The four horsemen of apocalyptic position sizing used by professional investors

4 horsemenDespite picking a fair share of good stocks, it is still tough to generate some consistent serious alpha. Picking the right stocks and exiting them well tells You how often You win. How much You win, however, is a function of how much You bet. Some professional investors pay surprisingly little attention to their bet sizes. Below are four algorithm often practiced by professionals that can

  • Four popular bet sizing algorithms used by professionals that have negative gain expectancy
  • Size does matter in the markets: 1$ or 100 will have a different outcome


When it comes to bet sizing, there are only two sizes: either too much, either too little. As a professional short-seller, position sizing is mission critical. Successful positions shrink. Not only do they contribute less and less, but they also tilt exposures (net & net Beta). To add insult to injury, they become less noticeable. On the other hand, unsuccessful positions balloon. They immediately hurt. So, I have spent years studying the science of bet sizing. I sought to learn from other investment professionals. It eventually dawned upon me that Long biased people rarely ask themselves the same questions. For them, bet sizing does not have the same degree of urgency. Worse even, it became apparent that some position sizing algorithms had outright negative expectancy, or nasty side effects that they were never even aware of.

Aral Sea Ships

Insufficient liquidity

Horseman 1: Liquidity. If You can’t get out, You don’t own stuff. Stuff owns You
Getting into a position is like buying a boat, or a second house. You can do that any day of the week. Now, selling a boat is tough (been there, done that). It may take time to build a position in a stock. Time is an expensive luxury few market participants can afford when they want to liquidate.So, no matter how attractive a story may be, if you can’t exit easily, just don’t enter.

Rule 1: don’t size your positions so that they may go Hotel California on You:
“You can check-out anytime You like, but You can never leave!”, Don Henley, Hotel California




Example of long conviction

Horseman 2: High conviction: feel-good position sizing
Disclaimer: this position sizing is used by the greatest and the worst investors. The classic rationale is: “if You believe in something, then you should go big or go home”. What else is it but a feel good position sizing algorithm ? Risk is not quantified but subjectively assessed. The problem is mental accounting, or the constant emotional revisionism of the situation. Jack Welch said: “what can be measured can be improved”. If You can’t quantify your risk, then don’t expect improvement in consistent alpha generation capability.

The greatest investors also use conviction as a position sizing algorithm. The only difference is that they express conviction in units of risk. They quantify risk first and then put chips on the table according to their perception of the reward. If an idea does not pan out, risk can be parred down.


Horseman 3: Equal size: one-size-fits-all and the volatility roller coaster
This position sizing algorithm will not bring ruin, but it has negative side-effects that may prevent You from achieving your obejctives in terms of performance, attractiveness to investors and quality of life…

Equal weight is a form of laziness:
First, let’s look at the math behind equal weight. All trading systems boil down to their trading edge (Avg Win% * Win% – Avg Loss% *|Loss%|). Since all bets are equal, equal weight implicitly puts emphasis on the signal, and excludes the value of money management. In other words, stock picking has to be consistently above 50% to absorb losses and generate a profit. Unfortunately, no system works all the time. So, equal weight carries cyclicality in performance.

Ignoring volatility at the position sizing level invites volatility in the portfolio
Not all stocks have the same personality. Some are more volatile than others. For example, internet stocks tend to be much more turbulent than utilities. If all positions are sized equally, then the most volatile stocks will drive the volatility of the overall portfolio. Morality, ignoring volatility at the position sizing level will in turn invite volatility in the portfolio.

Horseman 4: Average down, martingale and the certainty of ruin
Rookie gamblers always come up with some elaborate scheme to break the casino. It is usually a variation on the theme of doubling down after each loss. They believe that the losing streak will end and they will recoup their losses. This position sizing algorithm is known as martingale. Let’s look at the math behind this algorithm

1. Adding to a losing position reduces the hit ratio
2. even if You had infinite capital, the most favourable outcome would be break-even. First, do You have infinite capital ? Second, any other outcome before the most favourable one carries an interesting probabilistic property called certainty of ruin
3. Doubling down means adding to losers. Resources have to come from somewhere, probably winning trades. Books written by successful market participants always emphasize “cut losers, ride winners”. Do You know any successful market guru who says “cut your winners, ride your losers ?”

In conclusion, there is a reason casinos have gold, marble, paintings from masters and gamblers declare bankruptcy. Double down on losers and You will go broke. One more thing about probabilities, it’s not about if, it’s about when.

Size does matter in the markets. Not paying enough attention to position sizing has consequences that range from unpleasant volatility to certainty of ruin. Position sizing is not a glamorous topic, but in highly competitive sport, every little bit of edge counts

A powerful two step process to deal with the endowment effect: The game of two thirds, or how to deal with free loaders in your portfolio

Would You allow tenants to stay rent-free ?

Would You allow tenants to stay rent-free ?

If You were the owner of an apartment building, would You allow tenants to stay rent-free forever ? You would probably do everything in your power to either collect or evict free loaders. In the investment realm however, one of the main reasons managers fail to accomplish their goals is that they allow free-loaders to stay rent-free in their portfolios. The difficulty then is how to identify and deal with free loaders.

They don’t really stand out enough on an individual basis. Yet, as an aggregate free-loaders put a drag on performance.

  • Endowment effect: once in the portfolio positions are sticky.
  • How to identify and effectively deal with free loaders
  • The 3 main benefits of the game of two thirds
Once upon a time, i used to place thematic small positions across the portfolio like pawns on a chessboard. They were supposedly hedges for China, precious metals, oil, monetary intervention etc. They were all tiny positions that were supposed to kick in if any of these themes were to gain traction. Six months went by and I could not understand why performance was so pedestrian. Meanwhile, none of those stocks had worked. Then, it dawned upon me that even though they were tiny individual positions, they totaled 10% of the portfolio as an aggregate.
The endowment effect (Thaler 1980)
Endowment effect is the hypothesis that people value more what they own than what they could buy. It is hard for positions to dribble their way into our portfolios, but once in they become sticky. It is difficult to get rid of them, even though they do not contribute. Some managers would hold on to losers just because they do not know what to buy next.
Our lives, our desks, our houses are filled with clutter. Unless we actively create and enforce rules to get rid of it, clutter creeps up on us. Our inner saboteur will always find good reasons to hoard junk. To illustrate its potency, let’s look at a simple example: in your wardrobe, isolate the clothes You have not worn for over a year. Think about all the excuses to keep them, but then ask yourself: “If i did not have it, would i buy it now ?” If not, then bye bye, fashion moves on and so should You.
The game of two thirds: A simple two-step process to deal with free loaders
Free loaders neither detract nor contribute enough to be visible. They don’t stand out enough to be dealt with. Since it is not possible to deal with them on the y-axis (price), the solution is to introduce time x-axis. Rationale is simple, if stocks have been there for some time, but still fail to contribute, then their weight should be reduced.
  1. Calculate portfolio turnover, divide it by three: first 1/3. Add 1/3 turnover to the entry date of each position. For example, a stock entered on January 5th and a turnover of 1 would yield a cut-off date of April 5th
  2. Divide performance in 4 quartiles, concentrate on the third quartile: second 1/3. For all stocks in the third quartile past their anniversary date, cut weight in half
 Special mention for long-term winners
Apple (AAPL) or Softbank (9984:JT) are long-term winners. They sometimes go through extended periods of under-performance. Because there is so much embedded profit, it is difficult to realise that they have not contributed for some time. The idea then is to reset contribution on a rolling basis.
The idea then is to apply the same rules as above on a rolling basis. Instead of cutting positions to half, taking a portion the size of the out-performance from the previous haircut. For example, if Apple went up by 10% from previous haircut, then shave 10% off the current size.
The rationale is
  1. if it starts to underperform, it will be dealt with, and this profit taking will have cushioned the blow. This demonstrates stewardship
  2. If it continues to go nowehere, resources are re-allocated to a potentially more productive asset. If non-performance persists over 2/3 of portfolio turnover, then a more drastic reduction is in order
  3. if outperformance resumes, then it will be dealt with
It is important to periodically reset contribution. When stocks have been in the portfolio for a long time and substantially contributed, we become attached. Failure to reset contribution is one of the reasons why some managers escort their positions on the way up and then all the way back down. It doesn’t show until it is too late.
The three benefits of the game of two thirds

The game of two thirds may appear simplistic. It has however powerful psychological implications. It is a simple, powerful and objective way to short-circuit the endowment effect for three reasons:

  1. Simplicity: math is beyond dispute. Simple rules are elegant, easier to implement and harder to challenge
  2. Stewardship: great investors are not smarter, they have smarter trading habits. Getting rid free loaders builds the habit of dealing with difficult stocks
  3. The quality of our excuses determines the quality of our performance: one of the most frequent excuses is “what do i buy next ?” Constant re-examination of positions forces managers into action.
Once in a portfolio, positions are often sticky. Asking ourselves “would you buy it again today ?” is too subjective to deal with positions that have overstayed their welcome. Our inner saboteur will find good reasons to procrastinate until the next review. Our natural instinct to hoard junk “endowment effect”. The game of two thirds is an elegant way to identify and deal with free loaders.


The game of two halves: an elegant two-step process designed to cut losers, run winners, while maintaining conviction

In every hospital around the world, there is an unwritten rule: surgeons should not operate on their own children. There is no such thing as professional detachment when it comes to your own child. In the investment realm however, market participants are consistently asked to defend their convictions, but also expected to be surgical about their losers. How can someone maintain enough attachment to weather rough times, but stay detached enough to surgically cut when necessary ?

“Cut your losers, run your winners” is the key to survival in the markets, but no-one tells You how to pick the lock. This is especially difficult if You are a fundamentalist (fundamental analyst/manager/investor/trader). First, there is no price mechanism like a stop loss to tell You it’s time to move on. Second, You don’t want to be perceived as lacking conviction. Third, investors want You to manage risk. No wonder 80% of managers find it difficult to outperform every year.
This is the second article in a series of four about exits and affective neurosciences. Our central premise is that the quality of exits will determine the quality of performance. The purpose of this exercise is to help fundamentalists cut their losers, run their winners, while keeping conviction. It is based on the assumption that they are refractory to the idea of a stop loss policy. It is a simple yet powerful method that is guaranteed to mechanically lift performance.
You do not need to be right 51% in order to make money
One of the classic myth is that “You will make money as long as You are right 51% of the time”. Wrong. You will make money only if You have a trading edge:
                     Trading edge = Average Win% * Win% – |Average Loss%| * Loss %
Let’s take an easy example: if average profit is twice as big as average loss, what would be the break-even hit ratio ?
          0  = 2 * X – 1 *(1-X)
          X     = 1/3
with X = Win% and Loss% = 1- Win%
In a system with a 2/1 profit/loss ratio, you only need to be right 1/3 of the time. In other words, stock pickers who identify 3-5 baggers only need to keep losers small to make formidable gains
In reality, the visual representation of a stock picker’s P&L distribution looks very much like the chart below: a few princes make up for a lot of frogs. . Being right 51% of the time through the entire bull/bear cycle is the unicorn of stock picking. Every strategy experiences a drawdown at some point. Stock pickers make money as long as they stay disciplined and keep their losses small.
 Gain Expectancy - Classic Trend Following
 In order to move to the distribution shown below,  one of two things need to happen:
  1. Either reduce the number of frogs: easier said than done, particularly when strategies stop working at some point through the cycle
  2. or, their impact is reduced: reducing drag will mechanically improve profitability
 Gain Expectancy - Alpha Secure
Predicting tomorrow’s winners is much harder than dealing with today’s losses. The game outlined below is an elegant way to deal with losers. Not only does it mechanically improve the trading edge, it also salvages ego and rewires neural pathways from outcome to process orientation.
The game of 2 halves
The objective is to halve the weight of losers once they detract more than half average contribution. Proceeds are then re-allocated to either fresh ideas or winners. This is a simple two-step process:
  1. Divide all positions between contributors and detractors, calculate average contribution: first half
  2. Reduce weight by half (1/2) for all detractors below -1/2*Average contribution: second half
Average contribution: +0.5%          Babylon Ltd weight: 4%  Unrealised P&L: -0.4%     Realised P&L: 0%
After weight reduction                      Babylon Ltd weight: 2%   Unrealised P&L: -0.2%     Realised P&L: -0.2%
Now two things will happen: either Babylon Ltd will perish, or it will rise
  1. If Babylon meets a tragically eponymous fate : it would have to drop another -15%, just to reach minus average contribution, or -0.5%. At this point, it will be either it is a screaming Buy or a dog. Either way, it will be an easier decision to make
  2. If Babylon rises: then unrealised profits will compensate for realised losses. One rule of thumb in order to maintain a positive trading edge, do not add to the position until it crosses previous entry price
The additional 2% freed-up can be re-allocated either to winners or fresh ideas. Adding to winners cements conviction. Adding fresh ideas brings fresh blood to the portfolio. Either way, it is more of a good thing.
Special mention for managers who use an equal weight position sizing: Equal weight position has many drawbacks, but it has one benefit in this case. Instead of using contribution (weight * return), a simple distribution of return is sufficient.
The game of two halves has three deep benefits
  1. Trading edge mechanically improves: this is a simple elegant formulation of the first mantra: “cuts your losers and ride your winners”
  2. Good stewardship: managers are often torn between defending their convictions and dealing with problems. If they cut too frequently, they are perceived as lacking conviction, which negatively impacts investors confidence. By selling a portion of the position, they show peers and investors that they both maintain their conviction and deal with problems
  3. Process versus outcome neural pathways re-wiring: funds reach capacity not when they are too big in size, but when inertia sets in. Dealing with losers forces managers into action. This accomplishes three things:
    1. Managers become dispassionate with their problem children: since dealing with them improves stewardship, the stigma of taking a loss disappears. The game is simple enough to be executed even in the darkest
    2. Increased fluidity: since proceeds are re-invested, managers have a direct incentive to look for fresh ideas, or to their existing ones
    3. Process versus outcome mindset: believing that being right about a stock is a matter of profitability is an outcome process. When ideas are profitable, ego gets validation. When (not if) they are unprofitable, ego feels under attack. This invariably leads to defensive, unprofitable and often destructive behaviors. Dealing with losers in an orderly fashion changes focus from outcome to process. Being right is no longer about the outcome but about doing the right thing.
The game of two halves is a key to unlock the “Cut losers and ride winners” fortress. It is an elegant solution to the oldest problem in fundamental investment. It reconciles the demand for conviction with the need for action. The privilege of its (mathematical) simplicity is that it imposes itself even in the darkest times.
More importantly, it changes the definition of being right. It is not a binary outcome on the profitability of individual ideas., It is the observance of a process that will lead to higher aggregate profitability. In the Jungian archetypes, it no longer triggers the orphan (amygdala in the limbic brain, responsible for fight, fight or freeze), but activates the ruler (pre-frontal cortex or thinking brain). In short, the game of two halves reduces stress and improves profitability.

Amygdala and the neurophysiology of Greed and Fear

Going into a combat mission without an exit plan is suicide. In fact, the only soldiers who nevamyg400er bother with exit plans are kamikaze. On the other hand, market participants routinely enter positions without a clear exit plan. The problem is that as soon as we enter a position, our emotions impair our ability to make rational decisions. Greed and fear have a chemical signature. This is the first article of a series of four about exits and emotional mastery.

Dopamine and cortisol: the chemical brothers of Greed and Fear
When there is no exit plan, there is uncertainty about what to do next. A mild level of uncertainty can be exciting. A region of the brain Nucleus Accumbens (NAc) gets activated. This triggers the mesolimbic reward circuitry, often referred to as the dopamine reward circuitry. Dopamine is released. People take on more risk. By the way, cocaine, opiates and nicotine activate dopamine transmission. This is why just watching the portfolio feels a bit addictive sometimes. As Kuhnen and Knutson showed, risk seeking behaviors are often associated with NAc activation and high level of dopamine. In other words, Dopamine is the chemical signature of greed.
When a few positions “go against us”, uncertainty turns from thrill to mild discomfort. We are more vigilant and come back to reality. When performance starts to suffer, uncertainty morphs into stress. Stress triggers the amygdala, located in a primitive part of the brain called the limbic brain. Its primary function is to keep us alive at all times at any cost.  It is always on. The problem with the amygdala is that it cannot discern between real danger and an imagined threat, between a saber tooth tiger and a -1% dent in the portfolio. At higher levels of stress, the amygdala activates the pituitary gland that releases cortisol. When cortisol is released, the neo-cortex or thinking brain is hijacked, game over.
In his latest research, Daniel Goleman, author of Emotional Intelligence and focus, goes one step further. He describes a state of prolonged high stress as neurobiological frazzle: the thinking brain shuts down and physical health deteriorates. This is what we call burn-out. Bottom line, uncertainty has a destructive physiological signature.
Uncertainty: get comfortable with discomfort
Uncertainty cannot be eliminated whether in life or in the markets. We can learn to 1) manage it and 2) reduce it.
1) Getting comfortable with discomfort literally determines the quality of our lives. This is the subject of a future article
2) Reducing uncertainty simply comes down to  having plans and rituals or habits. One of the most important plans is the exit plan.
The three questions that will notably reduce stress:
When everyone else is stressed out, every bit of clarity counts. Unfortunately, every decision is an additional stressor. Every bit of stress reduces the mental bandwidth. This depletes the thinking rain of its capacity to make good decisions. This is called decision fatigue. Willpower is a muscle.
An interesting study was done in Israel about parole decisions made by judges. Convicts examined before lunch were 2/3 more likely to be denied parole than after lunch break.
Bottom line: if we do not want to look like deers in the headlights, we must plan our exits before entry. Experienced traders often say that the best time to put on a stop loss is 5 minutes before entry.
There are only three possibilities after entry: either a stock goes up, down or nowhere. So, an exit strategy must answer those three questions
  1. Price goes down, there is a loss: at what price do we reduce risk ? How much do we need to exit ?
  2. Profit goes up, there is profit: At what price do we take risk/money off the table ?  How much do we need to exit ?
  3. Price goes nowhere: how many days after entry ? How much do we need to exit ?
Note also that exits do not have to be binary 0-100%. This is the subject of the next two articles.
Note that there is no room for interpretation. This is not the time for abstract debates on valuations, long-term prospects, or any other rationalization that our amygdala fueled inner idiot will throw at us. It has to be an unambiguous IF…THEN sequence.
The good news is that unless any stock triggers any of those landmines, there is no need for action. It helps achieve three things:
  1. It reduces the need for constant monitoring: market participants often stay glued in front of their monitors expecting the markets to telegraph a compelling call to action
  2. It helps navigate volatility. Volatility often tempts us into action. Having a plan and sticking to it helps reduce the urge
  3. It frees up mental space that can be used for higher cognitive functions: research and planning.
Everyone knows that the key to success is to cut losers and ride winners. The problem is that no-one has ever come up with a formula. If You want a clear method to accomplish this, while maintaining your conviction, then the game of two halves is for you.
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3 reasons why selling futures is a not a hedge to the Long book

out_of_balance_-_Google_SearchIn the Long/Short equity space, managers find it difficult to find “good shorts”. So, they resort to selling futures in order to reduce the net exposure (Long – Short exposures). With low net exposure, volatility comes down, VAR is apparently low, so it is possible to leverage up again; problem solved, or not ? Selling futures solves only one of the five major hedges: gross, net, Beta, market capitalization, concentration. Selling futures is an implicit bullish bet on the market. It all works well, until it doesn’t. In this article, we will look at three reasons why selling futures is not an all-weather hedge to the short book. We will also look at other ways to hedge the short book.

On January 24th, 2006, the arrest of Horie-san, president of LiveDoor, sent the Japanese market into a tailspin. Despite our collective best efforts to reassure investors that we were properly hedged, our performance suffered. On the surface, it seemed like we had low net exposure, reasonable gross exposure (Long  + Abs(Short) exposures or leverage). Yet, we were caught like deers in the headlights, watching our performance inexorably sink day after day. The source of our problems to one big position in the short book: March 06 futures.
Selling futures is not a hedge for three reasons
  • Selling futures as a form hedge is an expensive form of laziness
  • Short futures is an implicit bet on market cap
  • Short futures is an implicit bullish bet on Beta
Selling futures as a form of hedge is an expensive form of laziness
Investors do not need to pay 2% & 20% for something they can do themselves. In fact, many investors are already natural hedgers. For example, insurance companies routinely trade futures and index options. Selling futures in lieu of single stocks unfortunately shows lack of skill in the Long/Short craft.
Some managers argue that net exposure management is an important tool in their arsenal. Managing net exposure is vital to deliver superior returns. When investors hear this, they understand “Beta jockey”. At 40%+ net Long, this is no longer a hedge, this is directionality. During the GFC, directional hedge funds did not bring the net to -30%, or at least -10% net Short. Net exposure continued continued to hover about +10/20%, sometimes neutral at best. Managers may have said they wanted to be positioned for the rebound, but in reality they were just scared. They did not know how to hedge and it was the wrong time to learn.
Hedging is a delicate craft that must be honed during bull markets. Those markets are more forgiving. As long as performance goes up, mistakes can be forgiven. When the going gets rough and patience of investors wears thin, hedging mistakes can be deadly.
There is one exception where selling futures as a hedge shows superior skill. When net exposure remains below +/-10% throughout the cycle, performance comes from the excess return over the index. This is as close as it will ever get to pure alpha in the equities world. This is a rare skill: managers understand they are not good at short-selling, so they concentrate on delivering excess returns, only partially juiced up by some residual market exposure. Managers who can deliver genuine excess returns deserve recognition and unsurprisingly see their AUM grow over time, survive and thrive through the thick or thin.
Long Stocks/Short future is an implicit bet on market cap and exchange
Managers like to invest in small/mid caps.  This is where the fun and the gold nuggets are. Small-mid caps tend to have better upside potential than large caps during bull markets. Besides, stories are interesting. It is easier to have access to senior management. Uncover a few 3-4 baggers and a new stock picking star is born.
On the other hand, futures are a reflection of the underlying large caps in the index. For example, Topix Core 30 accounts for more than half of Tokyo first section market capitalisation. So, performance of the index is driven by its top caps.
Then, selling futures and buying small-mid caps is an implicit bet on market cap: Long small/mid caps, Short large caps. It goes even one step further. It is often a bet on the exchange: small/mid caps are often listed on different sections of the exchange. So, it can take the form of Long Nasdaq/Short S&P 500, Long JSDA / Short Nikkei, Long Kosdaq / Short Kospi etc.
As usual, it all works well until it doesn’t. Small/Mid caps do better than large caps in bull markets. In bear markets however, small/mid caps fall faster and harder than large caps. This is what happened to us in 2006. Our Long book fell -4-5% everyday. Liquidity evaporated. We could not get out of stocks without pushing them even further down.  Meanwhile, our short book only fell by 2%, leaving a gap of -2-3% every day. Selling futures is an implicit bullish bet that works as long as the market stays bullish.
The psychological implications are even worse. As much as waiting for the first heart attack  is not recommended to start living a healthy lifestyle, waiting for a bear market is a bad time to start learning the discipline of short selling. Selling short is a muscle that atrophies when not flexed. Managers grow complacent during bull markets. They believe “good shorts” will be plenty available when the market turns bearish.
Unfortunately, bear markets are harder to trade. Volatility increases, volume drops, bid/ask spreads widen, borrow becomes harder to source and squeezes can be vicious. Small caps may drop and look like great shorts, but in practice, they are hard to sell short. Obvious shorts quickly become crowded and once they do, they rarely fall as fast as the market.
On top of this, investors are risk-adverse and prone quick to redeem. So, trying to learn a difficult skill in a tough environment, without being allowed the luxury to make mistakes is hardly a good recipe for a lasting business.
Long Stocks/Short future is an implicit bet on Beta
The index has a Beta of 1. Since futures are a reflection of the index, they have a beta of 1. Small/mid caps outperform the index during bull markets. They therefore have a Beta above 1. So, Long small/mid caps/Short futures is therefore an implicit bet on Beta.
The difficulty comes with the first derivative of Beta, or speed. When the drop comes, it is sudden and violent. In our 2006 “soft patch”, one investor noted that we had a beta of 1.5 on the way up and 3 on the way down, after which he proceeded to redeem his investment. The only way to manage the short book via futures is to turn Beta neutral to negative. All things being equal on the Long side, that means large negative net exposure, something that traditionally net long managers are not comfortable doing.
A classic solution is to replace small/mid caps on the Long side with Low Beta stocks such as utilities, pharmaceuticals, food stocks. Net Beta can be negative, or below while net exposure can stay marginally positive. It works, but this is a reactive move implemented only after the reality of bear market has settled in. That usually comes after a drawdown.
How to edge properly then ?
Are VIX options a real hedge ?
Every time there is an earthquake, earthquake insurance sales go up. They then peter out over the next few years. Every time the market tanks, VIX goes up and investors rush to buy VIX options. VIX options become rapidly expensive. Besides, VIX is the only true mean reverting asset class. Trading VIX options is therefore an expensive form of hedge, hardly profitable in bear markets.
Absolute versus relative series
Analysts often complain that  short ideas are hard to find in a bull market. This is true, but only if they look at absolute series. If one is to divide absolute prices by the closing price of the Index (relative series), then quite a different world starts to emerge. There is ample supply of underperformers out there, matched by an abundance of outperformers. This is however a paradigm shift. The objective is no longer to generate money in absolute terms. In fact, the true meaning of Long/Short is excess return over the index on the Long side and excess return over the inverse of the index on the short side.
All of a sudden, it becomes much easier to hedge the Long and Short side. Furthermore, competition is not as intense as in the absolute world. Shorts are not as crowded, because in absolute terms, they still look like they are going up, only slower the rest of the market. So, one would enter a short, knowing it would probably lose money in absolute terms. That is a challenging psychological hurdle. Years into it, It is still hard to intellectually reconcile positive performance, despite a full red inked absolute P&L column.
The main drawback of the relative series is the added complexity of calculation. Everything has to be divided by the index: charts, stop losses & target prices, risk management, even performance. The architectures of portfolio management systems radically differ. Imagine sending a limit order in absolute (try and send your favorite broker) a relative currency adjusted  but managing stop losses in relative terms. It takes time to getting used to it, but the reward is well worth the effort. Short and Long candidates are abundant. Volatility is much lower, which makes it more commercially attractive to investors. Institutional investors prefer low volatility consistent returns over highly volatile performance. For example, the largest hedge funds in the equity space do not shoot for the moon, they do want to beat the market, they just aim to deliver high teens performance year after year.
Selling short is a muscle that atrophies each time futures are sold in lieu of stocks. As much as waiting for a heart attach is not the best time to start exercising, waiting for the bear market is the wrong time to learn the discipline of selling short.  Investors are not dupe: they see through directionality and large futures positions on the short side. They have been there before and they did not like it then.
Shorts are plenty available all the time. They are just not going down in absolute terms but relative to the index. It implies a complete rethinking of both sides. It takes practice to learn but over the years investors have rewarded managers who deliver low volatility consistent returns from stocks on both sides of the book. As John F. Kennedy said, The time to repair the roof is when the sun is shining”.

The view from the short-side: how we process emotions and the market signature of the 5 stages of grief

Market participants are constantly asked to defend their conviction. The moment they have to justify their positions is the moment they lose impartiality. They become attached to whatever they have to defend. Being right is no longer about the process (taking calculated risks), but about the outcome (making money). A losing position is an attack on the ego. For this reason, market participants process emotions through a 5 stage cycle defined by Elizabeth Kubler Ross as the psychology of grief. Each phase has a distinctive market signature and even a specific language.

  • Short sellers have a unique perspective on how market participants process emotions
  • The 5 phases described: market regime, market signature, language and profitable course of action

 I have been a professional short seller for almost a decade. For 8 years, my mandate was to under-perform the longest bear market in modern history: Japan equities. I have always searched for a way to identify the signature of human emotions across markets. Many respected market gurus have come up with charts plotted with emotions ranging from euphoria to despondency. Yet, they never really resonated with the short seller in me. Those were written by market participants with a natural Long bias. The short side offers a unique perspective on how investors process emotions. We, short sellers, never sell against buyers. We ride the tails of those who were once holders and now have to “accept” losses and “let go” of attachment.
There are three market regimes: bull, bear and sideways. Each regime can be subdivided into two categories: quiet or choppy. Bear markets usually start in sideways choppy markets: an epic battle between bears and bulls. They usually end in indifference: sideways quiet or bull quiet. Everyone has thrown the towel and no-one cares anymore.
The psychology of grief has five phases: denial, anger, bargaining, depression and acceptance. We will examine each phase looking at the market regime, the market signature, the language and a profitable course of action.
Phase 1: Denial
  • Market regime is usually sideways choppy. Stocks stop making new highs. They are trapped in a volatile range. Short interest is low. Bulls fight bears.
  • Market signature is the compression of estimates. Optimistic and pessimistic analysts have fairly close estimates. All available information has been “baked in” the estimates. The decisive factor is a sudden penetration through support level.
At this stage, analysts jump in and say two things:
  1. This is a “one-off”, “inventory adjustment”, “seasonal adjustment” etc
  2. This is a “Buy on Weakness opportunity”: Analysts are usually quite vocal as they appeal to market participants who were waiting for a pullback to enter a position
If a stop loss was not triggered, it is best to wait until the ensuing rebound is over to make a decision. If the new peak is below the previous high, then start trimming. When in doubt, reduce position size.
Phase 2: Anger
  • Market regime has morphed into a choppy bear. Stocks make lower highs and lower lows. Volatility remains elevated. Short interest start to tick up. Professional short sellers, such as myself, put a chip on the table just to see. Fast money, those who bought the dips and lost money, turn around and engage in some revenge short selling.
  • Market signature is characterized by institutional reducing their weight. Initial sellers are Long Onlys trimming their weights. Mutual funds may well keep their bets over the index, but they still trim their weights so as to reflect under-performance.
At this stage, analysts express their frustration:
  1. “…But the market does not understand …”: that is always an interesting argument, particularly after years of out-performance, institutional participation. Market probably knows something analysts refuse to accept yet
  2. “Short-sellers and speculators are taking the stocks down…”: ignorant analysts and market commentators blame us for stocks tanking, yet facts are stubborn: short interest is low. Secondly, in order to sell short, we need to locate borrow. Borrow availability represents a tiny fraction of the free float. Simply said, we just do not have the might to take anything down.
At this stage, it is prudent to aggressively reduce bet size for two reasons: 1) Volatility remains high and 2) performance does not justify a big position anyway. For market participants with a Long/Short mandate, this is a good time to anchor a small short bet. Position sizing is crucial as volatility remains elevated. Those anchors become invaluable when stocks move into the next phase as they embed substantial profits.
Phase 3: Bargaining
Me: “Doctor, if I eat my vegetables, stop drinking, smoking, eating poorly and exercise more, will I live longer ?”
Doctor: “I don’t know, but it will feel much longer anyway”
  • Market regime shifts from bear choppy to bear quiet. Bears have won the battle.
  • Market signature is a softening of a leading indicator that triggers a downgrade of estimates. Negative earnings momentum attracts short-sellers. Short interest start to rise.
At this stage analysts bargain with their conviction:
  1. “We take our estimates down, we revise our target price, we extend our investment horizon, but…”: Since analysts were ardent supporters, they believe they cannot change their mind at once
  2. “… We keep our Buy rating, because the long-term story is still intact”: the softening is not perceived as the symptom of a disease but a temporary setback
Analysts devote their existence to a few stocks. They know something is wrong but they cannot publicly admit that it is time to let go, but market participants can read through the lines and sell. Price action has already shown some weakness, but quantitative short sellers see negative earnings momentum as the sign to build positions. Short interest rises and so does the cost of borrow. This is when anchoring a small position in the previous phase becomes invaluable: borrow was secured at a cheap cost.
Phase 4: Depression
  • Market regime is bear quiet to bear volatile because of short squeezes
  • Market signature is 1) deterioration of newsflow , 2) radio-silence from the analyst community and 3) rapid increase in short interest
At this stage analysts:
  • crawl under their desks: they hardly contact companies or market participants
  • “this is a stock for long-term investors”: to which there is only one retort: “then it should be matched by long-term commissions”. If they frown, sell short…
Short interest rises quickly. The quality of borrow deteriorates (callable stocks, usury borrowing rate etc). It becomes costly and difficult to sell short. As a rule of thumb, do not sell short when short utilization (shares borrowed/shares available) rises above 51%. Volume is thin so any tiny event can trigger a short squeeze. Amateur short sellers are forced to cover, which trigger a cascade of short cover.
Phase 5: Acceptance
When the inexorability of reality sets in, there is a sort of euphoric relief.
  • Market regime is either quiet bull (small higher highs, higher lows) or sideways quiet
  • Market signature is terrible news-flow, massive downgrade from the analyst community, elevated short interest (crowded short). It is also muted price action: stocks do not react to a torrent of bad news anymore
At this stage, analysts are frustrated and no longer afraid to tarnish their standing with companies. They downgrade ratings, estimates and publish some vitriolic content such as:
  1. “Structural short”, “flawed business model…”, “…mismanaged”: it sometimes becomes personal, because analysts had a rough inner journey being champions of a lost cause
When all the negativity, particularly the words “structural words”, does not move share price anymore, it is a sign that the worse is over. There is one logical thing left to do: cover the short and go long.
Markets are the ultimate mental sports. As much as we would like to think we are rational, the moment we are asked to defend our opinions is the moment we lose impartiality. The irony is that we intuitively know when something is not quite right. Still, we feel obligated to defend our stance. We refuse to admit reality, so we go through a painful process that eventually leads to acceptance. Pain is inevitable, suffering is optional. Making money in the markets is not about trying to be right, it is about accepting to be wrong and move on. Would You like to learn simple powerful techniques designed to reconcile the need for conviction and the reality of losses ?
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Regardless of the Asset Class, There Are Only Two Types of Strategies

Finance is one industry where there is no shortage of creativity. There is always a new strategy, investment vehicle, or asset class. This alphabet soup is confusing, particularly when it comes to assessing risk and reward across asset classes. Yet, there is a simple universal way to classify strategies. They fall into two buckets: either mean reversion or trend following. Simply said, the exit policy determines the win rate, which then shapes the return distribution.


  • A powerful visual representation of style/gain expectancy: Call to Action: our commitment is to help people become better traders. if YOU want to visualise your style, opt-in and we will send YOU a portfolio diagnostic tool for free
  • Regardless of the asset class, there are only two types of strategies: mean reversion or trend following
  • Each strategy type has a specific risk profile, which require different risk metrics. Common Sense Ratio recaptures risk for all strategy types (Read this, it is important)
  • How to increase the win rate, gain expectancy and overall profitability depending on strategy type ?

I. The only two types of strategies: mean reversion or trend following

Over the years of patiently testing multiple algorithmic strategies, patterns in the return distribution repeated over and over. It eventually became apparent that strategies fall into two buckets: mean reversion or trend following. Attached are graphical representations of the gain expectancy of mean reversion and trend following strategies. The reason why the same patterns repeat themselves is simple: exit policy.

Market participants tend to treat exit as a single final event. Each trade is a binary event: either it is profitable or not. The accumulation shapes the return distribution. Hit ratio is then determined not by what we enter, but how we exit.

Charts below are return distributions for each strategy type. They are also visual representations of gain expectancy. One image speaks more than a thousand words. This representation changed my life. It permanently altered the way I perceive the markets. The game is about tilting gain expectancy: contain the left tail, moving the peak hit ratio to the right and elongating the right tail. This visual representation is a powerful tool. This is why we want to share it. We are committed to helping people build smarter trading habits. Sign-in to our newsletter (it’s free) and we will send you a portfolio diagnostic tool.

Mean reversion strategies compound small profits

Gain Expectancy - Classic Mean reversion

Death by knock-out: many small profits. a few knock-out blows

Mean reversion strategies compound multiple small profits. They rely on the premise that extremes eventually revert to the mean. They aim ato arbitraging small market inefficiencies. They often have low volatility  consistent performance. They perform well during established markets: bull, bear or sideways. They unfortunately perform poorly during regime changes. They also perform poorly during tail events. The key issue is to contain rare but devastating blow-ups.

 Mean reversion strategies characteristics are (see graphical representation):
  • Moderate to high turnover
  • High win rate: often above 50%. The shorter the duration, the higher the probability of success
  • Consistent small average profits: trades are closed around the mean
  • Low volatility consistent performance
  • Potentially devastating left tail losses: make a little bit of money every day and lose a fortune in one day
  • Long period of recovery after losses:
Examples of mean reversion strategies are
  • Short Gamma: sell OTM options so as to collect pennies in front of a steam roller
  • Pairs trading (non FX): bet on the convergence between two historically correlated securities
  • Value investing: Buy low PBR stocks and “undervalued” assets
  • Counter trend: sell short shooting stars and catch falling knives

Mean reversion strategies post modest but consistent profits. They cater to investors who would look for low volatility returns. Their challenge is the left tail, those infrequent big losses that will take a long time to recoup.

Trend following strategies have a few home-runs 
Gain Expectancy - Classic Trend Following

Death by a thousand cuts: many frogs, a few princes

Trend following strategies rely on the capital appreciation of a few big winners. Whether they follow stories, fundamentals, earnings or price momentum, stock pickers are trend followers. They may fail to appreciate being called trend followers, but their P&L distribution tells a different story.

Trend followers kiss a lot of frogs: they have a low hit ratio, often between 30% and 45%. Performance is cyclical. Styles come in and fall out of favor. Volatility is elevated. Performance can be underwhelming for long periods of time. The key issue is to contain losses during drawdowns.

 Trend following strategies share those common characteristics (see graphical representation):
  • Relatively low turnover
  • Low win rate: 30 to 40%: see chart
  • Big wins and lots of small losses: right tail on chart
  • Relatively higher volatility
  • Pronounced cyclicality: style comes in and goes out of favor
Example of trend following strategies are
  • CTA type systematic trend following,
  • Momentum: earnings momentum, news-flow, price momentum
  • GARP investing: growth at reasonable price
  • Buy & hope
 Trend following strategies post impressive but volatile performance. They can go through long periods of underwhelming performance, which take their toll on the emotional capital of managers. Their main challenge is to keep cumulative losses small. Profits only look big to the extent losses are kept small.
II. How to measure risk for each strategy type
Investors suffer from a “nice guy syndrome”: some young women genuinely say they want to marry a nice guy, but unconsciously react to so-called “bad boys”. Investors genuinely say they want returns, but in reality they do react to drawdowns. More specifically, they are susceptible to drawdowns in three ways:
  1. Magnitude: never lose more than what investors are willing to tolerate
  2. Frequency: lull investors to sleep. Clients will trade performance for low volatility: big money is fixed income, not stocks
  3. Period of recovery: never test the patience of investors.
There are two ways to lose a boxing match: either on points or by knock-out. Mean reversion strategies score until they get knocked out. Trend following strategies lose on points. Risk is not evenly distributed. Therefore, each strategy deserves its own set of risk metrics.
Risk metric for mean reversion strategies: knock-out


Mean reversion strategies have low volatility, consistent performance and high Sharpe ratio. On the surface, they are what investors look for. The problem is mean reverting strategies work well, until they don’t. Big losses are unpredictable. LTCM had a great Sharpe ratio, at least until October 15th, 1987… Risk is in the left tail. The best metric for mean reverting strategies is therefore: tail ratio. Tail ratio measures what happens at the ends of both tails:

Tail ratio  = percentile(returns, 95%) / percentile(returns, 5%)
For example, a ratio of 0.25 means that losses are four times as bad as profits. Turnover then becomes an important variable: the higher the turnover the shorter the period of recovery. The two ways a mean reversion strategy can survive is either by 1) containing the left tail or 2) increasing turnover.
Mean reversion strategies will test investors’ nerves on two things: magnitude of loss and period of recovery. For example,  some strategies such as fundamental pairs trading post constant, reassuring but modest profits like 0.5% a month. Then one day, they post losses of 3 to 5%. They lose in one month the gains of an entire year.
Investors often succumb to the sunk cost fallacy with mean reversion strategies. They believe that big losses are rare and that managers will eventually make them back. This bias ignores probabilities, particularly the theory of runs. It also ignores opportunity costs. The good news is that there is an optimal point below which it makes more sense to redeem than to stick with managers who experienced a severe loss. It is often referred to as optimal stopping. Whilst the formula can be complicated, a simple rule of thumb is to redeem if losses are below 0.4 of turnover.
On the other, trend following strategies have tail ratios ranging from 3 to 10. Winners are much bigger than losers. So, tail ratio is meaningless for trend followers.
Risk metric for trend following strategies: erosion
Trend following strategies have typically low win rates. Risk is therefore not in the tails, but in the aggregates: are a few winners big enough to compensate for the multitude of losers ? Measuring risk then boils down a simple ratio of profits over losses. The risk metric for trend following strategies is therefore:
Gain to Pain Ratio = Sum(profits) / Sum(losses)
Trend following strategies will test investors nerves on frequency of losses and period of recovery. Frequency of losses is another word for volatility. Trend following strategies are volatile, but semi-volatility (downside volatility) is low. They can also post lackluster performance for long periods. For example, mutual funds have built-in cyclicality. Even if they claim to beat the index, mutual funds still lose money during bear markets.
GPR does not apply to mean reversion strategies because blow-ups are unpredictable. GPR can stay high until it is torpedoed by one or two bad losses.
Combined risk metric: Common Sense Ratio
 “Common sense is not so common these days”, Voltaire, French freedom fighter
Managers rarely define themselves as adherents of either mean reversion or trend following. Even so, it still would not be easy to assess robustness. Besides, the more risk metrics we use, the more confusing it becomes. For example, some managers have great performance despite a bad Sharpe ratio, so the question is “which matters more in which context?”
Since both metrics outlined above can be expressed in a simple binary ratio, combining them makes sense. When this ratio was first to colleagues and friends in the HF world, comments sounded like “yep, common sense”, hence its imaginative name: Common Sense Ratio
                                                                     Common Sense Ratio = Tail ratio * Gain to Pain Ratio
                                                               Common Sense Ratio = [percentile(returns, 95%) * Sum(profits) ] / [percentile(returns, 5%) * Sum(losses)]
Above 1: make money, below 1: lose moneyCSR is much more powerful than either metric taken individually.
Example 1: GPR = 1.12, TR = 0.25, turnover = 2, CSR =  0.275
Let’s take a classic mean reversion strategy that generates 10% p.a. (GPR = 1.1). It has a moderate turnover of 1.5. Within a 24 months period, it will post a monthly drop of -4%, with a 95% probability. This is 5 times as big as the average profit, and roughly 4 times as bad as right tail profits (TR = 0.25). Common Sense Ratio is CSR = 0.25 *1.1 = 0.275.
On the surface, it may look like a modestly attractive strategy. In reality, the period of recovery combined with magnitude of loss imply that investors will have to be patient. In very simple terms, the CSR shows that returns are not attractive enough to justify investing in such strategies. Try this with a few low volatility strategies. Risk is not where You think it is.
Example 2: GPR = 0.98, TR = 3, turnover = 0.5, CSR = 2.94
Now, let’s take a strategy that loses 2% over a complete cycle (GPR = 0.98). Best winners are 3 times as big as worst losers (TR = 3). Turnover is low 0.5. You may think, why invest in a vehicle that loses money ? It does not make sense. Yet, You are invested in such vehicles: welcome to the average mutual fund. 80% of mutual funds lose roughly 2% to the benchmark. Every now and then, they outperform with a vengeance. The rest of the time they suck air. Morality: over time, mutual funds are poor investment vehicles if You stay invested through the cycle.
III. How to tilt the win rate, gain expectancy and overall profitability depending on your win rate
Gain Expectancy - Alpha SecureThe question boils down to: is it possible to combine the benefits of both strategy types without having the drawbacks of either one ? How can we generate a return distribution that would look like the one on the chart ? (*)
The whole game of investing is about generating a return distribution that would have the following characteristics:
  1. No left tail: small losses like a trend following strategy
  2. Long right tail: big wins like a trend following strategy
  3. High win rate: above 50% win rate like a mean reversion strategy

This type of strategy combines both short term compounding with long-term capital appreciation.

Investors following a mean reversion typically come in early and leave too early. The key is therefore to elongate the right tail. This is done through allowing a remainder to extend beyond the mean with a trailing stop loss.
  1. Set a stop loss (more on this in an upcoming article)
  2. When the trade means reverts, close half the position
  3. Set a trailing stop loss (not based on valuation) and close the trade once the stop loss is penetrated
Bottom line, markets can stay irrational longer than You think. When it stops making sense for You, it may start making sense for someone else. Ride their tail, but protect your downside.
If You are a trend follower, here is a simple game (game of 2 halves) that will mechanically improve your return distribution. We all know that making money is about cutting the losers and riding the winners. Here is an objective way to do it:
  1. Calculate your average contribution, divide it by 2
  2. Reduce by half every losing position below – half average contribution
  3. re-allocate the proceeds to winners
Bottom line, you have reduced losers and increased winners in a simple way (more in an upcoming article)
The  purpose of this article was to introduce a simple yet powerful way to reframe strategies independent of asset class. This enabled us to look at the merits and drawbacks of each type. We then looked at risk metrics that would best recapture their risk profile. We introduced a unified risk metric Common Sense Ratio that works across all asset classes. Finally, we looked at ways to tilt gain expectancy for each strategy type. Last but not least, if You want to know what your trading style, please subscribe and we will send You a diagnostic tool for free.
Preview of the next article:
The next article will deal with investor psychology. Short sellers have a unique perspective on investors psyche. We never sell short against buyers. We observe people who once held a position and are now processing grief. The next article will be about the psychology of grief adapted to the markets.
  1. Market regime: bear markets have several distinctive phases, with a measurable market signature
  2. You will never read an analyst report the same way again. You will learn to read emotions through language and back it up with numbers
  3. You will be better equipped to bottom fish for stocks
(*) : All above return distributions are derived from the same strategy. It has both mean reversion and trend following components. In order to draw a mean reversion strategy, the trend following component was switched off, and vice versa to build a TF distribution. Both components are normally switched on, third distribution

Is Stock Picking Overrated ?


  • If 80% of managers underperform their benchmark, we probably focus on the wrong thing. How about focusing on gain expectancy instead of stock picking ?
  • Signal module: how often we win (hit ratio) is not a function of what we enter (stock picking) but how we exit.
  • Money is made in the money management module: how much we win is a function of how much we bet (position sizing).
  • Psychology module: Great traders are not smarter, they have smarter trading habits

The finance industry is built on the cult of the stock picker. We have been conditioned to believe that entering the right stocks is the recipe to beat the markets. Year after year, we spare no effort, expenses, technology and time just to find that golden nugget. We never stop and ask ourselves whether it works in the first place. SPIVA gives an unapologetic report on active versus index investing. Every year, about 80% of managers underperform the market by a few percentage points, the equivalent of fees plus transaction costs of one time turnover. There are probably two reasons for this.

Firstly, Charles Ellis explained in his book “winning the losers game” that markets are dominated by institutional investors. The index is therefore the average of highly educated, intelligent, hard working and ferociously competitive people. So, outperforming the index comes down to beating a very high average.

Secondly, if , year after year, we try the same old “better sameness” just a little bit harder and expect different results, only to be humbled each time, we may have been focusing on the wrong thing in the first place. The answer may lie in an equation so simple it is often overlooked: Gain Expectancy.

But first, please understand that our objective is not to throw stones at active management from our modest glass house. We are committed to helping market participants build smarter trading habits. We provide simple yet powerful tools to nudge performance: resources, research, links, Excel files.

Enter Gain expectancy

Gain expectancy is just another fancy word for average profit. All strategies without exception boil down to this formula:

Gain Expectancy = Win rate% * Avg Win% – Loss rate% * |Avg Loss%|

Using this equation, we will examine what we believe to be the four components of any strategy in increasing order of importance: entry, exit, money management and psychology.

Entry Accounts for 5% of performance


Finance is the only sport that hands out medals before the race

Finance is the only competitive sport where we expect medals to be handed out before the race. Market participants focus their energy on picking the right securities, but stock picking is the process that leads to entry. When we focus on stock picking, we just care about getting the best stocks to the starting blocks and assume they will do well thereafter. We overlook critical questions such as 1) what if they do not perform as expected, 2) how big we should be and more importantly 3) will we have the fortitude to stomach the ride ?

Stock picking is not irrelevant, it is overrated. There is no doubt that picking the right stocks increases our chance of success. The treasure hunt of stock picking is the most exciting aspect of the job. Ironically, entry is also the part that has the lowest impact on performance. Looking back at the gain expectancy formula, entry is just an ingredient of the win rate%, not the happy meal. After all, even the best ingredients will not necessarily turn into a succulent meal if there is no recipe. When everyone else is fixated on entry, paying a little more attention to other components may give us a critical edge.

In the coming articles, we will examine different types of entry techniques, common pitfalls and remedies. Everybody likes to buy on weakness and sell short on strength. But sometimes weakness is a symptom of a bigger problem and vice-versa on the short side, strength turns into bullishness.

Exit Accounts For 20% of Performance


It’s not what we pick but how we exit that determines the hir ratio

We all have been shaken out of a position and then watched it rally without participating. The hit ratio is not determined by what we enter, but how we leave. Exit is a binary event: a trade is either profitable or not. The only time when win rate% can be calculated with absolute certainty is after positions are closed. Anytime before that is just paper profit. The quality of our exits determines the shape of our P&L distribution.

Before I embraced the sophistication of simplicity, I used to believe that a certain combination of factors would generate optimal performance. I was looking for a holy grail of some sort. The first epiphany came after a Monte Carlo optimization. One of the combinations made money 19 years out of 20, despite a win rate of 34%. Meanwhile, the highest win rate (67%) lost money 17 out of 20 years. The lesson was clear: “making money in the markets is not about trying to be right. It is about accepting one is wrong and move on”. There is one class of individuals to whom it should come easy: married men.

Would You drive a car without brakes ? Then, would You trust a strategy without a stop loss ? Market participants are often refractory to the idea of a stop loss. It is however the second most important component in any strategy. It has direct impact on 3 out of 4 variables of the gain expectancy: win rate%, loss rate%, Avg loss%. In addition, it has a direct impact on trading frequency and bet sizing. Profits look big only to the extent that losses are kept small.

Entry and exit constitute the signal module. They only determine the win rate. A trading system is like a car. The signal module is the engine. The money management is the transmission and psychology is the driver.

In the coming articles, we will examine the various types of exits and their influence on the P&L distribution.

Money management accounts for 25% of performance

Different Weight simulations SPX - Excel 2015-03-10

Same strategy, different bet sizing algorithms generate different outcomes

Money is made in the money management module. There is rampant confusion in our industry that associates alpha generation capability with high win rate. LTCM used to boast a win rate above 70%. Yet, their demise nearly took down the modern financial system. By contrast, William Eckhardt, the father of the Turtle Traders, claims a modest win rate of 35%. He has however achieved a remarkable annualized performance of 18% over a 36 year career. It is not how often we win but how much we make that ultimately determines our performance.

In a previous job, I used to run my algorithm across various portfolios. The objective was to help other managers better trade their positions 5bps at a time. Compound this over a year and this is the difference between 2nd quartile and top decile performance. The same stocks kept on reappearing in top ten bets. Managers exchange ideas and have access to the same research. There was a low dispersion of holdings, but there was a high disparity of performance. So, the difference that made the difference was obviously not stock picking: everybody owned the same stocks. The primary determinant of performance was bet sizing.

Looking back at the gain expectancy formula, bet sizing is the component that tells how much we make. It helps us achieve our investment objectives. It is also the most important component for market participants engaged in short selling activities.

In the coming articles, we will look at various position size algorithms, risk management tools so as to help You extract more alpha out of your ideas. We will look at specific techniques designed to help You clarify your objectives and achieve your goals.

Psychology Accounts For 50% of Performance

“If You don’t know who You are, this [markets] is an expensive place to find out”, Adam Smith


Great traders are not smarter, they have smarter trading habits

Unfortunately, bull markets have never boosted anybody’s IQ. We simply get overconfident during winning streaks and start gambling away. Then, during the ensuing losing streaks, we get depressed and take too little risk. In any case, we tend to abandon our discipline. Even systematic traders tend to tweak their models during losing streaks.

We have been conditioned to believe that willpower is the key to success. Unfortunately, willpower is a muscle that tires quickly, particularly under stress. For example, we all know that the key to performance is to cut losers and ride winners. So, we promise ourselves that we will reevaluate positions once stories change. Unfortunately, no plan has ever survived its collision with reality. If we leave this process to our willpower, it invariably turns into an internal debate, where our inner saboteur often convinces us to keep losers in the portfolio.  Inertia creeps in and the next thing we know, our portfolio has turned into a toxic waste junkyard. The problem is: every time we say “Yes” to a loser, we say “No” to a potential winner.

Market psychology is comprised of two parts. It is the ability to execute a trading plan through winning and losing streaks alike. It is also the inner game of investing: the inner alignment from deep subconscious beliefs to daily unconscious routines. “Watch your thoughts, they become words. Watch your words, they become actions. Watch your actions, they become habits. Watch your habits, they become character. Watch your character, for it becomes your destiny”, Mohandas Gandhi

There is a simple, but not easy, solution to change our psychological make-up. According to a 2002 research paper by Wendy Wood, we spend between 45% and 60% of waking time in habitual mode.  Interestingly enough, the study was conducted on young undergraduates, a segment of the population where habits are still highly malleable. Imagine how habitual our behavior can be after 10 years on the job. We probably learned for the first 2 years and then pushed the repeat button ever since.

Great traders are not smarter, they have smarter trading habits. They have developed and practiced profitable behaviors that have turned into trading rituals. The beauty of habits is that they bypass conscious decision process. They become effortless and emotionless over time. Under stress, we ditch elaborate plans and fall back to our habits. This is why installing smarter habits is critical: success is a habit and unfortunately, so is failure.

Fortunately, executing stop losses can be as emotionally intense as brushing teeth. This is a gradual process that starts, not with ruthlessly cutting losers, but with keeping a portion in the portfolio…  It starts small but the compounded effects are immense. The difference between sending a golf ball off course or close to the hole is one millimeter when hitting the ball. If smarter trading habits resulted in a gain as small as 0.02% per trade, the compounded effect over 100 trades would put us in the rare company of market gurus.

At ASC, We are committed to help You build healthier trading habits. In the coming articles, we will provide You with research from the fields of finance and medical sciences, resources exercises, links that will help You change your habits.


“We are what we repeatedly do. Excellence, then, is not an act, but a habit.”, Aristotle

If we want different results, then doing something different is probably a good start. Stock picking is not irrelevant, it is overrated. All it takes to nudge gain expectancy (i-e performance) is to redirect a small portion of our focus to the other components of the success formula.

Great traders are not smarter, they have smarter trading habits. We are committed to helping market participants form healthier trading habits. We will provide You with resources, links, exercises and an App on the Bloomberg portal.

Preview of the next article

  • In the next article, we will introduce a powerful visual representation of gain expectancy
  • Using this tool, we will reclassify strategies across all asset classes in two types
  • We will provide You with suitable risk measures risk for either type of strategy
  • We will introduce a new risk measure: Common Sense Ratio
  • We will provide You with a simple technique that dramatically improve your win rate %