Basics of Portfolio Construction for Price Followers – Introduction Part 1 – Classifying the Nature of your Strategy
While many traders feel that diversification can be applied to all trading strategies…the bottom line is that it doesn’t quite work like that.
The first thing we need to do is appreciate the difference between price following versus predictive methods. You may hear professionals talking about divergent or convergent strategy classifications in a similar manner. We feel that Price Following versus Predictive Method actually is a better descriptor to this general principle which is easier to understand for the retail trader without having to get into any deeper underlying theory about “what is divergence versus what is convergence?”
Determining which style of strategy you possess helps us to classify our trading strategies into two broad churches that are used by speculators to extract an edge from a market and more importantly helps us to understand whether diversification will assist or detract from the outcomes you are seeking to achieve in your trading efforts.
Predictive methods generate their edge from the leptokurtic peak of the distribution of market returns (the positive kurtosis) that lies outside the mean of the normal distribution. Price following methods on the other hand generate their edge from the right fat tail of the distribution of market returns (the negative kurtosis) which lie outside the tail of the normal distribution. Dependent on which trading camp your strategy lies determines your ability to generate a ‘free lunch’ from diversification methods. Now this sounds like theoretical gumph….so let’s break down what we mean here. If you plot your systems trade result in terms of multiples of R you will have a histogram with trade frequency (number of trades) on the left hand axis and R multiple on the lower axis.
Let’s assume the left hand axis is in fractions of percent ranging from 0 % trades at the graph origin to 70% of total trades at it’s maximum. Let’s also assume the lower axis ranges from a loss of 2 standard deviations to a win of 2 standard deviations away from breakeven or the zero point. Now your sample of trade performance results (given a large enough sample) could plot in any distribution form…however for strategies with a long term edge, there are two broad ways to extract this edge from the market. These two broad forms relate to how that distribution from your trade sample map outside the normal distribution of returns (with zero kurtosis).
This zero kurtosis distribution represents the typical distribution arising from a normal distribution of returns. A normal distribution assumes that trade results follow an effective random distribution which fall away fairly quickly either side of the breakeven result and are confined in their standard deviation moves away from the mean of the return distribution. But do not be under the impression that you cannot have simply lucky traders who have benefited from a mere random string of profitable trades of an efficient market. You do….in fact they are most of the traders that spout their impressive short term trading results in many of the popular retail trading forums. The markets are incredibly efficient these days….and any exploitable edge to be found is very slim. Worse still for the predictive mob, is that the edge from stable predictive conditions is transient and short lived as predictive methods are very quick to find this repeatable pattern and exploit it.
On the other hand, the fat tailed events that rely on unpredictable market conditions are remarkably enduring but come at a cost to the psyche. They are just so hard to stick with which allows the edge in price following to be so persistent over the centuries.
That’s it in a nutshell and how to understand how your strategy should be classified. Strategies with a long term positive edge that have a high Pwin% have positive kurtosis and are predictive in nature. Strategies with a long term positive edge that have a low Pwin% have negative kurtosis and are price following in nature.
Now here is the rub….of all the billion different variations of different strategy, their is a deeper simplicity you need to be aware of in terms of the broad nature of the strategy. Is is predictive or price following? That’s it. The signature of the performance metrics will tell you what it is, such as the Pwin% and the R:R and whether or not the trade results possess negative of positive skew. The reason for this is that there are actually only two forms of general market condition that speculators can take advantage of. When markets are stable oscillating about an equilibrium, and when markets are unstable and moving between states of equilibrium. In fact there are three types of broad market condition to take note of:
1. Noisy markets that are in a flux between stability and transition (aka an efficient market). In these conditions neither predictor nor price follower succeed over the Law of Large Numbers. This is a zone where only luck determines your ultimate fate;
2. Stable markets that oscillate about an historic equilibrium such as the market state post 2010 where central bank quantitative easing has been deliberately attempting to stabilise the market by central banks buying the dips and selling the tips. In such predictive conditions, price followers have a tough time with increasing drawdowns but predictive techniques blossom; and
3. Transitioning markets where uncertainty rules the day as we just do not know where they are going to settle down to more stable market conditions around a new future equilibrium. In these market environments, predictive techniques are decimated and price following techniques blossom as we are simply following price in a non-predictive manner to where it might end up (aka the trend ends).
Of these 3 broad types of market condition, only two are available to the speculator who seeks an actual edge in the market.
In an efficient market where no edge resides, your trade results (excluding the frictional costs of spread, SWAP and slippage) will likely plot somewhere within this normal distribution. As your trade sample increases according to the Central Limit Theorem, your distribution of returns will lie symmetrically about this mean and plot as a normal frequency distribution. Now in a realistic efficient market that central mean will be slightly negative to the left of zero and your trade results will plot around it as a normal distribution to reflect the fact that with the Law of Large numbers and no actual edge, you are very likely to lose over the long term.
As speculators, the only way we can harvest an actual edge is to plot somewhere outside the normal distribution of returns in the long term. That means to have a profitable long term edge, we need to have a curve with a biased shape towards profitability (aka >0) and you can either plot close to the 0 point but to the right above the normal distribution curve (positive kurtosis) or to the far right above the normal distribution curve (negative kurtosis). If your curve is biased towards the left hand side of chart, you have a losing strategy no matter which way you look.
Having an understanding of where the edge resides outside the normal distribution of returns allows you to be able to plot which camp your strategy resides. If the strategy relies on a high average win rate or high Pwin% say upwards of 60% with a low R:R….then odds are very high that you have a ‘predictive’ strategy. Money Management methods such as averaging down, grid trading or martingale techniques serve to make this Pwin% extreme. Furthermore tight profit targets help you to achieve very high win rate percentages…..however the sting in the tail using predictive methods comes when markets stop behaving predictably when tail events arise or when noise dominates.
So the price follower has to deal with the other end of the spectrum which makes trading so psychologically hard when compared to predictive methods….and that is in dealing with being wrong most of the time. Now it is the psychological toughness of being wrong that makes the edge in systematic price following techniques persistent and so enduring when compared to predictive techniques that have a far shorter shelf life.
The low associated Pwin% of tail events prevents the price follower achieving higher win rates but ensures you have a potentially unbounded R:R. So price following strategies invariably have low Pwin% of say between 20% – 40%. Now price following techniques can be incorrectly applied using a profit target that lift the Pwin% to more psychologically acceptable levels of between 40% to 60% for a short time …..but they rarely stand the test of time as they tend to trade random trends with no enduring substance. As a result there is a lack of any noticeable edge being delivered as the profit target prevents this style of strategy from harvesting the unpredictable fruits of fat tailed events.
The only way therefore for a systematic price follower with a standard low win rate yet higher R:R to lift the bar and achieve a higher Pwin% without sacrificing the open ended profit potential delivered by fat tails is through diversifying across many uncorrelated return streams. The edge that diversification brings through the ‘free lunch’ is therefore specific to the price following technique. Fat tails occur across timeframes and across markets. Sometimes they are a restricted single event which offers some relief to the diversified systematic price follower and pays for some of the gruelling losses along the way….but the real bonanzas occur when fat tailed events start to cascade across timeframes and markets when collective market behaviour starts to reveal itself over the otherwise normal efficient noise of the markets.
Predictive methods are what are referred to as concentrated methods which seek to exploit the tendency of price in the future to move towards a predicted or estimated value. They therefore predate on the tendency of stable market conditions to oscillate around a known historic price point. For example technical traders who think they are ‘price following’ trend followers using retracement entries into a trend to obtain a higher R:R are actually deploying ‘predictive’ methods of entry. Furthermore traders who deploy mean reversion techniques on the basis that price is expected to revert to an estimated historic mean….and traders using fundamental techniques to assess under/overvalued prices with the expectation that price will move to an expected intrinsic value in the future are deploying a predictive mindset based on a future expectation.
On the basis that an estimated future value lies at some specific point in the future, you can now see how diversification about a future expected value actually interferes with this concentrated estimate of a future path and dilutes the predictive efficacy of this approach. Predictive models therefore require concentrated bets which leads traders towards an emphasis towards a single return stream approach which happens to offer the greatest potential for that future outcome to be achieved.
A price follower simply restricts their activities to more exotic market conditions to avoid the whipsaws of the normal day to day market noise, and under very wide diversification, fishes for the outliers that are known to unpredictably rise from time to time. It is only through very wide diversification that this can become very economical and of sufficient magnitude to generate long term sustainable wealth building returns. A price follower predates on market transitions that are of unknown duration and length. Given this degree of uncertainty, you simply follow price with no assumptions applied and see where it ends up. Predictive techniques applied to this very simple philosophy therefore totally stuffs things up by undermining the general principle of unpredictability which is a hallmark feature of this technique.
Now these fat tails occur at any timescale but they are unpredictable in nature.. They can occur at the M1 timeframe and above but the thing to note is that there is a lower bound to which price action emerges from…and that is the tick. There is a lower bound being the single transaction between buyer and seller but importantly there is no upper bound. What this means is that these fat tailed events (being very unpredictable) cascade up the timescale to become enduring features at the upper end of the spectrum. What appears initially as a tremor in a complex system of transition can cascade up into the higher timeframes causing the commencement of a trend with levy drift. So what starts out as an effective random disturbance in the market gets concentrated and more enduring in nature as more and more market participants are affected by this transition.
The unpredictable nature of fat tailed events means that on the short timeframe they are very rare indeed. It is not that enduring trends do not exist at the small timeframe, it is just there there is significant noise and mean reversion between these events that prevents trend followers from maintaining an edge in this small timeframe environment. HFT techniques are therefore almost all exclusively predictive or mean reverting in nature as the dominant form of arbitrage at the short timescale is based on an assumption of market stability.
However at the upper end of the system timeframe spectrum, most market activity is based on market transitions associated with mass participant behaviour arising from speculators, investors, hedgers, institutions and central banks etc. You rarely see markets not trending on the MN and weekly timeframe however frequently experience ranging stable market conditions on the short term timeframe. Mean reverting techniques are seldom successfully deployed over the longer term timeframe.
Now here is another important matter to consider when seeking to classify a trading strategy as being predictive in nature or price following in nature. Predictive methods like to have a high trade frequency when stable predictable market conditions exist. It is like playing on a roulette table with a persistent bias. You want as many spins of the wheel as you can muster while that bias persists. A strategy that therefore seeks higher trade frequency is therefore seeking to exploit the predictable opportunity. The rationale applied by the predictor is to have as many small wins as you can get while predictable conditions last because you know that when those predictable conditions cease, you are in a for a string of large losses. You therefore want to make hay while the sun shines with these methods. A central problem with these predictive methods is that traders assume these conditions will last. They therefore get hoodwinked by the markets that their strategy is invincible. Some even deploy Martingale methods in their belief that those rare events are just not considered likely and they therefore scale up their leverage with money management methods to capitalise on that predictable opportunity. As a result their focus shifts from risk management to profit taking….. so when markets transition the losses are fast and serious in nature.
Symptomatic of predictive strategies is their negative skew nature. Negative skew results from having many small wins with the occasional large loss. Now this can be tolerated while predictive conditions last, but when markets go into transition never to return to that historic equilibrium, these methods inevitably cease to work…catching many predictive traders with risk of ruin as consecutive large losses become the order of the day.
This is the exact reverse to price following techniques. Price followers are very frequently wrong. This forces them to strictly focus on risk management at all times as their bread and butter is not based on certainty, but rather market uncertainty. The pain for a price follower is the repeated frequent whipsaw. This seriously tests the psyche. To be wrong 60-80% of the time takes serious patience and the temptation is always there to change the rules and become a predictor. Despite the many frequent whipsaws, provided the losses are always small in relation to the occasional infrequent win, then that allows the price follower to survive. The characteristic signature of a price follower is therefore positive skew in nature (namely many small losses with the occasional large win). When markets go into transition, those occasional large wins go parabolic at the portfolio level resulting in a windfall.
Now here is another important fact about the markets. On the H4 and D1 timeframes where we like to play in catching the trends…..markets are not trending all the time. In fact if you drill out and look at the big picture, there may only be a few worthwhile trends every year. If you are too eager to catch the trends by relying on a single return stream….you are in for a miserable lesson in hard knocks where the whipsaw will eat you to death……so unlike the Predictor, Price Followers want to keep their trade frequency low and to only participate in those trends that appear to be significant and of an enduring nature that have a higher chance of becoming outliers than mere random trends of no substance. To compensate for the low trade frequency at the individual return stream level, you must diversify extensively to increase the trade frequency at the portfolio level otherwise you will experience protracted periods of stagnation and building drawdown. Price followers therefore learn that trading is a wealth building exercise as opposed to a cashflow exercise. They can never predict when markets will go into transition, but they just accept they do. In the meantime they learn to not expect instant cashflow but to diversify widely and to strictly preserve capital at all times until they do go into transition.
So at the individual return stream level such as a single market and timeframe, a price follower wants to avoid over-trading and only participate in significant moves where they capture the middle meat of the trending condition. They never cherry pick attempting to catch the tops and bottoms like swing trading techniques. Price followers therefore use filters to restrict trading activities to those periods where trends are more likely to exist. These filters tend to align any trade direction to the direction of the overall primary long term trend direction and avoid trading the fluff and noise of the market by distancing their entries away from more predictable reversal points that excite the Predictive trader. We therefore set traps in outlier zones waiting for those conditions to be met unlike the Predictor who uses sniper accuracy to pick the best entry condition. Sniper entries are not that important to the price follower, but market condition and general trend direction is very important.
The way to view it is a bit like this. Have a look at a monthly chart of any liquid instrument in FX
They all have trending periods. The problem however lies in the way you tackle them with a single system. Each variable in your system acts as a snag to whipsaw you out of a potential trending condition. It is your system design that prevents you from riding these great trends. Do not believe the wise sages who state confidently that there are better markets to apply price following techniques than the FX space. There is more than enough trending condition in these superb FX markets to keep you occupied for a life time and generate significant wealth building returns. The trick however is when playing the Law of Large Numbers you need Large numbers of different price following systems to capture the very variable different types of trending condition that exists. There is no one size fits all type of trend. Levy drift has significant volatility embedded in it which makes each trend different in nature.
A single trend following system cannot catch all these variations. You need a battalion of different variations on hand…where only a very small number of them will cut through the volatility. The price you pay is the large number of whipsaws you receive from trying to catch a wave from these large trends that we know exist and can easily see each time we open a chart.
The success of price following actually does not lie in only catching the trends as a much greater influence to your long term PL are the impacts of the inevitable whipsaws you receive from your incorrect system application towards trend following. What actually delivers the lasting edge in price following itself is not simply catching trends….but more importantly catching the outlier that lies outside the normal noise of the market. This is the way that you pay for the many whipsaws along the way from those systems that were snagged by virtue of their specific design constraints.
So in Summary here are some of the central takeouts to consider as food for thought from this post.
1. Just because a price pattern appears to be in a trend is this sufficient for a price follower to take an entry? The answer is just a big fat no. Context is just so important. What is this pattern in the context of overall price movement. Where is this price now in the context of it’s Maximum Adverse Excursion (MAE). Does it lie in outlier territory or is it a trend that exists within the normal everyday price movement? If the latter forget it….we are after outliers.
2. If I have 50 trade entries per year with a trend following technique with a particular instrument and timeframe, am I over-trading? Your answer is a big fat yes. Sure you will catch a trend when it occurs….but you will encounter significant drawdown with the whipsaws from over-trading. Have a look at a long term price chart and examine the significant trends that you would have liked to have caught. Be honest now….how many would be considered tradable and significant in nature. You only have to eyeball a chart over the long term on the H4 or D1 timeframe to realise that perhaps 3 trades a year is about as much as you can expect. This means that you need low trade frequency per market per timeframe per system and only trade during those extreme moves when trades are likely to be more enduring. Filters used to assist you from avoiding trading during the everyday noise are essential for price following techniques as it is only a few large wins that make your payday. The rest of the time should be spent avoiding losses.
3. I have a single trend following system. Is this sufficient to be classified as a price follower provided I diversify across different markets? The answer is no. You need lot’s of different trend following systems to capture the big moves. Trends comes in a vast array of different shapes and sizes. Most of your systems will catch segments of the big move but very few will catch all of the move.
4. I use a trend following system that waits for retracements and have a 60% win rate. Am I a price follower? The answer is no. You are a predictor. You are adopting a predictive technique that assumes that price will retrace in the future back into the direction of the trend. You are effectively a swing trader….not a price follower. Price followers operate off breakouts from extreme price moves. Predictors assume price will revert at this point. Price followers simply follow price in the direction of the move. You will most often be wrong…but you are after the extreme outlier move to make your bacon. The type 2 error is a serious error for a price follower. That error is the missing of an outlier trade. You can never predict an outlier in advance but you can develop a breakout technique to activate trade entries when price gets to extreme levels so you never miss a possible biggie.
5. Who cares what you say….I mean, trends are unique and depend on the technique you use to capture them? The answer to that is also a big fat no. If you have this opinion then please supply validated performance results of long term systematic trend followers who adopt predictive techniques and trade off retracements. You will find that they simply don’t exist.
6. Trend following is just so hard. Such low Pwin%. Mean reversion and other quantitative price action techniques are the way to go. If you believe this little nugget then once again, please provide an audited track record of a professional FM firm that deploys these techniques as their bread and butter. We know that Renaissance Technologies (Jim Simons), Two Sigma and now Winton Capital deploy highly quantitative methods that may utilise ‘predictive techniques’ but they do not share what they do. On the other hand we have a vast array of highly successful long standing systematic price following firms that do declare their techniques….and none of them owe their bread and butter to predictive techniques. The discussion here applies what they do to the world of price following in the FX space. Predictive techniques have a very short shelf life. All your time is assessing when to turn them off or on….which is a hindsight technique. You can never tell when trading the right edge when predictive certainty is lost. If you are predictive in your application of your trading strategy, then you also need to be predictive of when to turn them off. You cannot have it both ways.
So you may now be asking “Why is it necessary to separate strategies into these two buckets? Wouldn’t it be prudent to trade both forms of strategy under a diversified portfolio? That way you can capture both forms of alpha that are delivered by the market from time to time”. Once again….nice in thought but incorrect in practice.
We have already discussed how prediction requires concentrated bets surrounding the notion that we can estimate with a degree of certainty where price will be tomorrow based on recent predictable market oscillations…… so under models of diversification, a correct prediction will be compromised by those diversified bets which fail to reach their target. Diversification will therefore dilute the outcome of a predictive trading model.
Diversification is actually a form of risk management for traders that are uncertain about the future and have a low win rate with respect to their entries. Diversification ensures that all your efforts are not dedicated towards a single outcome and accordingly forces you to dilute your bets associated with a single outcome. Furthermore, diversification directed towards uncorrelated outcomes allows you to benefit from a principle referred to in physics as constructive and destructive interference of outcomes. This is where the ‘free lunch’ of diversification resides and is a significant windfall for price followers who are ambivalent towards what the future brings.
The principle is this. If we can imagine an array of random equity curves, by definition each random curve will have no connection with each other. When one curve goes up or one curve goes down, the other curves can go in any direction. They are uncorrelated to each other. Randomness effectively guarantees this as there is no connection between the return streams.
The free lunch of diversification resides in the way in which maximum drawdowns of each equity curve are suppressed by the balance of non correlated return streams that are not receiving maximum drawdowns at the same time. This feature is allowed for on the basis that the maximum drawdown for each random returns series will occur at different times in the random return series. Randomness and more importantly the non correlated nature of a random series ensures this. Luck may have a role to play where drawdowns of two random return series may coincide in the short term but a coincidence of max drawdowns at the same time is extremely unlikely over the long term. This is a feature that lurks within the Law of Large Numbers which is capitalised on by the diversified price follower.
This free lunch of diversification is specific to aspects of risk and not a feature attributed to aspects of return. It holds no benefit to predictive techniques that are certain about the future path, but is a significant benefit to price followers who are uncertain about the future path.
So in a $100K portfolio setting where we have $10K allocations towards 10 separate random equity curves which are by definition uncorrelated, when we summate the total result of the 10 separate return streams we find that the worst drawdown of each return stream is actually suppressed by the other return streams that do not possess a max drawdown at the same time. The principle of diversification suppresses the adverse random volatility that is present in the risk to reward signature of every investment asset by summation. The total profit outcome however is simply the addition of the overall result of each separate equity curve in the portfolio.
Now for a predictor who likes to be certain about a future estimate, they are less likely to choose to have 10 equally allocated separate $10K bets, but rather will have invested all their efforts (aka $100K) towards a singular outcome which they believe is the more likely. Of course in a predictive environment, they would be correct and take their windfall in their correct prediction, but in random or simply unfavourable market conditions (eg. transitioning markets), they will fail to obtain the benefit that diversification brings to the equation.
So now let’s refer back to the 3 broad market conditions where:
- markets can be efficient (noisy) in which the trade outcomes for both predictors and price followers are simply a result of luck with no edge;
- markets are predictive in nature and stable oscillating around some historic equilibrium where predictors blossom and positive kurtosis prevails; and
- markets are in transition and unpredictable in nature where fat tails lurk and negative kurtosis prevails and price followers receive their bonanza.
For a Predictor, the market conditions that support their premise are only when markets are stable and predictable in nature. In the other two market states, only luck will have a say in whether this method will survive or not….and over the Law of Large numbers, they converge towards risk of ruin if markets do not remain predictable in nature.
On the other hand, for the Price Follower, the free lunch of diversification assists them in surviving the adverse conditions of both the noisy or efficient market and the predictive market context. Diversification is a significant windfall for price followers in it’s ability to suppress adverse volatility arising from the inability to predict the future. Of course in transitioning markets, the impact of fat tailed events compound the fortunes of the price follower who is simply riding the tail of uncertainty. On the other hand, the fat tailed market condition is the death-knell for the predictor who happens to be sitting on the other side of the trade.
So let’s now explode a myth you might have heard before. The myth that trend following systems carry more volatility than predictive methods.
This myth is a feature associated with the incorrect assumption that markets remain predictable in nature. During predictable market conditions, the predictor blossoms and receives a very nice linear equity curve rising towards the heavens given their concentrated bets and high frequency of bets…..however over the long term where markets move between different states of predictable, efficient and unpredictable, predictive techniques simply stop working. You need to ask the question then, what is the true volatility of the predictive equity curve over the longer term where differing market conditions have a say? The answer is that it works when markets are predictable, but simply stops working when markets are not. Worse still, the reason why you cannot find any predictive technique that stands up longer than a few years is that predictive techniques meet risk of ruin head on.
Now as at the writing of this post I simply cannot find any predictive technique that can stand the test of time over say a 20 year period. Furthermore there is very little evidence of a professional FM that adopts predictive techniques surviving over this extended period apart from perhaps a handful of examples. Buffet for example is one well known exception who is a value investor, but you only need to examine his extremely volatile performance record to see the myth that prediction delivers less volatility. Three plus 50% max drawdowns since the 1970’s. Would you really have had the stomach to stick with that investment?
On the other hand we can find a very large class of long standing systematic price following firms that not only have outperformed Buffett but have done so with far less volatility. Just refer to the long term CTA performance results you can find on this website. Furthermore we can produce 20 year return streams with positive expectancy with simple price following models. These models are what we focus on in developing our diversified portfolios. The equity curves of these particular simple models are unappealing for the trader seeking a single system offering regular cashflow, but collectively as a very diverse portfolio, can offer stunning long term returns.
Predictors in general have a very short lifespan. They are successful when markets are predictable but they simply cease to exist when they are not. Strategy hopping is a central feature of the predictive camp and a necessity when markets no longer sing the familiar predictive tune. Worse still is the nagging feeling in the back of your mind when in drawdown that never goes away. Is it a natural drawdown…or is this a signal for risk of ruin? Prediction is all about profiteering with very little regard for the risk that is inherent in the risk-return equation.
So hopefully I have convinced you that it actually is not wise to be a little bit pregnant with both price following and prediction. It is not the nice linear rising equity curve of the predictors that compromise the overall portfolio…but rather it is the rapidly descending curve to oblivion when markets become unpredictable that is. We need to ensure that no single return stream compromises the diversified nature of the overall portfolio. Including predictive techniques in your portfolio has the ability to adversely affect your portfolio when predictions fail.
Price following is all about robustness. Inclusion of predictive techniques in your portfolio compromises this overriding ambition of survival while waiting for markets to transition.
We are price followers here chaps….and that is just the way we like it. I have dabbled with convergent predictive methods, but over the long term testing environment have found there is a sting in the tail in the need to decide when to turn them of or not…..so I now avoid them entirely. This is a cost we forget about and is the major reason why predictive methods fail over the long term. You might have a great predictive method that has delivered an excellent result over the last 5 years or so…..but it is the longer term that decides you fate. If you are not lucky in identifying a new predictive method each time following the inevitable market transitions, that success over 5 years will be whittled away and you are likely to severely compromise your capital account in the long term. The cost of finding the next predictive strategy eats away at your finite capital base…..but we don’t see that in the equity curves presented by the predictor. They are far too short to accurately describe the long term reality.
Price followers revel in being very uncertain about certainty. Our way around this uncertain dilemma is in taking many small diversified bets across a vast universe of possible uncorrelated outcomes. There is no single path of certainty into the future. There is just a vast array of many possible paths. We invest a small amount in as many different paths possessing the same broad trend following signature with a small positive expectancy while managing risk at all times.
We simply have faith that markets are unpredictable from time to time and can deliver super profits to pay for all that uncertainty along the way. It is not a blind faith statement of belief however. It is just a statement backed up by quantitative evidence of how markets behave. We just need to open our eyes and undertake due diligence about those successful funds that have stood the test of time over the long term. Pay less heed to the anecdote and pay more attention to the simple fact. Test every assumption you hear which cannot be quantitatively validated.
Trade well and Prosper
The ATS mob
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