Algorithmic and Mechanical Forex Strategies | OneStepRemoved

Less Is More: The Halo Effect & Green Lumber

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It is often said that system traders spend too much time attempting to perfect entry and exit points. What if we expand that idea and take a look at whether or not we are putting too much effort into all of our trading efforts?

There is more to be learned from actually trading than is taught in classrooms. You can trade successfully right now, despite the fact that there are thousands of people who have more knowledge than you.

When Two Things Are Not “The Same”

In Book IV of Antifragile, Nassim Taleb spends a good portion of the chapters addressing the lack of actionable knowledge that can be gained from institutional learning. He strongly advocates a self-directed style of learning as opposed to the standard university approach.

As systematic traders, we are forced to follow the self-directed approach that Taleb mentions because systematic trend following strategies are not taught in expensive universities.

“When you are fragile you need to know a lot more than when you are antifragile. Conversely, when you think you know more than you do, you are fragile (to error).” – Taleb

Taleb uses both the Halo Effect and The Green Lumber Fallacy to illustrate his point that knowledge about a topic does not necessarily lead to success in that field. In trading, it is popular to discuss why markets behave in different ways.

This need to understand why something happens increases fragility. In order to make our trading systems more antifragile, we must focus less on what we know and more on what we don’t know. We don’t know the future.

Halo Effect

“The more interesting their conversation, the more cultured they are, the more they will be trapped into thinking that they are effective at what they are doing in real business (something psychologists call the halo effect, the mistake of thinking that skills in, say skiing translate unfailingly into skills in managing a pottery workshop or a bank department, or that a good chess player would be a good strategist in real life). – Taleb

The most commonly used example of the halo effect, which was first researched by Edward Thorndike, occurs when our opinion of someone’s character traits are influenced by their attractiveness.

The halo effect applies well to brand marketing. The amazing popularity of Apple’s iPod has resulted in great success for many of its other products. I personally have experienced this effect with Apple products.

After being a long time iPod user, I purchased an iPad a few years ago and was completely blown away. My enthusiasm for the iPad convinced me that I next needed to acquire an iPhone. Six months later, I was the proud owner of an iPhone 4S, which has a woman inside of it that talks to me. Now that I had an iPod, iPad, and iPhone, the decision on what kind of laptop to buy was already made for me. I wanted a MacBook Air.

While the halo effect worked out nicely for Apple, Taleb suggests that it increases fragility. In the last part of the quote above, he compares the skill of playing chess with real life strategy. The obvious connection to trading is that knowledge about trading does not translate into profitable trading.

An extensive working knowledge of the Black Scholes Model will make you sound intelligent at a dinner party, but there is a lot more that is needed to actually trade options successfully. A trader with far less knowledge can benefit simply by not over thinking his trades.

He is free to experiment with trial and error the way Taleb suggests. The learn as you go approach is far more antifragile. This is how the Green Lumber Trader operates.

Green Lumber 

Green lumber fallacy

You don’t have to know everything about the lumber industry to trade it.

The Green Lumber Fallacy is a reference Taleb makes to a commodity trader who traded “green lumber” successfully, even though he didn’t know why it was called that. The theory behind this example is that the information that is generally associated with a market may have little to no bearing on that market. Taleb also gives an example of a Swiss franc trader who “could not place Switzerland on the map.”

“So let us call the green lumber fallacy the situation in which one mistakes a source of necessary knowledge – the greenness of lumber – for another, less visible from the outside, less tractable, less narratable.” – Taleb

Again here, we see success coming more from the lack of knowledge than an abundance of it. This idea reminds us that many of the issues and strategies discussed on television simply have no bearing on our trading results. Rather than drowning ourselves in data, the correct way to build a successful system is to look at less data. Less truly is more.

Making Trading Systems More Antifragile

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In order to make trading systems more antifragile, we must focus on changing their risk exposure. If your primary concern in trading is your system’s profitability, then you are setting yourself up for an epic failure. The first and foremost concern of any trading system absolutely must be the risk within a system.

Risk of Ruin

In Book III of Antifragile, Nassim Taleb presents the argument that profit is a secondary goal in business. He argues that anyone who primarily focuses on profit is underestimating their risk exposure.

This concept applies directly to trading systems. Far too many traders use potential returns as the measuring stick for a trading system. Following Taleb’s argument, traders should put far more emphasis on the nature of the system.

“This fragility that comes from path dependence is often ignored by businessmen who, trained in static thinking, tend to believe that generating profits is their principal mission, with survival and risk control something to perhaps consider – they miss the strong logical precedence of survival over success.” – Taleb

While generating profits is certainly the end goal of any system, the ability to generate those profits requires the survival of the system. If the system goes bust at any point, then those future profits mean nothing.

Even if the system generates huge profits for years, if there are significant risks that could eventually catch up to it, then the system is just trading on borrowed time. The most important criteria for assessing a system’s fragility is its risk of ruin.

risk reward comparison

Risk and reward should be balanced against the long term objective of continuing to trade.

The least desirable way to protect against risk of ruin is to decrease the fragility of the system. This may sound like common sense, but far too many traders never make the connection.

As I covered earlier this week, there are three way of doing this: increasing the system’s win rate, increasing the system’s profitability, or decreasing trading size. Of these options, the only one that is completely in the trader’s control is the amount of risk their capital is exposed to.

Sensitivity to failure is best analyzed by adjusting the accuracy percentage and payout ratios. If you trade a trending system and the average payout drops by 20%, what happens to the system? Many trending systems completely fall apart.

Sometimes, a difference of 10% between the historical returns and future observations makes the difference between decent profits and huge losses. This is far more true when the expected percent accuracy falls and the payoff falls, too. Minor errors in observation lead to drastically different outcomes.

Fragility is Relative to Upside/Downside Risk

In the preceding chapter, Taleb explains that fragile systems have more to lose than they can gain. The opposite is true for antifragile systems. They have more to gain than to lose. They have a limited downside.

“You are antifragile for a source of volatility if potential gains exceed potential losses (and vice versa).” – Taleb

This further supports the argument that risk of ruin should be the primary concern when evaluating a trading system. Regardless of the system’s apparent upside, if the downside is too great, the system is no good. If the potential exists to lose everything, there is no possible upside that can balance that.

Long Term Capital Management

Taleb uses the example of a gambler to illustrate that no matter how good his strategy is, if he is exposed to the risk of losing everything then nothing else matters. The same can be said of anyone who’s trading system exposes them to too much risk.

It doesn’t matter how efficient the strategy is or how impressive the returns are if the risk of losing everything is too great. Risk of ruin trumps all other factors because it has the ability to end the game.

Long Term Capital Management (LTCM) provided an excellent example of this concept in the late 1990s. The fund was believed to have superior strategies implemented by brilliant traders and many investors expected the strong returns to continue indefinitely. The problem is that no one was concerned with the downside risk, leaving the fund vulnerable to a Black Swan event, which happened in 1998.

The combination of some unexpected events with a big appetite for leverage proved to be disastrous for LTCM and its investors. LTCM believed that it had smoothed out volatility and could provide consistent returns. As we all learned, the short-termist obsession with pretty Sharpe ratios on high leverage came at the cost of making a blowup inevitable..

Naive Intervention – Noise & Too Much Data

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The best way to improve your trading system is to leave it alone. The best way to increase your returns is to turn off the TV and stay off of the internet. The best way to trade is from a cabin in the mountains with data that is a week old. That’s not what you’re used to hearing, is it?

Overwhelmed With Data

“A very rarely discussed property of data: it is toxic in large quantities – even in moderate quantities.” – Nassim Taleb

We have more data at our fingertips than any generation before us could have ever imagined. We can pull real time market information out of thin air in any small town that has a coffee shop. We can watch multiple 24 hour cable news networks from a hotel room anywhere in the world. Not only is data accessible, it’s surrounding us, and closing in fast.

The problem with all of this data is that it can be too much. We can have trouble seeing the forest because we’re too busy staring at the trees. This is especially true in the trading world. It is far more exciting to trade every hour than every month. According to your television, trades should depend on the next non-farm payroll report. But what if they’re all missing the point. What if simpler is better?

Simpler is better. Find a trading system with a long term track record, and then only track your returns over the long term. However, this is easier said than done.

Naive Intervention

In Book II of Antifragile, author Nassim Taleb presents his concept of naive intervention. This happens when we unnecessarily interfere in an attempt to help, but end up doing more harm than good.

Naive intervention

I *never* mess with my open trades… ever… I promise.

The most classic example of naive intervention is Alan Greenspan continually interfering with the economy in an attempt to smooth out the cycles. Despite his intentions, by smoothing out the bumps along the way, Greenspan dramatically increased the fragility of our economy. The result was a complete financial meltdown in 2008.

Many traders attempt to do the exact same thing with their trading systems. In an effort to avoid taking any losses, many traders either overtrade or constantly tweak their systems. This can lead to missing out on the big moves because of focusing too much on the smaller moves. I have fallen into this trap many times throughout my trading career. I lost count of the number of times that I have interfered with or adjusted systems based on what turned out to be insignificant data points.

The Neurotic Fellow vs The Mafia Boss

Taleb uses examples of a neurotic coworker who freaks out over everything and a calm mafia boss who chooses his words very carefully. The neurotic fellow overreacts to even the slightest changes, while the mafia boss almost never reacts to anything. He waits for only the most important times to speak up.

This is the attitude we need to take with our trading systems. There will be ups and downs, but we shouldn’t rush in to save the day and fix all of the problems at the first sign of a slight loss. We need to wait for the most significant places to intervene. It can be very difficult at times to tell the difference between the general noise and a signal that something needs to be adjusted.

My Struggle To Fight The Noise

Throughout my evolution as a trader, I have had my struggles with overexposure to data. I have been suckered by cable networks that scream “Buy, Buy Buy!” but never tell you when to sell. I have tried trading systems that I didn’t understand, only to question them at the first sign of weakness. I have bought on insider tips as well as expert analyst recommendations. None of this worked because it was all noise.

Once I evolved past that level of noise, I was introduced to the next level of noise. Every time I opened a position, I became addicted to refreshing the web browser to calculate my up-to-the-second return. I then found myself making decisions based on the price movement over the past five minutes even though I established the position based on the last five months. This was a cruel addiction.

The struggle for me today is in determining the difference between the real signals and the noise. I have gotten dramatically better at focusing on the big movements and tuning out the tv networks and penny stock twitter experts.

Focusing On The Big Stuff

“The best solution is to only look at very large changes in data or conditions, never at small ones.” – Nassim Taleb

In almost any career or hobby, it can be very easy to lose yourself in the details. It happens to everyone, everywhere. The power of the urgent issue at hand to consume our entire world can lead us to spend all of our time obsessing over things that aren’t important in the long run. We have a passion for the moment, and many times, the moment is just a head fake.

Antifragile Trading – Enhanced By Volatility

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In Antifragile, author Nassim Nicholas Taleb presents the argument that the opposite of fragile is not simply something that is unaffected by stress or pressure. He argues that there is a quality called antifragile where something actually improves as a result of that stress or pressure. Taleb categorizes things on a scale from fragile to antifragile, with a mid-point he calls robust.

When this idea is applied to trading, the first comparison that jumps out at us is between buy and hold investors and systematic trend following traders. Systematic trend following traders excel under extremely volatile situations, are virtually ignored by intellectuals in their field and are capable of handling deviations because they are not predictive in nature.

An Illustration of The Antifragile Concept

Taleb illustrates his concepts of fragile, robust, and antifragile through Greek and Roman mythology.

Fragile is represented by the story of Damocles, who was invited to a dinner at which there was a sword hanging over his head that was held up by a horse’s hair. Damocles is considered fragile because at any second the hair could snap dropping the sword onto him.

The concept of robust is represented by the Phoenix, which is a bird that is able to be reborn from its own ashes. No matter how many times you attempt to destroy the Phoenix, it continues to return to its original state, unharmed.

Antifragile is represented by the Greek Hydra, which had multiple heads. Every time one of its heads was chopped off, two more would grow back. Any attempt to hard this creature actually made it grow stronger. This is the core concept of antifragile.

An Application To Trading

One of the characteristics that can help measure the fragility of something is how it responds to volatility. This allows us to easily apply this concept to trading, because volatility is actually measured in most markets.

VIX Monthly shows antifragile periods of strength

A monthly VIX chart dating back to 1985

If we look at a long term chart of the VIX, we can see four distinct areas of extreme volatility: The Market Crash in 1987, The Asian Currency Crisis in 1997-98, The Dot-Com Bubble & Crash from 1998-2002, and the Financial Collapse in 2008. These highly volatile periods were high stress situations that would have made antifragile trading strategies better while making fragile strategies worse.

It is no coincidence that it was during these exact periods that systematic trend following traders posted some of their best years, and at the same time, buy and hold investors lost fortunes.

Systematic trend following strategies are not only built to handle these kinds of high stress, high volatility situations. They become stronger from them simply because they provide traders with a way to change direction. This ability to go with the flow during even the most chaotic times is a stark contrast to the rigidity of a buy and hold strategy where the investor has no choice but to sit and watch their portfolio crumble.

Overcompensation & Overreaction

“Intellectuals tend to focus on negative responses from randomness (fragility) rather than the positive ones (antifragility).” – Taleb

Again here, we can see a clear application of this with respect to trading during high volatility periods. In each of our four high volatility trading periods from the past 25 years, most of the intellectuals and so-called market experts were focused on the negative responses, which were the buy and hold investors who were losing their fortunes left and right.

During each of these periods, there was very little focus on traders who were benefiting from the increased volatility. The antifragile traders seemed to go unnoticed, and we know now that systematic trend following traders where the ones who were benefiting from these volatile markets.

Layers & Deviation

Taleb also discusses the complexities that can arise when looking at fragility through different layers and dimensions. He illustrates that since what is good for the antifragile is bad for the fragile, then what is good for the fragile is likely bad for the antifragile.

We have already discussed the huge success that antifragile trend following strategies have seen during times that were terrible for fragile buy and hold strategies. When the inverse situations occurs where markets have little volatility, we have seen that systematic trend followers and buy and hold investors can produce rather similar results. The key difference though, is that the antifragile systematic trend followers have the ability to adjust when a black swan shows up.

“When you are fragile, you depend on things following the exact planned course, with as little deviation as possible – for deviations are more harmful than helpful.” – Taleb

He continues to explain that the fragile is very predictive and that being so predictive is exactly what causes fragility. This is the problem with buying and holding with the expectation that a position will go up over time. The entire strategy is predictive in nature, and that is exactly why it becomes fragile. It can’t handle a deviation from what it predicts.

On the contrary, a systematic trend following approach can, by definition, handle any deviation from what is expected because it simply goes along with that deviation. This ability to adapt and change is magnified during periods of high volatility, which is when systematic trend following is at its best.