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What Is Behavioural Finance Theory?

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At the end of the day, people are the driving force of economic markets.

 

This can be either directly through individual traders, investment groups and proprietary firms, or the ultimate human hands behind the methodologies and algorithms that assist the myriad of trading technologies seen throughout the market.

 

This is also why prop firms will evaluate new traders and find ones that not only make successful investments but do so using an appreciation for risk and a strong overall market knowledge.

 

None of this is new, of course, and even early classical economists such as Adam Smith would explore the connection between psychology and economics, long before the term behavioural finance was even coined.

 

To understand the market and how it has changed over the years, it is important to look at behavioural economic theory, its core fundamental aspects and why for over 60 years it proved to be incredibly controversial amongst economists before being embraced once again.

 

Behavioural Finance Vs The Economic Man

 

Behavioural finance theory is perhaps best explained in contrast to more empirical and utilitarian theories that dominated economic discourse from the dawn of the 20th century until around the 1990s, often grouped under the name Homo Economicus (Economic Man).

 

The economic man theory, first suggested by utilitarian philosopher John Stuart Mill, is a hypothetical person who makes decisions based on a perfectly rational perspective and a narrow sense of self-interest, seeking maximum utility for each purchase as a buyer and maximum profit as a seller.

 

In the stock market, an economic man is someone who makes decisions based on an entirely consistent rationality and an interest only in maximising their own investment, which for traders is almost always maximising ultimate profit.

 

Whilst it can be helpful in the construction of mathematically-focused economic models, it does not accurately reflect investment behaviour or the market itself. Investors do not always make decisions based on rational criteria and either through bad data or bad interpretation can make irrational decisions.

 

Even taking into account that someone can make entirely rational decisions and still lose a trade, there are almost no investors that are truly rational actors, and everyone on the market floor has their own biases and limits, both of which can lead to errors.

 

Behavioural finance theory takes this into account, and works under the assumption that every trader is not an “economic man” but instead may have a set of cognitive biases, gaps in their knowledge or be influenced by a range of sociological and psychological factors.

 

Whilst the psychology of finance and economics had been explored before this, the big turning point for the field was the Nobel Prize-winning work of Daniel Kahneman and the late Amos Tversky in what they described as “prospect theory”, an evolution of Adam Smith’s loss aversion theories, in 1979.

 

Ultimately, behavioural finance theory is the idea that everyone who participates in financial markets is human and subject to the same foibles, flaws, bad days, brain fog, biases and fallacies as everyone else.

 

Assuming that people are perfectly rational and entirely selfish is why so many traditional models of economics fall apart when applied in practice.

 

Instead, it can be far more beneficial for both analysts and traders to explore not necessarily the rationale behind market movements but the biases, fallacies and irrational heuristics that could cause the market to move in unexpected ways.

 

Core Concepts Of Behavioural Finance

 

Because behavioural finance explores how psychology affects trading decisions and whether these decisions can be made better, there are a lot of different concepts to explore in behavioural finance, and likely far too many to be able to cover in depth.

 

They can, however, be separated into two distinct groups of concepts, which themselves can be separate and sorted as well:

 

Heuristics – These are the mental shortcuts we use to make decisions when we do not have the time to gather and review our options. These can themselves be divided into heuristics focused on searching for information, and other mental effects.

Biases and Fallacies – A bias is a weighting towards a particular decision, whilst a fallacy is a fault in our decision-making that ostensibly appears plausible.

 

What Are Search Heuristics?

 

Search heuristics are the shortcuts we use when gathering information that leads us to make a decision, often a necessity as carefully weighing up each option is often an impossibly slow option, especially when trading in a volatile market.

 

There are many different types of search heuristics, and a combination will apply to nearly any decision, but there are three in particular that affect financial decisions the most.

 

The first is elimination by aspects, often simply known as the “process of elimination”. This is a decision-making technique where a group of options are compared based on a quality about them that matters the most, with those that do not meet the requirements progressively eliminated.

 

After the first search eliminates options, the search is refined according to the next most valued quality until a clear winner emerges. This can be seen when comparing investments with enough similarities, such as an angel investor looking at startups to invest in.

 

Another common heuristic is “satisficing”, which is the opposite of elimination, where the first option that meets a minimum threshold is chosen because it is “good enough” at the expense of finding the best answer.

 

Other Cognitive Effects And Mental Shortcuts

 

There are a lot of different mental shortcuts that affect decision-making, especially in the unique world of financial markets, although some of these are often discussed in other contexts as well, particularly the first concept in this section.

 

Herd behaviour, or herd mentality, is the idea that people make decisions based on what everyone else is doing and follow the consensus. This is often a reason why a stock can rise and fall so quickly, as when a few people buy in or cash out, the rest will tend to do the same.

 

Another common mental shortcut is anchoring, which is how success and failure are often perceived as relative to a set mental reference point, which on the stock market tends to be whatever price it was bought for.

 

This often leads to traders often being reluctant to realise a small loss in a difficult market decision despite that being the rational decision, or conversely selling too early in a surging market.

 

As well as this, there is the concept of linguistic framing, which is the tendency for decisions to be made not necessarily based on the merit of the choices but instead on how they are presented to the trader.

 

Finally, in portfolio management, there is the concept of mental accounting, where money is automatically sorted into different pots based on what the money is for or where it came from.

This is why in some cases unexpected trading gains are reinvested more recklessly, a concept often referred to as “playing with house money”.

 

Biases And Fallacies

 

The most common topic discussed when it comes to behavioural finance is the logical fallacies and cognitive biases that lead to irrational trading decisions and aberrations in the market compared to models that assume rational actors and equal access to information that could affect the market.

 

The most well-known of these, as well as the first one to bring behavioural finance theory to the attention of a wider group of economists, is loss aversion, which is the fallacy that a loss will affect a trader far more than an equivalent gain.

 

That intensely negative feeling will cause traders to opt for strategies that avoid losses rather than maximise their overall profits by avoiding trades that would otherwise have an acceptable level of risk.

 

However, it is far from the only cognitive bias out there. Several biases are widely cited and discussed outside of the financial markets but have particular resonance for traders, including:

 

Confirmation Bias – a cognitive bias where we place greater weight on any information we already agree with compared to information that stands opposed to this.

Recency Bias – when we place more weight on recent events or information than historic ones. In market terms, this is the assumption that a bull market will keep going up and a bear market will keep falling.

Familiarity Bias – when people stick close to what they know rather than researching new markets and solutions.

Status Quo Bias – where people opt for choices that keeps their situation as close to the way it is as possible instead of seeking more radical changes.

Present Bias – where people prefer to take a small gain now rather than a higher payoff later.

 

There are also several fallacies based on how people handle incomplete or difficult-to-process information:

 

Narrative Fallacy – This is where people tell themselves or other investors stories to connect random events and information. This is often part of a black swan event or a surprising major financial event rationalised after the fact.

The Gambler’s Fallacy – The idea that an event that has happened recently is less likely to happen again, even in cases where that should not affect the odds. This is often why an investor dealing with a string of losses will keep going assuming the next win is around the corner.

The Hot Hand Fallacy – The opposite of the gambler’s fallacy, this is the belief that a string of successful trades should be continued, even if the most rational option is to trade more conservatively or study the market’s trajectory.

FTUK Funded Account Disclaimer

CFTC Rule 4.41 – Hypothetical or Simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, because the trades have not actually been executed, the results may have under-or-over compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs, in general, are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown.

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