear market becomes high. I use a combination of leading fundamental (to accurately evaluate economic developments) and technical indicators (for exact execution decisions dependent on fundamental evaluation following price trend) to achieve this. The results are published in a monthly newsletter – read more about the strategy in a series of articles containing all the background information and rules.
Short volatility strategies
I use two basic strategies that harvest the volatility risk premium: systematic option selling and selling volatility directly using instruments based on Vix futures. The edge here is strong, because many investors willingly overpay to insure their portfolios against crash risks. The ability to take on such outsized risks ensures high returns in good times, but, as this is an extremely negatively skewed strategy, traders have to diligently control their own risk. It materializes seldom, but in violent crashes.
Few hedging strategies make sense for individual investors, usually reducing portfolio exposure to risky assets is a cheaper option with the same result. But, in return for giving up some upside potential, writing covered calls on a core portfolio will dampen downside volatility by the size of the option premium – leading to a higher risk-adjusted return expectation over time. For me the strategy is a good addition to my core ETF portfolio to hedge medium term down-swings while the bigger bear market risks are taken care of at the portfolio level – by switching to safe assets when downturns go beyond a certain level, especially when paired with economic deterioration.
Throughout my blog I examine different strategies that show promise over the long run or are used for special occasions only:
- Trend Following for Individual Investors – A Manageable Futures Strategy
- and, adding carry to trend: Short Option Overlay for Trend Positions
- Trading Parabolic Moves (…after the fact)
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