As a trader I believe in technical analysis and use it daily to trade the currency market. Technical analysis is still better than artificial intelligence and machine learning driven trading algorithms. In this post, I want to discuss how we can explain technical analysis using behavior finance. Did you read the post on GBPCAD long trade that made 1000 pips with 30 pips stop loss.
As day traders we fight the randomness of the financial markets on a daily basis. Efficient Market Hypothesis stipulates that markets are inherently random and it is almost impossible to beat the market randomness. But those who use technical analysis daily argue that they can predict the financial market based on chart patterns at least in the short term if not on the long term. Long legged doji is an important candlestick pattern that you should take note of.
Modern financial markets are sentiment driven. Fundamentals do play a role in the long run but in the short run price action is all sentiment driven. If you want to understand the market sentiment you will need to understand the crowd psychology. Sentiment is nothing more than the collective psychology of the market participants. Watch this documentary on the life of a professional forex trader.
As traders we are constantly analyzing the charts and making trading decisions which is essentially when to buy and when to sell. As investors also we are making investment decisions. Decision making is what is happening when we are trading and investing. Behavior Finance is a new subject the makes an attempt to explain how we make decisions under uncertainty. In this post, we will take a journey into the world of Behavior Finance and see if we can use it to explain technical analysis. Let’s start with Behavior Finance. Once we have some understanding of Behavior Finance we will use it to explain Technical Analysis.
The Rise of Behavior Finance
Traditional economic theory talks about a rational economic man who has been trained since his birth to think rationally under all circumstances. Rationality implies that decisions are being made with full knowledge of what is happening around us. Soon people started questioning the rationality assumption. We all know we seldom make rational decisions rather most of the time our decisions are emotional in nature. Learn how to make 200 pips daily with a small stop loss.
In the last few decades Behavior Finance emerged as a new subject that challenged the notion of rational decision making under uncertain conditions. Trading is essentially a decision making process in which we constantly analysis the price data and make a judgement on risk and uncertainty. As said above most of the time we are making emotional decisions. Behavior Finance studies how we make our investing decisions based on uncertainty.
Behavior Finance is a new attempt at understanding human financial decision making in the light of what human psychology has shown us how humans actually act and react to uncertainty. This is unlike the rational economic man who was supposed to behave without any emotions ideally to any uncertain situation. A rational human is supposed to analyze the uncertain situation in a logical and unemotional manner under conditions of perfect information. Reality is far different from this.
Suppose you are a rational economic man. You want to buy a car. This is how your decision making process will take place according to the classical economic theory. First you make a list of why you need a new car and why a new car will be more cost effective as compared to using public transport. So first you calculate the monetary benefit that you will drive by buying a new car. If the monetary benefit is worthwhile as compared to the other alternatives like using public transport, you decide you need a new car.
Now that you have decided to buy a new car, you go about buying one. But you don’t enter a car showroom straightaway and buy a car that you like. First you make a list of cars that you think you should buy. Then you compare the prices. You also make a list of all vendors that are good in reputation and can give you a discount. The car list that you made contains a thorought analysis of each car against the others. Once again you make a cost benefit analysis and make the final decision based on it. Learn how to make 1000 pips per month with very low risk.
So as a rational economic man, you will first gather all publicly available information and once you have perfect information, you will do a cost benefit analysis and make your final decision. But you will be laughing on reading how you make decisions as a rational economic man. You will say this is all a caricature and a joke and you never make your decisions in this manner. But there is some element of truth in the rational economic man model. When we buy a new car, we do consider whether we really need a new car and what will the cost of buying a new car and running it. So something parts in the rational economic model are indeed true.
This is how we make our decisions. We don’t make a thorough research and then a cost benefit analysis like a rational economic man. We carry out much simpler calculations in our mind when we compare different car models and different vendors. We also involve our emotions in the decision making process. Maybe we have much greater emotional preference for a certain model despite the fact that it is a bit costly.
We all know that we are carried away by fear, greed and the emotions of others around us especially if we are in a crowd. All these emotions unconsciously enter our decision making process. So we humans are a mix of rationality and emotions. We have an inherent limitation when it comes to solving complex problems. At times we can make unexpected, illogical and counter intuitive decisions. So as investors and traders, we can act illogically based solely on emotions.
As said above Behavior Finance uses psychology a lot in explaining how we make financial decisions. But there is a problem. Psychology as a subject is not built around a single unified theory. Rather it revolved around a number of theories and hypothesis that are used to explain the experimental results. Since Behavior Finance depends heavily on psychology, it gives a fragmented appearance. Whatever. This is what we do. We divide the subject of Behavior Finance into six categories:
- Complexity
- Perception
- Aversion
- Self
- Society
- Gender
Aversion is a very important and powerful concept that is used to explain the investor behavior a lot. Most investors show very good performance when they are paper trading with virtual money as no emotions are involved. Once they start trading on the real account, their performance suffers and becomes very poor because they start taking emotional decisions. Since real money is involved most of the time they are hesitant , emotional and illogical when making decisions. A good training for a trader develops poise in him and makes him emotionally detached when making the trading decisions.
There are two types of investment styles. One is called Value Investing. Warren Buffet who was at one time the world’s richest person is fond of value investing. In value investing, you first study the company before investing in its shares. You questions like what are the profits of this company after taxes. How many shares of this company are in circulation. What is the profit as percentage of turnover? What is the market share of the company and does the company has an edge in the market?
Is the company business model robust and will survive the test of time? Coke has a product that can last for a long time as compared to Apple iPhone which is technology based and will become obsolete with competition and new innovations. How much debt the company has and can it pay it back? You also do a SWOT of the company and so on. Read about the Million Dollar Trading Challenge Trading Plan.
The idea is to gain a thorough understanding of the company and its business model before you decide to invest in its shares. Once you have done a thorough analysis of the company you make an assessment of its fundamental value known as inherent value. If the company shares are trading at a higher value than the inherent value you wait for the share price to fall before you invest in them. You are a long term investor. Warren Buffet is a long term investor. Value investing suits long term investors who have a long investment horizon.
The second approach to investing is based on Technical Analysis. In Technical Analysis, you look at the price charts solely. You don’t bother about studying the company balance sheet and income statement. You look at price charts and look for certain chart patterns like the double top, double bottom or the head and shoulder pattern etc. Once you have identified a breakout pattern you trade it and make profit. Your time horizon is short and you are making profits by speculation.
This approach is also popularly known as day trading and swing trading. In day trading, we open and close the trades in one single day. In swing trading, we open a trade and ride a trend till it lasts which can be a few days or a few weeks. We are just speculating, we are not interesting in determining the inherent value of the company shares. For example we are not interested in Apple’s long term growth potential. We just look at Apple’s stock price charts and once we identify a chart pattern like the death cross we trade accordingly.
The third approach is more recent and has become very popular. This approach is based on quantitative finance, statistical models, artificial intelligence, machine learning and deep learning. This approach is also known as Quantitative Trading or Algorithmic Trading. Algorithmic trading is now very popular with almost more than 80% of the trades being placed on Wall Street by algorithmic trading systems. Watch this documentary on hedge fund trading strategies.
Algorithmic trading is very sophisticated and specialized and has impacted the market in ways that has changed the way market behaves. Flash crashes have become more frequent. Price moves have become very fast as algorithms are pretty fast in exploiting arbitrage opportunities. We humans cannot react fast enough. High Frequency Trading HFT is a domain that is dominated by these algorithms. There are arguments. Some claim HFT is bad for the bad and is responsible for flash crashes. Other argue that HFT is good for the market and has reduced the spreads. Jury is out.
Whatever approach you use, you can be wrong many times in your decisions. People claim that algorithmic trading takes the emotions out of your trading. It maybe true. But algorithmic trading is just what the programmer has coded and code can be dead wrong in reading the market sentiment. So there will always be mistakes. Markets are just too fickle. They can change their sentiment in a moment. Algorithmic trading can be wrong and incur big losses. Meet the London Millionaire Forex Traders.
Whatever approach of trading we use, we need to understand how the market works and behaves. Markets are just depicting what we the participants are thinking at the moment. We call it Crowd Behavior. We will talk about it more in this post. Price movements are due to the buy/sell decisions that we are taking as market participants. Now some participants are big players like banks and hedge funds and their buy/sell decisions will move the market more as compared to us retail traders who trade with a 5 standard lots most of the time.
So whatever decisions we are taking on our level at getting reflecting in the overall price action. As said some players have more market power like the banks and hedge funds as they have the capacity to open big orders. But whoever we are. We have a tendency to act in irrational and illogical manner. This can be the result of imperfect information. Most of the time we can’t get complete information. At times we can behave in a totally unexpected manner. Learn swing trading and make 200% in 20 days.
We Are Irrational Mostly
So let’s discuss the role of emotions in our financial decision making. Every one of us sees the situation differently and acts in own ways. Most of the time we are not rational. This is a fact. We behave irrationally more often than rationally. We most of the time do the cost benefit analysis of a decision in our mind in a rough and haphazard manner. While doing the cost benefit analysis our emotions creep into our decision making unconsciously. Most of the time we taint our facts and figures with emotional baggage.
This irrationality arises due to two main sources which are Biases and Heuristics. Biases are further divided into Emotional and Cognitive. Bias is a systematic error we make when analyzing the situation. Bias is always consistent in one direction as compared to a random error which is not consistent and can be positive and negative both. A random error in the long run cancels out as the positive and negative errors cancel each other.
A Bias is consistent in one direction. We may always underestimate a situation. In this case the bias error will be always negative. We may as well overestimate a situation in which case the bias error will always be positive. Sometimes this bias is a result of our cognition. Sometimes this bias will be the result of our emotions. Be warned US Dollar can change course suddenly.
Heuristics is another name for the rule of thumb that we often develop when dealing with complex situations. Heuristics can be wrong as they are based on trial and error and guesswork. Emotions like fear and greed also creep into our decision making. Suppose you are given two boxes containing US Dollars. One box has got $100 and the other box has got $50. You are allowed to open a box and look into it. Once you have looked into a box, you can also open the second box and look into it. But you cannot go to the first box.
You are not told the amount of dollars in each box. You are just told that one box contains double dollars as compared to the other box. So when you open a box and find $100. You can reason, if I look into the other box it might has $200. So in greed you open the other box and find only $50. So you lose $50 due to your greed. In the same manner, you open the box and find $50. You hesitate to open the other box and take $50 thus losing $50 due to your fear of losing.
These emotions of fear and greed wrack havoc with traders on the daily basis when they make their trading decisions. We cannot be rational. We have the famous ass problem. There is an ass very thirsty in a yard. Five feet to his left is a bucket full of water and five feet to the right is a bucket full of water. So the donkey is facing an identical thing on his left as well as right. If the donkey is rational, it will stand still and die of thirst because rationality means both buckets have same amount of water and it cannot choose which bucket to drink water from. On the other hand if the donkey is irrational, it will just move to a bucket and start drinking water and quench its thirst. So most of the time we are compelled to act irrationality and invoke our emotions just to make a decision.
When you have little sleep, you should avoid trading. Studies have shown that lack of sleep makes you take risky decisions on the expectation of making high profits and disregard the losses that you can incur if your decision goes wrong. Studies have shown that most of the time there is a dynamic interaction between our rational side and the emotional side in decision making. Best traders are those who learn the ability to emotionally detach themselves from the daily profit and losses and see the whole game of trading on a statistical long term basis.
Financial markets today are highly complex. There are many hidden factors that affect the price action and we cannot exactly figure out what is happening in the market meaning all the time we are dealing with imperfect knowledge rather than perfect knowledge. This brings us to the topic of complexity and how we deal with financial market complexity. Once again we will use the models developed by Behavior Finance that try to explain how we cope with complex situations around us.
When we are faced with complexity in our life, we try to use simplification. This simplification process can use heuristics, stereotypes and conjunction. We try to filter out the noise in the complex situation and focus on what is important. We tend to develop rules of thumbs which help us simplify things. We also classify things into categories. We also try to create stereotypes. This process is known as representativeness and this representativeness can create problems in financial decision making as we will see below.
We are constantly receiving data. We filter that data and try to separate the noise which we consider to be irrelevant. When we remove noise from the data we get the signal which is information that we are seeking. So whatever data we receive we filter out the important from the unimportant. So filtering helps us separate the important from the unimportant but in the process of filtering we can ignore important facts and classify is as noise. This happens often in financial decision making.
If you are an investor or a trader, you will find a lot of financial data online. There are financial websites, financial videos, financial TV channels and there are so many gurus and experts pedaling their advice on financial products and instruments. Then there is news from the corporations, central banks, governments, stock exchanges and so on. So we are being inundated with continuous financial news. All this financial information is being pedaled with a particular viewpoint. As an investor you need to filter all the financial information and avoid overload.
One method to understand complexity is to look at what has changed. Now let’s discuss how withdrawal works in financial decision making. The most common form of withdrawal is rejection. When you face losses, an investor can simply refuse to accept the reality. We buy a security and when bad news is released, we simply refuse to accept it. When the security price starts going down, we rationalize it by saying the loss is small and the stock price will turn and start going up again. The losses continue to grow bigger but we keep on telling stock price will turn and we will be again profitable. When the losses become too big, we simply upgrade the investment as a long term investment hoping that in the long run the stock price will turn and the losses will disappear.
As you have seen, rejection of real situation involves lot of wishful thinking. Wishing thinking is the result of our emotional attachment with a particular scenario. There is another thing more dangerous than rejection. This is Confirmation Bias. Confirmation bias simply means we give more importance to information that confirms our beliefs and we don’t give that much importance to information that negates our beliefs. As said above when we try to understand complexity, we use filtration and filter information that we think is important. Confirmation bias also creeps in unconsciously and most of the time we don’t even know we are facing it.
So the evidence which does support the scenario that we expect is either ignored or tested against some higher standard. We need to take the evidence seriously and evaluate it objectively. As an investor, you need to see the good with the bad. Now you can understand how dealing with complexity is not easy and often entails making irrational decisions based on our biases which we often don’t recognize. Learn how big brokers went bankrupt.
We have discussed how emotions and heuristics can cloud our decision making. We need to now consider cognitive bias. Cognitive bias is basically a misinterpretation of reality what we should call misperception. Misperception means we are seeing reality not as it is but what our mind imagines it to be. Hindsight is a perfect example of cognitive bias. You can now say I always knew Google will be a great investment. Android will be a success. Hindsight bias only works afterwards. But at the moment there is a lot of uncertainty and it is difficult to get a clear picture of what is going to happen. Humans has this problem. Humans view reality as what they want to see and not as what it actually is.
There is another thing very common amongst investors known as Representativeness Bias. There are thousands of stocks listed on the stock exchanges and it becomes very complex to analyze them. So investors often classify stocks as growth stocks, value stocks or income stocks. Now this classification scheme tends to masks the dissimilarities in the different stocks that belong to the same category. So if A and B are two growth stocks, analysts will ignore that fact that these two stocks maybe susceptible to different influences. Company A may be a solar panel company while company B may be a defense contractor.
Then we have the Gambler’s Fallacy. If we toss a fair coin say 100K times, the ratio of heads to tails will be close to 0.5. But if I toss the coin only for 10 times, I am sure. It can be 10 heads in a row or 8 heads in a row or 8 tails in a row. You never know. Why? Law of Large Numbers on which we calculate the probability of events is not valid for small numbers. In Gambler’s Fallacy we assume that the law of large numbers hold when it does not especially if we have small number of trials. Do high frequency traders need a speed limit.
Mean Reversion is a popular trading strategy. The stock price is supposed to reverse towards the mean after it shoots in one direction. Suppose a company announces a ground breaking drug that can cure cancer. Its stock shoots up. We would expect the stock price to fall after it has risen for sometime. But in reality the stock price can continue to rise for months and months. Gambler’s Fallacy is an example of Representativeness Bias. In the long run, the law of large numbers hold. So in the short run you can win the jackpot but in the long run when you have played a large number of times, the house will always have an edge. At times we do the opposite. We observe a small sample and assume that it represents the whole population. In actual reality, we need a sufficiently large sample to make valid statistical inference about the population.
In the financial services industry, heavy advertisers often get more clients. Mutual fund industry believes in advertising in the financial media. So when a high net worth individual goes to a financial advisor for investment advice. Guess what the investment advisor does. He goes to the heavily advertised mutual fund because it is fresh in his mind. Now a heavily advertised mutual fund may not be the best in the industry. Plus it has to pay the heavy advertisement costs which are obviously deducted from the clients. Now when the investment advisor suggests the mutual fund, the client most probably has already heard about it and willingly accepts the proposal.
Investment is all anticipation and sentiment. Our anticipation about the future is dependent on our sentiment today. Prices are always fickle and can turn on slightest provocation. Today we have electronic markets. Unlike the past, now investors don’t have to meet physically to place buy/sell orders. All orders are placed and executed electronically. You can invest and trade from the safety of your home. But we are still a market crowd and behave like a crowd even though we don’t meet physically now. But we are meeting all the time online on the trading forums, trading blogs, trading platforms and financial news channels. All the time we are expressing our opinion about the market with our buy/sell decisions by clicking the buy/sell buttons.
Modern financial markets are much more than a human crowd. Modern financial markets are now intricately linked with the human society, its fashion, culture and other things which makes it heterogeneous and not homogeneous. There are many players in the market that make is heterogeneous. Long term investors don’t bother about intraday volatility and usually look for price movements that can take months to materialize. On the other hand, day traders are concerned with intraday volatility and don’t bother at all what will happen months ahead.
Modern financial markets are driven by breaking news. A sudden breaking news like a catastrophic earthquake can send the market downward in seconds if the damage has been widespread. Breaking news impacts the different players of the market differently. The impact depends on what the market player is expecting. A long term investor will ignore short term news and only care about long term news. On the other hand, a short term trader will care about the short term fluctuations in the price of a stock due to a short term supply side problem the company faced. Once this short term supply problem has been resolved the company stock will rebound and the retracement will be over. A day trader cares about the retracement.
What this means is that the financial market reacts to the news in a measured manner. The impact of the news is felt over time. This is due to the fact that the day trader will react immediately and take remedial action. Trading and investing is all about anticipation. Modern financial markets are part of our society. What makes a few individuals a crowd is emotional contagion. An individual in a crowd feels the emotions as the rest of the crowd. Emotional contagion is what converts a bunch of individuals into a crowd. As a crowd they feel and share the same fear, greed and anger.
Emotional Contagion In Crowds and Group Culture
Emotional contagion is one of the primary reasons why we see strong price trends in the market. Groups have their own culture, rituals, symbols and ways of doing things. When an outsider joins a new group, he has to adjust and adopt to the new group culture. Successful companies develop strong group culture. New people who join these successful companies are required to adopt the company culture as early as possible without many questions or quit.
The main benefit of group culture is that it provides coherence to the group and makes team work possible as all the members share almost same values. Financial companies also tend to evolve strong group culture. Every one working in the financial company is supposed to adhere and adopt the company group culture. Crowds can lump together highly dissimilar things into something magical. Emotions that grip the crowds in the financial markets can result in the familiar ascending and descending triangle patterns as well as broadening formations.
Most of the time the stock price is consolidating. We call this consolidation ranging. Ranging is when the stock price goes up and down in a narrow range. As time passes, the price range gets narrower and narrower and it appears that a sort of triangle pattern has been formed. Studies have shown that crowds are much better at decision making as compared to individual investors. So it is highly possible that a crowd defeats individuals in solving certain problems. As said above sentiment plays a pivotal role in determining prices in the stock market.
Sometimes a snow ball effect like of thing happens in the financial markets. We call it Market Avalanche. In the last few years, we saw a tremendous commodities boom. Developing countries with huge population needed to develop their economies which required import of commodities to feed their populations as well grow the economy. This caused the commodity price to rise. When investors saw this they also invested in the commodities expecting a further rise. So it became like a market avalanche and prices increased more. In this case a positive feedback loop was created that fueled commodity prices to rise. In other cases a negative feedback loop can also get created which can spiral the prices to collapse. This phenomenon is also known as Information Cascade.
When an information cascade forms a positive or negative feedback loop there is no other option than to follow the crowd. A bullish or bearish sentiment is formed in the market and individuals have no choice but to follow the market sentiment. There are many times when these market sparks suddenly develop and then suddenly die down after a short time later. Investors develop scenarios and they constantly need confirmation of their scenarios. Most of the time the market is consolidating or ranging as said above because it is receiving contradictory short lived information sparks.
At time a powerful information spark arrives and the market starts moving in one direction. It can also happen many information sparks arrive in a short period of time all pointing in the same direction. Information cascades are purely the result of market crowd behavior and can result in overshooting and extremes which are often exploited by investors to find a good entry into the market.
George Soros and his Reflexivity
George Soros the famous investor who broke the Bank of England and made a cool $1 Billion profit in 24 hours has developed his own analytical framework to under the market behavior. He calls it Reflexivity. He uses his Reflexivity framework to understand market structure and secondly he also uses it to understand market disequilibrium that results when a feedback loop is formed that disrupts the market perception developed by the participants.
Reflexive processes that have had big impact on the financial markets initially started off as self reinforcing process but later on turned into a self defeating pattern. This is typically what happens in a boom/bust cycle in the financial markets. According to Soros, there are primarily three underlying processes that are working behind a reflexive system. The first is the underlying trend in the market which is causing the price to either go up or down. There is also a bias with which the market players view the market. Then there is a two way feedback loop working through the market prices that is influencing both the underlying trend and the bias.
This is what is happening in a Reflexive system. A process is set in motion that starts from market equilibrium to disequilibrium and boom to bust. This is how the whole process works. In the beginning a new trend is not recognized but after sometime it gets recognized which reinforces the trend and makes it more strong. In the start both the trend and the bias support each other. In the beginning the bias reinforces the trend and becomes somewhat exaggerated. But soon this exaggerated bias makes the market divorced from its underlying fundamentals.
But a time comes when the market has drifted too far away from its fundamentals and the market players can see it clearly. This creates self doubt in their beliefs. This creates a cross over point where the trend reverses and a new trend starts. Soros has used his Reflexive Theory to explain the boom/bust cycles of the past. Reflexive Theory is based on the fact that our actions are influencing our observations. So it is very difficult to know what is the actual reality. So at any given point of time our knowledge of market reality maybe defective. Soros Reflexivity Theory is a good example of how the market prices are intimately bound with the market participants emotions and thoughts.
Participants in a financial market can be considered as a crowd that is connected electronically. Markets just like crowds are often susceptible to herding, emotional contagion and mirroring which spreads the sentiment in the market and eventually is responsible for causing trends in the market. It has also been proven through research that gender also influences investment decisions. Male and females take different investment decisions. We need to consider the role of gender in influencing the financial markets.
Investment is basically a bridge that connects our present with our future. We form expectations about investments in future. Now this expectation of our future is colored by our sentiment. Our sentiment depends on how we are feeling about ourselves and how we are feeling about the world around us and how we are seeing the future.
Role of Hormones in Risk Taking
Hormones have an important role in risk taking. Investment decisions are all about risk taking. Testosterone is an important hormone that is produced in both men and women. Men produce testosterone 50 times more than women and have more of it. Still women are sensitive to this hormone. Research has shown that high testosterone levels are associated with higher profitability in traders. It has been observed that traders who take more risk have higher testosterone levels.
Another hormone is Cortisol. Cortisol is also known as stress hormone as it is involved in our reaction to stress and its effect on high blood pressure and sugar levels. Cortisol is the exact opposite of testosterone. Cortisol is associated with risk aversion and falling market prices. Research has shown that cortisol is mostly induced during choppy and uncertain market. Testosterone is associated with causing market bubbles and cortisol is associated with market crashes.
Role of Gender Difference in Investment Decision Making
Both men and women tend to be overconfident. When it comes to financial matters, men tend to believe that they are more competent as compared to women. Both men and women believe that their selected portfolio will outperform the market. Men believe their selected portfolio will outperform the market by a wider margin as compared to women. It has been found through study that men tend to be adventurous in investing while women tend to be cautious. Of course emotions play a pivotal role in decision making. Men tend to overestimate their investing skills and also tend to overtrade.
As an investor this is what we want to do. We want to make the highest return possible by risking the least amount possible. Investment involves exchanging one opportunity for another. There is a Money Time Probability (MTP) Framework that is often used to understand the investment decision making. We commit money by forgoing using it now to recoup it later at a future time with a high probability of profit.