Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part 1
by Van K. Tharp,
Ph.D.
At any given instant, over two billion bits of information impinge upon your senses. Yet consciously,
we can only process “7 +or - 2 chunks” of information.This tremendous reduction in information necessary to act
upon external signals or make decisions is accomplished through various “heuristic” rules or shortcuts.
These rules, which are essential if you are to make any decisions at all, are both a strength and a limitation.
They offer strength in that they provide tremendous shortcuts to making decisions. Decision-making would be practically impossible
without them. However, they are a major weakness because people are unaware they are even occurring or how much they distort
and delete information and bias our decision-making. For example, two such biases that make it difficult for most people even
to make money in the markets are the gambler’s fallacy and the tendency to be risky in the realm of losses and conservative
in the realm of profits—the opposite of what it takes to become a successful trader.
In this three-part article, we’ll explore several of these biases and how they might affect one’s
trading and investing decisions.We will learn about randomness, sampling variability, and data reliability. Today let’s
look at randomness and the gambler's fallacy.
The real “secret” to making money in the market has to do with developing an edge in the market
by using probabilities and proper money management.Unfortunately, people have trouble distinguishing between luck and skill
when it comes to market predictions. We are unable to comprehend the many factors influencing an event as complex as the movement
of a market. For example, if we had access to the number of buyers and sellers in the market at a given time plus information
about the conviction and capital behind each trade, we would probably find the markets to be very predictable. Thus, any uncertainty
you may have about how the market is going to behave at any given time is in you, not in the market. When you accept the fact
that uncertainty is in you, rather than in the market, you will suddenly find you have much greater control over your own
behavior towards the market. More importantly, you will have much greater control over the process of designing a trading
system and greater understanding of how that trading system works.
When you develop a trading system, you are essentially deciding upon a set of judgmental shortcuts to help
you make a decision. Yet people are completely unaware of how we make most of our predictions and judgments, let alone any
biases in the way we make them. Thus, the process of designing a trading system is replete with error and becomes a very difficult
process. In order to simplify the process, traders need to understand the following major factors:randomness, sampling variability,
and data reliability.
Randomness.
People want to treat the world as if they could predict and understand everything. As a result, one of the
most significant biases people have is to seek patterns where none exist and to invent the existence of unjustified causal
relationships. Traders don’t want to trade probabilities. They want consistency. For example, people fail to understand
that a random sequence can include a long string or what would be called a trend. Instead, they try to understand the “trend”
as something that it isn’t, instead of accepting that such phenomena occur.
Understanding and trading well are not necessarily the same thing. People don’t understand randomness,
yet they expect to be able to understand the market. They then build trading systems out of their attempts to understand the
market by identifying unjustified causal relationships without ever realizing they are doing it. It is this expectation to
understand markets that leads traders to search for “Holy Grail” trading systems that explain the “underlying
order” of the markets. There is nothing wrong with building a trading system based on microcosmic glimpses into how
the market might work; but you need to know what you’re doing when you’re doing it.You are not trying to understand
some mysterious underlying order in the markets. You are developing a set of rules whose long term expectancy gives you an
edge in the market, while allowing you to withstand the worst possible catastrophe that could occur in the short term.
For example, many people observe a relationship in the market and assume it explains how the market works.
Jack noticed when a particular pattern occurred in the market, it frequently moved 50 to 100 points higher.
He assumed the pattern meant that strong hands were moving into the market. And, when the market didn’t follow the pattern,
he became very confused. I said, “How often, when you observe this pattern, does the market move like that?”He
responded, “About 35% of the time!”Thus, Jack had simply observed a pattern that was quite profitable 35% of the
time. The rest of the time it had no meaning.
A relationship may occur only 35% of the time, and that may be something you can make money with, but it
has nothing to do with being right or trying to explain something. What you must learn is that most trading systems come out
of observations that have a certain probability of being correct. Those observations do not explain anything. Remember, a
trading system is just a set of rules to guide behavior, nothing less or nothing more. Apparent random fluctuations in the
market are caused by many more factors than you can possibly monitor in your system.
Develop the attitude of following rules
because they give you an edge in the market.
Avoid the need to understand or explain the market.
Because people attempt to understand and make order out of the market, they assume that the longer a trend
continues, the more likely it will suddenly turn around. More importantly, traders are usually willing to bet larger amounts
of money on that assumption. Thus, traders want to pick tops and bottoms in a trend—a behavior that tends to be as dangerous
as stepping in front of a moving freight train, hoping it will stop and turn around just for you. These biases are usually
referred to as the gambler’s fallacy. They have resulted in the ruin of millions of traders over the ages. The gambler’s
fallacy is one of those biases, which make trading difficult without a system and proper money management. However, traders
frequently develop counter-trend following systems because of this bias—usually with disastrous results.
At any given instant, over two billion bits of information impinge upon your senses. Yet consciously, we
can only process “7 +or - 2 chunks” of information.This tremendous reduction in information necessary to act upon
external signals or make decisions is accomplished through various “heuristic” rules or shortcuts.
These rules, which are essential if you are to make any decisions at all, are both a strength and a limitation.
They offer strength in that they provide tremendous shortcuts to making decisions. Decision-making would be practically impossible
without them. However, they are a major weakness because people are unaware they are even occurring or how much they distort
and delete information and bias our decision-making. For example, two such biases that make it difficult for most people even
to make money in the markets are the gambler’s fallacy and the tendency to be risky in the realm of losses and conservative
in the realm of profits—the opposite of what it takes to become a successful trader.
In this three-part article, we’ll explore several of these biases and how they might affect one’s
trading and investing decisions.We will learn about randomness, sampling variability, and data reliability. Today let’s
look at randomness and the gambler's fallacy.
The real “secret” to making money in the market has to do with developing an edge in the market
by using probabilities and proper money management.Unfortunately, people have trouble distinguishing between luck and skill
when it comes to market predictions. We are unable to comprehend the many factors influencing an event as complex as the movement
of a market. For example, if we had access to the number of buyers and sellers in the market at a given time plus information
about the conviction and capital behind each trade, we would probably find the markets to be very predictable. Thus, any uncertainty
you may have about how the market is going to behave at any given time is in you, not in the market. When you accept the fact
that uncertainty is in you, rather than in the market, you will suddenly find you have much greater control over your own
behavior towards the market. More importantly, you will have much greater control over the process of designing a trading
system and greater understanding of how that trading system works.
When you develop a trading system, you are essentially deciding upon a set of judgmental shortcuts to help
you make a decision. Yet people are completely unaware of how we make most of our predictions and judgments, let alone any
biases in the way we make them. Thus, the process of designing a trading system is replete with error and becomes a very difficult
process. In order to simplify the process, traders need to understand the following major factors:randomness, sampling variability,
and data reliability.
Randomness.
People want to treat the world as if they could predict and understand everything. As a result, one of the
most significant biases people have is to seek patterns where none exist and to invent the existence of unjustified causal
relationships. Traders don’t want to trade probabilities. They want consistency. For example, people fail to understand
that a random sequence can include a long string or what would be called a trend. Instead, they try to understand the “trend”
as something that it isn’t, instead of accepting that such phenomena occur.
Understanding and trading well are not necessarily the same thing. People don’t understand randomness,
yet they expect to be able to understand the market. They then build trading systems out of their attempts to understand the
market by identifying unjustified causal relationships without ever realizing they are doing it. It is this expectation to
understand markets that leads traders to search for “Holy Grail” trading systems that explain the “underlying
order” of the markets. There is nothing wrong with building a trading system based on microcosmic glimpses into how
the market might work; but you need to know what you’re doing when you’re doing it.You are not trying to understand
some mysterious underlying order in the markets. You are developing a set of rules whose long term expectancy gives you an
edge in the market, while allowing you to withstand the worst possible catastrophe that could occur in the short term.
For example, many people observe a relationship in the market and assume it explains how the market works.
Jack noticed when a particular pattern occurred in the market, it frequently moved 50 to 100 points higher.
He assumed the pattern meant that strong hands were moving into the market. And, when the market didn’t follow the pattern,
he became very confused. I said, “How often, when you observe this pattern, does the market move like that?”He
responded, “About 35% of the time!”Thus, Jack had simply observed a pattern that was quite profitable 35% of the
time. The rest of the time it had no meaning.
A relationship may occur only 35% of the time, and that may be something you can make money with, but it
has nothing to do with being right or trying to explain something. What you must learn is that most trading systems come out
of observations that have a certain probability of being correct. Those observations do not explain anything. Remember, a
trading system is just a set of rules to guide behavior, nothing less or nothing more. Apparent random fluctuations in the
market are caused by many more factors than you can possibly monitor in your system.
Develop the attitude of following rules
because they give you an edge in the market.
Avoid the need to understand or explain the market.
Because people attempt to understand and make order out of the market, they assume that the longer a trend
continues, the more likely it will suddenly turn around. More importantly, traders are usually willing to bet larger amounts
of money on that assumption. Thus, traders want to pick tops and bottoms in a trend—a behavior that tends to be as dangerous
as stepping in front of a moving freight train, hoping it will stop and turn around just for you. These biases are usually
referred to as the gambler’s fallacy. They have resulted in the ruin of millions of traders over the ages. The gambler’s
fallacy is one of those biases, which make trading difficult without a system and proper money management. However, traders
frequently develop counter-trend following systems because of this bias—usually with disastrous results.
Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part 2
by Van K. Tharp,
Ph.D.
Last week we looked at the randomness bias, which is the tendency people have to seek patterns where none
exist and to invent the existence of unjustified causal relationships. Because people attempt to understand and make order
out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. This manifests
into the "gambler's fallacy" which is a very common trap that traders fall in to and lose money when they do.
This week we will cover the topic of data reliability and biases that come up in this area.
Reliability. When people obtain information, they fail to assess how reliable their data is, where reliability
refers to the degree to which information reflects what is really happening. What traders observe in the market, with the
possible exception of floor traders and other market makers, is not the market, but some sort of visual representation of
the market. Thus, you are responding to a bar chart or a candlestick chart, or a point and figure chart, or to a representation
of the market profile, etc.—and not to the real market. Furthermore, few people make decisions from that information
alone. Instead, they distort the information even more by using indicators. These indicators are essentially shortcuts or
heuristics that people have thought up to condense, organize and make sense of the data. Interestingly, there are hundreds
of possible indicators—in fact, hundreds of thousands if you count various permutations and combinations—but most
traders use only about 20 of the most common ones in their decision making.
Market information is certainly distorted, and thus less reliable, when it is transformed into various indicators.
The less reliable the information is, the less value it has for predicting. Using our example from last week when Jack observed
patterns in the market, reliability is a measure of how accurately Jack’s pattern actually predicts a sharp move in
the market.Many people might notice a pattern or relationship in the market and then use it in developing a system without
ever determining how reliable the relationship is. Accurately knowing how well the pattern predicts the move is very important
information for any person wanting to develop a trading system.
A lot of the biases people have in their decision making tend to distort reliability in some way.For example,
we have many biases keeping us from knowing the true probability of an event happening. The true probability refers to the
actual probability of the event occurring as opposed to a statistical estimate of the probability from a small sample.
One such bias that keeps people from developing a good trading system is called the representation bias.
We tend to imagine that what we see or expect to see is typical of what can and/or will occur. Thus, if you observe a pattern
in the market, you expect it to occur. If you develop some concept about the market, you will look for data to support that
concept in the market, and you will probably find it whether it exists or not.
Once again, if you do not test objectively, and understand the results of the testing, you will probably
find that your observations, in developing a trading system, tend to confirm what you expect to find. Thus, the representation
bias is particularly important when it comes to assessing various trading signals. Are you considering the true probability
rate in assessing your indicator? That is, are you considering the percentage of time a particular indicator is followed by
the predicted outcome? Probably not!
I cannot overemphasize enough that trading indicators are merely ways of representing things of interest.
Does a significant chart pattern actually mean that buyers are about to dominant sellers, or vice versa, and produce a significant
price change? Of course not!It merely represents the possibility such an event might occur. Thus, any indicators you develop
for buying or selling in markets are your way of representing potential trading opportunities. It is not the opportunity per
se. Yet most traders, because of this particular bias, act as if the indicators are what they represent. It is like the indicators
(be they stochastic, RSI, or moving averages) start becoming reality, instead of a representation of a concept or a belief
in your head. When you realize this, you will become much more attuned to what trading is all about and less concerned about
indicators and understanding the market.
Another bias that keeps people from understanding the true probability of an event happening, and thus distorts
its reliability, is called the availability bias. We make predictions based upon how available the information is to us instead
of the true probability rate in the population. Thus, when you first start looking at the market, the data sample you use
will determine what you observe. In addition, strong emotional experiences, which affect how strongly information stands out
in our minds, tend to strongly bias our decisions.
When people start to develop an estimate of how much a trading system can earn in a year or how many winning
trades it will have, or any other estimate of its reliability, they tend to start with a set point. They then make adjustments
to that figure according to anticipated changes in conditions. The initial set point is called an anchor. The dangers associated
with using anchors in our decision making about trading systems (or anything else) is called the anchoring bias.
The first danger is that you assume there is some relationship between the anchor and what you are predicting.
For example, in order to predict the price of the market a year from now, you would probably start making your estimate with
the anchor of today’s price. Over a short period of time it may be an accurate basis for beginning to make an estimate
(i.e., today’s price is a good starting price for forecasting the price in two or three days), but over a longer period
of time the strategy does not allow for the unpredicted or the unexpected.That is why one of the most important parts of developing
a trading system is extensive planning. And this extensive planning should include a careful consideration of everything that
might go wrong.
The second danger in the anchoring bias is that people make an assumption that the initial set point or
anchor itself is meaningful. For example, if you use the results of your testing to predict future results, you are assuming
that those results are meaningful and will not change dramatically over time. This is probably true if your testing data is
different from the data you used to develop the system and included enough samples to make future estimates reliable. But
those are big “ifs.”
Another bias that tends to have a significant effect on trading decision-making is hindsight bias. People
tend to see relationships in the market after they occur, and then assume they knew it all along. It’s very easy to
point out such a relationship after it occurs. I’ve worked with a number of clients who claim that they cannot follow
their signals. However, what tends to happen is that they do not recognize the signals while they occur. Instead, they see
many possibilities in the data.But once the signal is complete, it is too late! They then criticize themselves for not taking
it when it occurred. The typical response is, “I knew it all along. Why didn’t I take that signal?”
This problem will not occur if you write down your criteria for a signal in enough detail so that it could
be entered into a computer.You can then make a checklist for your signal (or computerize it). Once you do, you will always
see a signal when it occurs or the computer will see it for you. Thus, you really will know whether or not you actually knew
it all along.
Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part 3
by Van K. Tharp,
Ph.D.
So far in this series, we have looked at biases regarding randomness, which is the tendency people have
to seek patterns where none exist and to invent the existence of unjustified causal relationships. Because people attempt
to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly
turn around. This manifests into the "gamblers fallacy," which is a very common trap that traders fall in to and lose money
when they do. And, last week we examined data reliability as it relates to the degree to which information reflects what is
really happening. We focused on the representation bias, availability bias, anchoring bias, and hindsight bias.
Today we continue with four common misuses of sampling variability in relation to system development, and
finish with some tips to help overcome all of these biases.
Sampling Variability. Most people misuse the basic concepts of sampling theory in making predictions and
designing trading systems. The first principle, which is highly abused, is that you can make more accurate estimates of the
true population probability from larger samples than from smaller samples.In other words, you can get a much more accurate
estimate of the reliability of a trading signal from a large sample than from a small sample.In our earlier example, Jack
said that his pattern predicted a higher market price 35% of the time. The accuracy of his estimate would be much better if
it were based on 100 measures of the pattern than if it were based on 20 measures. Unfortunately, most people follow a bias
called the law of small numbers. Once they observe a phenomenon occurring a few times, they believe they understand it and
know its likelihood.
People tend to form their opinions based on a few cases, and fail to revise their opinions upon the receipt
of new data to the extent that they should, based on probability theory. Traders tend to stick to their old opinions rather
than updating them as new information becomes available.
We call this the conservatism bias. This points out the importance of doing a thorough, objective testing
of your market observations on a set of data that is different from the data in which you made the observation.
Traders want consistent information from various sources, such as three oscillators based upon the same
data (which of course are likely to show similar results). However, this consistent information will lead to increased confidence,
but not to increased accuracy of prediction.
We call this the consistency of information bias. What it means is that traders are likely to add more indicators
in order to get more consistent information so they can feel confident about it. But adding more indicators is not likely
to give one more accurate information. This points out the importance of developing a simple, robust trading system.
A fourth major misuse of sampling variability is that people fail to understand that the amount of variability
in a sample is positively related to the degree of randomness in the sample. Once you have observed a relationship in a set
of data, it is no longer random with respect to that relationship. The more relationships you observe with respect to various
parameters in the data, the less random the data is with respect to those parameters. Unfortunately, system developers frequently
make this mistake when they use a sample of data to optimize a system and then test the system on the same data. Once a set
of data has been used to optimize a system’s parameters, then it is not random with respect to those parameters.As a
result, when you use the same sample of data to test the system, you can expect it to do well in the test, but this has nothing
to do with how it will work as a system trading real money. Data must be tested on a sample that is independent from the sample
used to observe the original relationship.
How to overcome judgmental biases
You probably cannot totally overcome the effect of the various judgmental biases. One reason is that one
of the most prevalent biases is the ego bias in which people decide, “Yes, I understand all of this, but it applies
to other people, not to me. I’m a very special person and it doesn’t apply in my case.”Nevertheless, if
you are willing to assume you are human and that these biases do apply to you, then you can take steps to minimize their impact.
Remember, your job as a trader is to find an edge in the markets. You must capitalize on that edge, so you
will make money in the long run, while doing everything possible to preserve your capital in the short run. As a result, I
strongly recommend that you spend a lot of time writing down your objectives and designing something to meet those objectives.
What is an objective?
Your objective is your goal, your target. It is the thing that you want to attain or accomplish.
Objectives set the roadmap for the entire system development process. How would one know how to get someplace
if they didn’t know where they were going first? It is easy enough to see that if one trader had an objective such as
“I want a system that trades long-term stocks, that requires my attention only once each week and makes 20% per year”
compared to a trader’s objective that was “I want to actively trade my mother’s retirement account for four
hours each day, without holding overnight positions” then two completely different systems would be required. The objectives
or goals are very different. There are endless configurations of objectives. The point is you need to specifically know what
it is that you are trying to attain; and only then can you develop a trading system that will help you attain it.
Observe the markets as an artist would. Be creative. Determine relationships in the market that occur over
a wide variety of markets and market conditions. Remember, you are not trying to explain the markets, but just determine some
market relationships you can capitalize upon. The more widespread the relationship—does it occur in different markets
and different types of markets—the more likely you will be able to profit from it.
Be willing to be unique. Think about how you can best represent the price of the market. Notice relationships
in the patterns of price movement that you can capitalize upon. Once you have observed some relationships, figure out how
to measure them. If you can avoid common indicators, then you probably have a real edge.
Simple is probably better. Why? Because the more complex the relationship, the more likely it is to be unique
to particular markets and the less likely it is to make you money.
Be sure you understand the edge the relationships you observe in your data give you. Do your observations
make sense? How do they give you an edge? Also be sure that you can write down your observations in enough detail so you can
recognize them as they occur and not just in hindsight.
Understand money management so you can capitalize on your observations. Trade according to a predetermined
plan rather than your emotions.
Be sure to objectively test your observations on extensive market data that is different from the data you
used to observe the relationships in the first place. Objective testing is very important because with subjective testing
you will tend to see what you want to see. In other words, the market will confirm your expectations.
Many of the psychological issues described in this article are covered in my How to Develop a Winning Trading
System that Fits You workshop and home study program.These programs will help you clarify your objectives, and then show you
how to design a trading system to meet those objectives.
About the Author Dr. Van K. Tharp is the founder and president of the Van Tharp Institute and stands out
as an international leader among professional trading coaches and consultants. Helping others become the best trader or investor
that they can be has been Tharp’s mission since 1982.
Tharp collected more than 5,000 successful trading profiles in a 10-year study of individual traders and
investors, including many of the top traders and investors in the world. From these studies he developed a model for successful
trading and investing that other people can adopt and learn. He also developed The Investment Psychology Inventory Profile
to help people better understand their strengths and weaknesses in relation to trading or investing and has produced a number
of home study courses.
His unique learning strategies and techniques for producing great traders are some of the most effective
in the field. Over the years Tharp has helped people overcome problems in areas of system development and trading psychology
and success-related issues such as self-sabotage.
Tharp, who now lives in North Carolina, received his Ph.D. in psychology from the University of Oklahoma
Health Science Center in 1975. He is a certified Master Practitioner of Neuro Linguistic Programming (NLP), a Certified Master
Time Line Therapist, a certified Modeler of NLP, and an Assistant Trainer of NLP.
He is the author of three books, Safe Strategies for Financial Freedom with co-authors Steve Sjuggerud and
D.R. Barton, Trade Your Way to Financial Freedom, and Financial Freedom Through Electronic Day Trading.
Outside of trading, Tharp has a strong interest in spiritual studies, is an avid stamp and art collector
and is a big supporter of the Green Bay Packers. He is also a movie buff, loves going to theatrical productions and shows
and is a big fan of music and dancing (everything from ballroom to the disco dance floor).
He has a son, Robert, from his first marriage and has been married to Kala for 12 years. Her niece, Nanthini,
from Malaysia lives with them and is like a daughter who they are putting through college.
