Introduction
So what does influence our behaviour when it comes to participating in money markets? From common behavioural biases like the gambler’s fallacy, FOMO, and herd mentality, we dive deep into the various influences behind the psychology of behavioural finance, exploring why money market participants make bad choices — and how to avoid doing the same.
Key Takeaways:
- In the efficient market hypothesis (EMH), which implies that conducting market analysis in the hopes of uncovering mispriced assets would be futile, there are three forms: weak form, semi-strong form, and strong form.
- Momentum is a key market anomaly that refers to uptrends and downtrends in price movements; momentum trading is a strategy that involves buying recent winners and selling recent losers.
- The three stages in the life cycle of a price trend are underreaction, overreaction, and fundamental value. An illustrative example is the boom and bust of Bitcoin in 2017–2018.
- Behavioural biases include disposition effect, herding, FOMO, anchoring, and gambler’s fallacy, to name a few.
The Base of It All: Efficient Market Hypothesis (EMH)
As Nobel laureate Eugene Fama proposed, a market is efficient if market prices reflect all relevant information about the underlying assets. In such a case, the market price is always identical to the fundamental value. If news releases impact the fundamentals, prices should adjust immediately to take the new information into account.
The efficient market hypothesis (EMH) can be classified into three forms:
1. Weak form: Past prices do not contain any information about future prices.
The weak form implies that any efforts conducting technical analysis on predicting price movement would be in vain.
2. Semi-strong form: Prices accurately summarise all publicly known information.
This implies that it is impossible to take profits from studying any publicly available industry news or market analysis about cryptocurrency since the tokens’ prices reflect all the publicly known information.
3. Strong form: Prices reflect all insider information and publicly known information.
The strong form indicates that even so-called ‘insider’ information is already incorporated in the prices. If financial markets are as perfectly efficient as described by EMH, then it implies that conducting market analysis in the hopes of uncovering mispriced assets would be futile.
However, the reality is far more complex than this hypothesis.
Things Are Always Changing: The Importance of Momentum and Value
A key market anomaly refuting EMH is the momentum observed in market prices. Momentum refers to uptrends and downtrends in price movements: rising prices keep rising, whereas falling prices keep falling.
This proposition rejects the weak-form EMH, as it supports the idea of a correlation between future prices and current prices. Momentum trading is a strategy based on this anomaly and involves buying recent winners and selling recent losers. Numerous studies have confirmed the persistence of momentum in diverse markets and asset classes. Research also shows that the current returns of Bitcoin can predict its returns days and weeks ahead.
How can we explain the existence of momentum in market prices? Economists have tried to explain momentum with ‘underreaction’ and ‘overreaction’ in the markets.
There are typically three stages in the life cycle of a price trend. Here we assume there are two groups of market participants: news watchers, who only react to the news; and momentum traders, whose trades are based only on past price changes.
Stage 1: When a piece of good news gradually spreads in a group of news watchers, they start buying in on the good news. The asset now has a higher fundamental value due to the positive developments. News watchers are value investors trying to profit from the difference between the new fundamental value and the current trading price. Initially, the price remains stable due to underreaction by market participants, but it slowly rises to reflect the latest information. Such underreaction can be caused by human beings’ behavioural biases.
Stage 2: Traders notice the slow uptrend and buy on it, pushing up the momentum. As more traders join the party (e.g., perhaps due to herd mentality), the price overshoots above the asset’s fundamental value, leading to a delayed overreaction.
Stage 3: When the market fully understands the news, the uptrend reverses, and the price finally converges to the fundamental value.
If the momentum is strong, a speculative bubble may form, and prices could plunge afterwards. The boom and bust of Bitcoin in 2017–2018 is an illustrative example. As the future potential of cryptocurrency and blockchain became better understood by the public, the Bitcoin price rose to reflect the fundamentals (stage 1). Then more traders bought Bitcoin and pushed up the momentum (stage 2). Bitcoin’s price overshot its fundamental value, and the market began to learn more about the risks and limitations regarding the asset. Fear, uncertainty, and doubt (known as FUD) spread in the market. Its price finally crashed (stage 3).
Behavioural Biases: The Disposition Effect and Prospect Theory
Since the market is not perfectly efficient, some trading strategies could be profitable. These strategies, however, are not easy to execute. The paradox here is that human beings’ irrationality partly creates room for such profits, as we generally believe we can make rational decisions, especially in playing the market. Still, findings in behavioural finance have shown that we are probably overconfident and susceptible to various biases.
An interesting phenomenon is that traders tend to sell their wins too soon and hold their losses too long. This is called the disposition effect, which explains why prices initially tend to underreact before the start of price momentum.
Prospect theory provides a framework illustrating the psychology behind the disposition effect. The gist of the prospect theory is that individuals are generally risk-averse when facing potential gains and risk-loving when facing potential losses — and more sensitive to the pain from losing than the happiness of winning.
For example, suppose there was a choice between 1) a 100% chance of winning $500, or 2) a 50% chance of winning $1,000 and a 50% chance of winning $0. Most people are likely to take the first choice, even though the expected value of the two choices is exactly the same. In another example, the choice is now between 1) a 100% chance of losing $500, or 2) a 50% chance of losing $1,000 and a 50% chance of losing $0. Many would likely choose the second option.
Some traders prefer to ‘HODL’ (buy and hold) crypto, staying away from short-term price fluctuations while believing in the crypto’s long-term growth in fundamentals. They may still HODL in the case of plunging prices since they think that irrational market sentiment drives the price far below its fundamental value. However, as illustrated by prospect theory, they just may be reluctant to realise the loss.
Mind the Trap: More Behavioural Biases
Besides the disposition effect, people have many other behavioural biases that can impact their market decisions.
1. Herding Behaviour and Fear of Missing Out (FOMO)
Many people jump on board when an asset price is on a strong uptrend, and the hysteria pushes the price higher and higher. This ‘herding behaviour’ is related to ‘fear of missing out’ (FOMO), where traders fear they miss the profitable chances and are thus eager to buy on the trend. Such a mentality is not only found in retail and amateur traders, however. Institutional players like mutual funds have also shown herding behaviour, as they are afraid their portfolio performances may fall short of market returns.
2. Confirmatory Bias
People generally have a particular belief first. Then they tend to search for information supporting their idea, which explains why sometimes they may see recent price movements as indicators of future price movements. Traders then buy more of the assets that have recently made money and sell those with a downtrend in price movement. Such behaviour can be self-fulfilling and a contributing factor in building up the price momentum.
3. Anchoring Effect
Anchoring is a perception bias with the theory that people may stick to historical information and adjust their views insufficiently to new information. Anchoring is an alternative explanation for the initial underreaction in the momentum anomaly.
4. Gambler’s Fallacy and Hot-Hand Fallacy
Gambler’s fallacy refers to the belief that the persistence of one signal in previous draws increases the chance of having another signal in the next draw. A simple example is flipping a coin and having ten tails in a row, and thinking heads will land on the next flip. Or, if the price of Bitcoin has kept rising for ten consecutive days, one may expect the price will retreat the next day.
In contrast, the hot-hand fallacy is the belief that a sequence will exhibit excessive persistence rather than reversals. For example, suppose a crypto commentator makes a streak of correct predictions on market movements for weeks. In that case, people may think this is an above-average commentator who will continue to make correct predictions.
The two above phenomena seem contradictory, but they are connected to the same statistical misconception: People tend to assume that what they observe in a small sample should be identical to the whole population from which the sample is drawn.
The reality is that people underestimate the likelihood of streaks in a small sample. In the commentator’s case, they infer from the small sample and conclude that the winning streak is strong proof of the commentator’s ability to outperform the market in the long run.
Conclusion
Understanding behavioural biases is key to smart market decisions, especially in the crypto world, where emotion and hype can play a big role in many people’s decisions. These concepts can serve as reminders for us to stay vigilant of the market’s sentiment and our own biases when making decisions.
Due Diligence and Do Your Own Research
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