Loss aversion is a psychological phenomenon that refers to the tendency of individuals to strongly prefer avoiding losses rather than acquiring gains of equal or even greater value. In other words, people tend to feel the pain of losses more intensely than the pleasure of equivalent gains. This bias can have a significant impact on decision-making, particularly in the fields of economics and finance.

Loss aversion was popularized by psychologists Daniel Kahneman and Amos Tversky as part of their Prospect Theory, which explains how people make decisions involving risk and uncertainty. The concept can be illustrated by the following example:

Imagine you have the choice between two scenarios:

• Scenario A: You receive $100.
• Scenario B: You have a 50% chance of receiving $200 and a 50% chance of receiving nothing.

From a rational perspective, both scenarios have an expected value of $100. However, due to loss aversion, many people tend to prefer Scenario A because they dislike the possibility of receiving nothing in Scenario B, even though the potential gain is higher.

How Can Loss Aversion Affect Our Financial Decisions?

This bias can lead to several behavioral tendencies and impact decision-making:

• Risk aversion: Loss aversion contributes to risk aversion, meaning that people are willing to accept lower potential gains to avoid losses. This can influence investment decisions, as individuals may choose safer, less profitable investments to avoid losing money.
• Sunk cost fallacy: Loss aversion can lead people to stick with decisions they have made. Even when these decisions are no longer rational, because they have already invested time, money, or effort. This is known as the sunk cost fallacy.
• Holding losing stocks: Investors may hold onto losing stocks longer than they should, hoping to avoid realizing a loss. This can cause them to miss opportunities to reinvest in more promising options.
• Negotiations: In negotiations, loss aversion can make individuals more reluctant to make concessions for fear of giving up something they already have.
• Consumer behavior: Loss aversion can affect purchasing decisions, as people may hesitate to buy if they perceive a risk of losing money on a product or service that doesn’t meet their expectations.

How to Limit the Impact of Loss Aversion on Financial Decisions?

To counter the effects of loss aversion, it is important to:

• Recognize the bias: Being aware of your tendency toward loss aversion can help you make more rational decisions by objectively considering potential gains and losses.
• Assess risks realistically: Evaluate potential risks and losses more objectively by taking into account both the potential outcomes and their probabilities.
• Diversify investments: Diversifying your investment portfolio can help mitigate the impact of potential losses from a single asset.
• Focus on long-term goals: Consider the long-term perspective and overall objectives when making decisions, rather than focusing solely on short-term gains or losses.

By understanding how loss aversion works and actively seeking to counter its effects, you can make more balanced and informed decisions in various aspects of your life, including financial choices.

L’article How Does Loss Aversion Affect Our Financial Decisions? est apparu en premier sur Neuroprofiler.

Loss aversion is a psychological phenomenon that refers to the tendency of people to strongly prefer avoiding losses over acquiring gains of equal or even greater value. In other words, individuals tend to feel the pain of losses more intensely than the pleasure of equivalent gains. This bias can have a significant impact on decision-making, particularly in the realm of economics and finance.

Loss aversion was first identified by Tversky and Kahneman in their paper: “Prospect theory: An Analysis of decision under risk”, published in 1979.

This theory aims to explain how people make decisions involving risk and uncertainty, often deviating from the predictions of traditional economic theory, which assumes that individuals are entirely rational and always seek to maximize their expected utility.
On the contrary, Prospect Theory is based on the assumption that our decisions are influenced by emotions, context, cognitive biases, and social norms..
More specifically, Prospect theory introduces the concept of value functions and decision weights to model how people perceive and evaluate potential outcomes in uncertain situations. The theory is built around four main components:

1. Value Function: The value function describes how individuals perceive gains and losses relative to a reference point. It suggests that people evaluate outcomes in terms of changes from a reference point (often the status quo) rather than in absolute terms.
2. Gains: People are risk-averse when considering gains. As the value of gains increases, the perceived satisfaction or utility gained from those gains diminishes at a decreasing rate. In other words, the psychological impact of gaining $100 is less than the impact of gaining an additional $100 when you already have $200.
3. Losses: People are loss-averse when considering losses. The pain or disutility experienced from losses increases at a steeper rate as the losses become larger. The emotional impact of losing $100 is greater than the impact of losing an additional $100 when you’ve already lost $200.
4. Decision Weights: Prospect theory also introduces the concept of decision weights, which represent how individuals perceive probabilities. People tend to overweight small probabilities and underweight large probabilities, especially when it comes to losses. This contributes to the phenomenon of probability distortion.

Graphical representation of loss aversion

The graph represents the value function of the Prospect Theory, where we can visually understand the notion of loss aversion.

The vertical axis represents the subjective value/ utility that an economic agent perceives, depending on the different outcomes. The horizontal axis represents the outcomes, and whether they are gains or losses. The utility function depicted on the graph is generally concave for gains and convex for losses, which corresponds to the definition of loss aversion.
In other words, the economic agent is more sensitive to losses than to gains. Another property recognizable on the graph is that as the gains increase, the subjective value of the gains does not increase proportionally. Thus, the larger the gain, the smaller is the increase in subjective value.
The opposite is true for losses, the subjective value for losses decreases faster than the actual outcome.

Behaviors induced by the Prospect Theory

Beyond loss aversion, the Prospect Theory can predict other behavioral tendencies that deviate from traditional rational economic behavior:
Risk Aversion for Gains, Risk Seeking for Losses: Individuals are generally risk-averse when facing potential gains but can become risk-seeking when facing potential losses. This contributes to behaviors like selling winning stocks too early and holding onto losing stocks too long.
Diminishing Sensitivity: People’s sensitivity to changes in outcomes diminishes as the magnitude of those outcomes increases.
Framing Effects: The way a decision is framed can significantly influence people’s choices. People often make different decisions based on how a problem is presented, even if the underlying options are identical.

References

Brown, A. L., Imai, T., Vieider, F., & Camerer, C. (2021). Meta-analysis of empirical estimates of loss-aversion. Available at SSRN 3772089.

Kahneman, D., & Tversky, A. (2013). Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I (pp. 99-127).

L’Haridon, O., Webb, C. S., & Zank, H. (2021). An Effective and Simple Tool for Measuring Loss Aversion (No. 2107). Economics, The University of Manchester.

L’article Loss aversion: back to the theory! est apparu en premier sur Neuroprofiler.

The halo effect is a cognitive bias that involves the tendency of people to judge an individual or a product positively or negatively in multiple areas based on their impression of that person or product in one specific area. In other words, a positive or negative quality in one aspect can influence how people perceive qualities in other unrelated aspects.

This bias was first identified by psychologist Edward Thorndike in 1920, who noticed that soldiers rated as having a positive characteristic were often rated as having other positive characteristics, regardless of whether they actually possessed these characteristics.

Subsequently, numerous other research studies have taken place, highlighting the halo effect in a wide variety of fields.

Today, this bias is very prevalent in society and can lead to inaccurate judgments and evaluations because we tend to focus on a specific personality trait.

The halo effect can also result in a lack of objectivity and critical thinking in decision-making. If we already have a positive impression of a person, we may be more inclined to overlook or excuse their flaws and focus only on the positive aspects. This can lead to poor decisions in areas such as hiring, promotions, and investments.

Similarly, the halo effect can lead to discrimination and prejudice because individuals can be judged based on their appearance, gender or any other arbitrary criterion rather than on their skills or accomplishments.

The halo effect can lead to a preference for people who fit a certain profile or standard. This can reduce diversity in organizations and society, reducing the entry of people who do not fit this profile.

Examples of the Halo Effect

• Physical Appearance and Personality: If someone is physically attractive, they might be perceived as having positive personality traits such as kindness, intelligence, or confidence, even if there’s no evidence to support these assumptions.
• Brand Reputation: If a company has a strong positive reputation in one product category, people might assume that all their products are of high quality, even if they haven’t experienced those products themselves.
• Celebrity Endorsements: If a celebrity endorses a product, people might assume that the product is of high quality, even if the celebrity’s expertise is unrelated to that product.
• Academic Achievement and Leadership: If someone excels academically, they might be assumed to have strong leadership skills or other positive traits, even if there’s no direct correlation.

Effects of the Halo Effect

• Biased Perception: The halo effect can lead to biased perceptions, causing people to overlook or downplay negative qualities in individuals or products that they perceive as generally positive.
• Misguided Judgments: People might make judgments or decisions based on incomplete or inaccurate information due to the influence of the halo effect.
• Inaccurate Hiring and Evaluation: Employers might hire or promote individuals based on positive qualities that are irrelevant to the job role, leading to poor job fit.
• Consumer Behavior: Consumers might make purchasing decisions based on the overall positive perception of a brand, without considering the specific attributes of the product they’re buying.

How to measure the halo effect ?

In order to measure the halo effect, scientists set up experimental studies that aim to replicate everyday situations and test various hypotheses and variables. In these studies, participants are placed in real-life conditions and are asked to give their opinions, evaluate subjects with different criteria and in different situations. For this, experts use several measurement tools.

First, evaluation questionnaires or surveys are set up, allowing for specific questions to be posed to individuals and presenting them with different propositions. In some studies, interviews or open discussions may be more appropriate as they allow candidates more freedom in their choice of responses.

Additionally, participants may be subjected to cognitive tests to assess their ability to make objective decisions. These tests can help identify whether participants tend to be influenced by the halo effect when evaluating subjects.
Subsequently, all responses and results are collected, and experts analyze the data to try to identify potential correlation links or emerging trends.

Finally, scientists reach a conclusion to highlight the halo effect or not, by observing whether the
responses and behaviors are consistent with reality or influenced by a judgment bias.

How to mitigate the halo effect ?

• Seek Objective Information: When making judgments, decisions, or evaluations, gather objective information about the specific qualities you’re evaluating, rather than relying solely on overall impressions.
• Separate Traits: Recognize that positive or negative qualities in one area don’t necessarily imply the presence of those qualities in other areas. Consider each trait or quality separately.
• Critical Thinking: Develop critical thinking skills to assess individuals and products based on relevant criteria rather than general impressions.
• Question Assumptions: Challenge your assumptions and question why you’re attributing certain qualities to an individual or product.

By being aware of the halo effect and actively working to evaluate individuals and products objectively and based on their specific merits, you can make more balanced and informed judgments and decisions.

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The well-known phenomenon of home bias in finance refers to the tendency of investors to prefer investments in domestic securities instead of enjoying the added value of diversification through investments in foreign securities.

Home bias is difficult to measure. This is due to the behavioral aspects that are problematic to quantify.

A research study on measuring home bias

Sercu and Vanpée (2007) tried to produce quantifiable results for home bias. In their research Home Bias in International Equity Portfolios: a Review (2007), Piet Sercu and Rosanne Vanpée of the Katholike Universiteit Leuven examine the existence and development of home bias at an international level.

In their research, Sercu and Vanpée also report on possible theories that could explain home bias, but this was already dealt with in the first chapter of this analysis.

Sercu and Vanpée use a very similar method to the majority of research on the subject. They compare each country’s market share with its holdings of domestic securities. The proportional shares of these factors are then used to calculate the degree of home bias as a home bias factor.

The data in the research is from the end of 2005, with portfolio holdings collected from the Coordinated Portfolio Investment Survey (CPIS) of the IMF and the respective countries’ market shares from the World Federation of Exchanges (Sercu & Vanpée 2007).

Through the research, Sercu and Vanpée highlight the existence of home bias in all countries that were included in the survey, in that all countries hold a strongly biased portfolio towards the home country.

The results

The home bias factor, which represents how home biased each country is towards domestic securities, is a scale from 0-100 where a higher value indicates greater home bias. Through the research, Sercu and Vanpée find that the largest home bias is in Indonesia with a home bias factor of 99.7%, while the Netherlands has the lowest level of home bias at 30.8%.

The results show a pattern where industrialized countries generally have a lower level of home bias compared to developing countries or emerging markets, where home bias is often very high.

This is strongly linked to a high level of home bias existing in the most unstable or risky markets, which also tend to be emerging markets.

Through these results, it can be concluded that domestic investors in emerging markets carry a lot of risk as they are heavily invested in the home country and that international investors are not willing to take on this risk, leading to a high level of home bias.

L’article How to measure the impact of home bias? est apparu en premier sur Neuroprofiler.

The framing effect is a cognitive bias that describes how people’s decisions and choices are influenced by the way information is presented or “framed”. This bias suggests that the way a message or option is framed can significantly impact how individuals perceive the information and subsequently make decisions, even if the underlying content remains the same.

The framing effect is often observed in situations where the same information is presented in different ways, leading to different responses.

Here’s an example to illustrate the framing effect:

Imagine a medical treatment with two options:

• Option A: There is a 70% chance of survival
• Option B: There is a 30% chance of death

Both options convey the same outcome: a 70% chance of success. However, people tend to view Option A more positively because the information is framed in terms of survival, even though the numerical value is the same. The framing of the information can influence individuals to choose the option that sounds more favorable or less risky.

Framing effect affects our daily decisions

The framing effect can be observed in various contexts, including marketing, politics, healthcare, and decision-making in general. It highlights the psychological impact of how information is presented and how people respond to different framing techniques.

Academic background of the framing effect

The theoretical foundations of framing effects can be traced back to research conducted by Amos Tversky and Daniel Kahneman in 1981. During their social experiment, they explored how different phrasing could affect participants’ responses to a choice in a hypothetical life and death situation.

Later on, in their seminal paper The framing of decisions and the psychology of choice, they introduced the concept of framing effects and demonstrated their impact on decision-making, using hypothetical scenarios and experiments. In 1998, Levin, Schneider and Gaeth proposed a typology of framing effects, identifying four different types of frames that can influence decision-making in their paper named All frames are not created equal: A typology and critical analysis of framing effects.

The different types of framing effect

• Positive vs. Negative Framing: As shown in the medical treatment example, positive framing emphasizes gains and benefits, while negative framing emphasizes losses and risks.
• Gain-Loss Framing: This type of framing focuses on what can be gained or lost by choosing a particular option. People tend to be more risk-averse when choices are framed in terms of gains and more risk-seeking when choices are framed in terms of losses.
• Attribute Framing: This involves emphasizing different attributes or qualities of an option to influence perception. For instance, highlighting the fat content of a food product can make it appear less healthy, even if the overall nutritional value is acceptable.
• Temporal Framing: This involves presenting information in terms of time, such as short-term gains versus long-term gains, which can influence decision-making based on time preferences.

How to mitigate the framing effect?

• Awareness: Being aware of the framing effect can help individuals make more objective decisions by consciously considering the underlying content rather than being swayed solely by how it’s presented.
• Critical Thinking: Practice critical thinking when making decisions. Analyze the information presented from different angles to understand the implications of each option.
• Consider Multiple Frames: When presented with a choice, try to reframe the information in different ways to gain a more comprehensive understanding of the decision’s implications.
• Focus on Core Content: Try to focus on the core content or information presented rather than getting caught up in the way it’s presented.

Recognizing and understanding the framing effect can enable individuals to make more informed and rational decisions by evaluating options based on their actual content rather than being overly influenced by the presentation style.

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What is anchoring bias?

The anchoring bias is a cognitive bias that refers to the tendency of individuals to rely too heavily on the first piece of information they receive when making decisions.

This initial piece of information is denominated “the anchor”. It often serves as a reference point or starting point for subsequent judgments or decisions. People adjust their judgments or decisions away from the anchor. However, they often don’t adjust far enough, leading to systematic errors.

Anchoring bias can be observed in various contexts, such as negotiations, pricing, or financial decisions. Here’s an example:

Imagine you’re at a car dealership looking to buy a new car. The salesperson starts by showing you a car with a high price tag, let’s say $60,000. This initial high price becomes an anchor in your mind. Even if the salesperson later presents a lower price, say $45,000, you might perceive it as a good deal because it’s lower than the initial anchor. However, without the anchor, you might not have considered a $45,000 car to be a good deal at all.

Anchoring bias can lead to irrational decision-making because people are often influenced by irrelevant information that should not influence their judgment.

Being aware of this bias is important in order to make more rational and objective decisions. It’s recommended to consciously question the relevance of the initial information. Thanks to that, you will consider a broader range of options when making decisions.

How can the anchoring bias affect our financial decisions ?

Anchoring bias can significantly impact our financial decisions by leading you to make suboptimal choices that are influenced by irrelevant or arbitrary information. Here’s how anchoring bias can affect various financial decisions:

1. Purchasing Decisions: When buying products or services, the initial price you encounter can serve as an anchor. That influences how much you’re willing to pay. For instance, if you see an item originally priced very high but then offered at a “discounted” price, you might perceive the discounted price as a good deal, even if it’s still higher than the item’s true value.
2. Investment Decisions: Investors can be prone to anchoring bias when valuing stocks or other assets. If you anchor on a recent high price for a stock, you might hesitate to sell it even if its current value has dropped significantly. You might also anchor on the price you paid for an asset. Which leads you to hold onto it even if it’s no longer a good investment.
3. Salary Negotiations: Anchoring bias can affect negotiations related to your salary or compensation. If your current or previous salary serves as an anchor, you might be hesitant to ask for a significantly higher salary, even if your skills and the market value suggest you deserve more.
4. Budgeting: Anchoring bias can affect how you allocate your budget. If you start with a certain spending level as an anchor, you might be less willing to reduce spending in certain categories even if it’s financially prudent to do so.
5. Real Estate Transactions: When buying or selling a property, the initial listing price can serve as an anchor that influences your perception of the property’s value. This can lead to overpaying for a property. If you anchor on the listed price without considering comparable properties or market trends, your decisions are biased.
6. Loan Decisions: Anchoring can also affect loan decisions. If you’re presented with a loan offer that has a high initial interest rate, you might be more likely to accept it without shopping around for better rates, even if you could secure a more favorable loan elsewhere.

How to mitigate the impact of the anchoring bias on our financial decisions?

To mitigate the impact of anchoring biases on your financial decisions:

• Research: Gather as much information as possible before making a decision. Consider multiple sources of information and various perspectives to avoid anchoring on a single piece of data.
• Set Clear Criteria: Establish clear criteria for your decisions in advance. This can help you evaluate options objectively rather than being swayed by the initial information.
• Seek Independent Advice: Consult with financial advisors or experts who can provide an unbiased perspective and help you make informed decisions.
• Take Your Time: Give yourself time to deliberate and consider alternatives before making a decision. Avoid making impulsive choices based solely on the first piece of information you receive.
• By being aware of the anchoring bias and actively working to counter its effects, you can make more rational and effective financial decisions that align with your goals and financial well-being.

L’article Anchoring biases and financial decisions est apparu en premier sur Neuroprofiler.

Decision-making, including in the financial sphere, is largely modulated by automatism and the unconscious. Neuroscience (and neurofinance) is essential for studying the stages of decision-making that affect the subject’s unconscious choice.

Factors linked to the presentation of visual information (color, location), rather than content, can be decisive in choice.

What is neurofinance?

As a relatively new discipline, neurofinance combines finance, neuroscience and psychology to advance theories and knowledge related to decision-making. The majority of neural processes that guide choices, including economic-financial ones, are automatic and unconscious by nature, and are therefore difficult to assess via self-evaluation.

Neuroscience offers research methods such as functional magnetic resonance imaging, electroencephalography, eye-tracking and facial expression recognition, which can shed light on the neural mechanisms of economic-financial decision-making. 

Decision-making and the limits of the human brain

Decision-making is a cognitive process that can be defined as “the ability to select an advantageous response from a set of available options”.

Whatever the domain involved (from the purchase of consumer goods to the response to an election, via the selection of financial products), human beings have to deal with cognitive resources, knowledge and, sometimes, limited time availability. Hence the need to “filter” information.  Indeed, our brains quickly navigate between those deemed most relevant to the final decision and those that are more detailed.

In general, the number of stimuli is so high that it is impossible to process each one systematically. The functional limitations of the human brain make it impossible to construct an effective behavioral response to every stimulus received. At the physiological level, therefore, the need arises to select the sensory stimuli to be taken into account in order to organize and stimulate behavioral responses that are congruent and effective.

In this sense, all stimuli continuously collected by the sensory system and transferred to the brain undergo selection before being processed. The mechanism that enables a stimulus to overcome this selection, to the detriment of others that are inhibited, is that of selective attention: a process that is mainly automatic and partly voluntary.

• In its automatic phase, it can be linked to the intrinsic characteristics of the stimuli derived from the observed sources. For example, shape, color, location or clutter.
• In the will phase, on the other hand, motivational aspects dominate. In other words, the individual’s objectives and expectations.

Decision-blocking in the financial sector

The financial sector offers a wide range of financial products and services, accompanied by information and documentation. As a result, investors are continually exposed to financial information and are often confronted with problems of information overload.

To increase transparency and promote consumer protection, financial authorities are introducing succinct disclosure documents that present the main features of products. This enables consumers to assess their quality.

These summaries are standardized throughout Europe, as consistency facilitates comparison, which can improve decision-making. Validation of information documents is generally carried out by combining qualitative interviews with quantitative surveys of consumers, who are asked to comment on the clarity of the information they receive.

Research in neuroeconomics suggests the possible limits of self-reported measures, and calls for the evaluation of decision-making by combining economics and finance with neuroscientific theories and methodologies. 

How can attention process be studied using neurofinance and decision-making approaches?

In recent years, a number of researchers have begun to study a specific stage in the decision-making process. Namely, the processing of visual information, using the non-invasive technique of eye-tracking.

Capturing the visual attention process with eye-tracking

The brain constantly receives stimuli from the environment, which are selected by automatic processes, then processed and interpreted. In the case of visual stimuli, the first motor reactions set in motion by the brain involve activation of the eye muscles: the gaze is thus fixed, “focusing” images of objects/phenomena deemed “relevant”, while those identified as “background noise” are excluded from processing.

It can be argued that eye movements are indicators of attentional processes, and that their evaluation enables us to predict which information most influences the final decision.

With the eye-tracking method, the minute movements made by the eyeballs while an individual is observing a controlled visual stimulus (an image or a document) are measured non-invasively, safely and objectively: we thus obtain a series of quantitative parameters, such as background noise level, background noise intensity, duration of exposure, and so on.

Some studies on the visual attention process in neurofinance and decision-making

In some research carried out by BrainLine on investment products described by the Key Investor Informational Document (KIID) (Ceravolo et al. 2019, 2020), it was observed how the layout and color of information documents affect the allocation of attention and the perception of product attractiveness by the subjects interviewed. In a succession of visual or auditory information, the position occupied by a stimulus represents a significant factor in the probability of it being considered as the object of attention, and deserves to be taken into consideration.

The anchoring effect is the phenomenon whereby individuals attribute a determining value (with a view to subsequent decision-making) to the first or last (the anchor) in a set of information (Turner & Schley, 2016). Numerous studies testify to the use of anchoring even when making decisions in real estate (Lambson et al. , 2004) or finance (Baker et al. , 2016; Dougal et al. , 2015).

In a recent study (Ceravolo et al. , 2021), BrainLine researchers investigated the role of anchoring in subjects’ assessment of the attractiveness of current account prospectuses by reading and evaluating a piece of information (Fee Information Document – FID). The aim of the FID, introduced by the Payment Accounts Directive, is to improve the transparency of charges and information relating to current accounts. 

The study, carried out on 70 cases, confirmed the tendency of respondents to anchor their judgement of product attractiveness to the information presented in the top left-hand corner (in this case the annual fee), neglecting other elements and thus making unprofitable decisions in many cases. Subjects with low levels of financial education were more likely to use the anchoring heuristic, basing their decisions on biased assessments of available information.

Decision-making processes, algorithms and advisors: who can we trust?

To cope with the abundance of information and its growing complexity, individuals often decide to rely on operators in the banking and financial sector. Numerous researchers have studied the appearance, personality and behavioral characteristics of financial advisors, which influence consumers’ willingness to follow their advice.

In finance, no study to date has investigated the advisor’s influence on subjects’ visual attention mechanisms and the likelihood of them accepting the advice they receive.

A recent study (Fattobene et al., 2022) attempted to fill this gap by assessing the distribution of visual attention. Subjects analyzed a pre-contractual information document on a consumer loan application (the Standard European Consumer Credit Information – SECCI), while alternately receiving advice from a human operator or an algorithm.

It was observed that attention to specific interests (notably those related to costs) was modulated by the type of advisor. Subjects show a different distribution of attention, and in particular of costs, when the advice to buy the product is provided by a human rather than an algorithm. The different attention mechanisms according to advisor type are followed by a different tendency to trust the algorithm, depending on whether the contract conditions are objectively advantageous or disadvantageous.

Neurofinance and decision-making: edited by Maria Gabriella Ceravolo, Gianmario Raggetti, Lucrezia Fattobene, translated and adapted by Neuroprofiler. 

L’article Neurofinance and decision-making est apparu en premier sur Neuroprofiler.

You are quite busy and do not have a lot of time to make your investment decision. What is your strategy to choose the right funds?

Strategy 1: analytical thinking

You analyze one by one the elements which are important in your investments., you want of course a fund with a good past performance, but also with a strong ESG impact, if possible in climate change mitigation. You want if possible to avoid complex products like structured or derivative products since you are not familiar with their mechanisms… Finally, you end up with a list of about 7/8 criteria to find the right fund.

You can try to use your analytical system 2 by considering each criteria one by one. Unfortunately most of us cannot cope with more than five criteria at once, especially if they do not have the same importance. So the best thing you can do if you want to be rigorous is to write all our weighted criteria on a paper or excel file and make a few calculations.

If time allows, this is the best approach. However, the risk, if time is limited, is to do this job partially and to end up with the wrong choices.

Strategy 2: intuitive thinking

In practice, people rarely follow the first scenario. It is quite laborious and time-consuming.

Most investors will read quickly the fund descriptions and make their choice intuitively.

What is the most effective strategy?

Behavioral experiments have shown that for simple decisions (where, for instance, we would have only three criteria to choose between two wines), the analytical thinking approach (strategy 1) is the most effective.

Yet, for complex decisions, like in our example of multi-criteria fund selection, the intuitive approach is more effective, especially if our time is limited.

Why? Because our analytical brain is not able to consciously manage a huge quantity of data. If we try to use our analytical brain (System 2) in a too complex situation, we will not finish our reasoning and finally focus on one arbitrary criteria. For instance, we will focus only the funds’ risk or ESG impacts, ignoring the other criteria even if they are as important.

The reasoning will thus be incomplete and the result will not be satisfying, unless we have tools to help us manage rigorously this amount of data, like an excel file or a robo-advisory process.

If not, the intuitive approach will be more effective. The results may not be optimal, but more satisfactory than in the first approach.

Behavioral economic experiments

To test the hypothesis described above, Dijksterhuis and co ran the following experiment.

Two groups had to choose their favorite car in a list of four, each one described by 12 attributes.

The first group was asked to read the description of the cars before doing a 4-minute long task to finally spontaneously choose their favourite car.

On the contrary, participants of group 2 had 4 minutes to view and review the criteria to make up their mind. At the end, Group 1 made better decisions than Group 2. The spontaneous answer of Group 1 triggered by their intuitive mind, was better than the thoughtful answer of Group 2.

Further studies have shown that in both cases, groups use their prefrontal cortex which is correlated with high cognitive decision-making.

Conclusion

Our intuition can sometimes provide better solutions than our analytical mind for complex problems

References

Unconscious errors enhance prefrontal-occipital oscillatory synchrony
Michael X Cohen1,2* †, Simon van Gaal1,3†, K. Richard Ridderinkhof1 and Victor A. F. Lamme3 Pessiglione, M., Schmidt, L.,
Draganski, B., Kalisch, R., Lau, H., Dolan, R. J., et al. (2007).
On Making the Right Choice: The Deliberation-Without-Attention Effect, Dijksterhuis,Bos,Nordgen,Baaren
Activation of the Cognitive Control System in the Human Prefrontal Cortex, HakwanC. Lau1,2 and Richard E. Passingham
How the brain translates money into force. A neuroimaging study of subliminal motivation. Science, 316, 904–906

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We have a new job promotion. We have kissed for the first time our new girlfriend. We have won 4 times in the casino. This is our day of chance, we should continue playing (gambler’s fallacy)! This is a much nicer story to tell than just saying that we have had today an accumulation of positive but independent events.

This appetence for story-telling leads us to often take correlation for causality, and to draw conclusion from a limited number of data (small sample bias).

Funds in the luxury sectors have outperformed the last three winters? It means that we should invest in the luxury sector specifically in winter. The top three startups of the year are managed by three cofounders? It means that startups should have three cofounders to be successful!

Let’s take the example below of a perfect correlation between the number of suicides by hanging, strangulation and suffocation and… US spending on science, space and technology.

Even if the correlation is nice, there is obviously no causality between this 2 phenomena, even if we are strongly tempted to find a nice story to tell…perhaps the US spending is so depressing that it generates a high level of suicides?

Financial markets cannot always been explained by nice stories

This heuristics strongly influences our financial decisions and leads a number of specific biases.

Gambler’s fallacy

This bias, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the incorrect belief that, if a particular event occurs more frequently than normal during the past, it is less likely to happen in the future (or vice versa), even if the events are in fact independent.

This fallacy is commonly associated with gambling and investing, where it may be believed, for example, that the next dice roll is more than usually likely to be six because there have recently been fewer than the usual number of sixes. In the case of investing, it can be that, since a specific fund has decreased during 6 consecutive days, there is a high chance that it will go up on the 7th day.

Survivorship bias

Survivorship bias is the tendency for failed companies to be excluded from performance studies because they no longer exist. It often causes the results of studies to skew higher because only companies that were successful enough to survive until the end of the period are included. For example, a fund company’s selection of funds today will include only those that are successful now. Many losing funds are closed and merged into other funds to hide poor performance. In theory, 70% of extant funds could truthfully claim to have performance in the first quartile of their peers, if the peer group includes funds that have closed.

Confirmation Bias

This the tendency to search for, interpret, favor, and recall information in a way that confirms or supports our prior beliefs. We are convinced that the luxury sector is highly profitable. Before investing, when we will look at the description of mutual funds, we will only focus on the positive aspects of the description if the fund invests in luxury, and only on negative features for fund which do not. If we do not do so, our global story will be inconsistent…

Rationalization 

This behavior is a defense mechanism (ego defense) in which apparent logical reasons are given to justify behavior that is motivated by unconscious instinctual impulses. You have invested in the luxury sectors in the past. You do not remember why. The sector of luxury collapsed. Your relatives tell you that it was not a very good idea to invest so much in this sector.

You may rationalize a posteriori your choice to make it consistent and rational (i.e. to have a nice story to tell). You may explain that this investment was very rational, and that this decrease means than a huge increase will follow soon and make your investment even more profitable

References

• McLaughlin, Brian P.; Rorty, Amélie, eds. (1988). Perspectives on Self-deception. University of California Press.
• Tsang, Jo-Ann (2002). “Moral rationalization and the integration of situational factors and psychological processes in immoral behavior” (PDF). Review of General Psychology. 6 (1): 25–50
• Kahneman, Daniel. Thinking fast and slow.

L’article Beyond rationality: We love nice stories est apparu en premier sur Neuroprofiler.

How do you proceed to take your final decision? Can you trust your intuition?

Intuition and heuristics

When we use our intuition (see system 1) to make decisions, we usually use heuristics.

It refers to any approach which helps to make decisions quickly and effectively, even if there are not always optimal or fully rational. There are mental shortcuts, rule of thumb or educated guess which help us to make decisions quickly and often effectively with a limited cognitive load.

Heuristics are an effective way to solve rapidly complex problems. Nevertheless, the provided answer is often an approximation or even false. It is thus important to learn the ”bad habits” of heuristics to use them adequately.

In the Kahneman system, this corresponds to our system 1, while our system 2 will correspond to a thoughtful approach of the problem.

To come back to our problem, the intuitive approach will mean that, after reading all the documents, we choose the company that we “feel” the most relevant. IN the thoughtful approach, a new analytical approach will be necessary, like creating an excel file with a specific weight for each criteria, for instance.

So what is the most effective approach? Research in cognitive science has shown that this highly depends on the context.

Criteria 1: Familiarity

The first aspect to consider is if we are making our decision in a familiar or in a new context. Is it the first time we to select this kind of companies or is it a situation we face every month? Do we already have information about the performance of the companies we selected previously?

Heuristics are indeed mostly based on our past experience. More precisely, research in behavioral economics have shown they are based on a Bayesian learning model.

We simply have an a priori belief about, for instance, the link between being a female CEO and being a successful startup that we update each time we interact with a female CEO.

These prior beliefs help us cope with uncertainty. When we face a new situation, we try first to identify similar situations we had in the past to decide how to react. The more similar situations we faced in the past, the most powerful how intuitive thinking should be. An art expert will immediately recognize that a painting is from Picasso, even if he has never seen this painting. For that, he will not use his analytical thinking. His intuitive thinking, based on his numerous past experience, will be more effective.

He will have difficulties to explain why he is convinced that it is a Picasso and justify it by tangible elements.

On the contrary, if you do not know a lot about art and want to identify the author of the painting. We will need time and attention to analyse thoughtfully the painting in order to find the solution based on rationalized elements (date, color, subject, style…).

TO come back to our example, if you are new to VC investing, it may be dangerous to trust your intuition to find the right investment.

To further understand this powerful learning system of the brain, you can look at this more theoretical talk from the University of Edinburgh.

Criteria 2: Number of criteria

Many cognitive experiments have shown that our conscious brain (system 2) cannot deal with a choice where there are more than 5/7 criteria to take into consideration.

This is the case when we want buy a car, for instance. If we focus on a limited number of features (ex: price, color, size, hybrid, brand), we can find the right car using our analytical brain (system 2). If we focus on more criteria (ex: price, color, size, hybrid, brand, look, number of seats, engine power,…), our conscious brain will not be able to manage so much data. Our decision will be biased and suboptimal. We will either focus unconsciously on less criteria, or choose the last car we have seen, or the one our neighbor has just chosen… The experiments show that we will be less satisfied by our choice in this case than if we had chosen the right car intuitively.

If we come back to our example, our analytical brain can be effective if the selection criteria are limited and quite clear. For instance, the company should have a minimum turnover of 1M euros, should have a developed technology and have a positive environmental impact.

In this case, the choice can be quite straightforward. If there are more criteria, the analytical decision will be complicated and you may certainly need to if

If the list of criteria is much longer or very subjective, our analytical brain may not be able to treat properly so much data. There will be the option to use tools to help us (excel, paper, decision-making software…), or to trust our intuition if time is limited and do not allow this time-consuming decision-making processes.

Criteria 3: Time and effort

Using our analytical brain is always more time and effort-consuming that using our intuition. If your time is very limited or if you are very tired, you may not be able to use your system 2 properly. You will, for instance, analyze the first 3 companies in details, and then give up. In this case, it should be much more effective to use our intuitive brain than using our broken analytical decision-making process.

Criteria 4: Situation prone to personal biases

A last aspect to take into consideration is your knowledge of potential biases which could influence your decisions. You love biscuits. One of the companies offer a new concept of biscuits. You are biased in favor of this company. You know the father of one of the founders ? Even worth…

In these situations, trusting your intuition may be suboptimal. Coming back to a more analytical approach may help you to limit these biases.

References 

Thinking fast and slow, D.Kahneman, 2001

Antifrigale, Nassim Taleb, 2012

Knill, D. C., & Pouget, A. (2004). The Bayesian brain: the role of uncertainty in neural coding and computation. TRENDS in Neurosciences, 27(12)

L’article Can we trust our intuition? est apparu en premier sur Neuroprofiler.