Behavioural Finance 101: Overcoming Cognitive Biases in Investing
Most investors believe they make rational decisions. Yet research consistently shows that human psychology often steers us away from logic. Behavioural finance sits at the crossroads of psychology and economics. It explains why even smart, experienced investors repeatedly make the same costly mistakes. Understanding this field is one of the most valuable steps any investor can take.
This guide walks through the core principles of behavioural finance. It covers the most common cognitive biases in investing and offers practical strategies to overcome them. Whether you are a beginner or a seasoned trader, knowing your own psychological blind spots is essential.
Traditionally, finance theory assumed that investors act rationally. They were supposed to process all available information and maximise utility. However, real-world behaviour tells a very different story. People sell winning stocks too early and hold losers too long. They chase trends, ignore evidence, and let fear drive their choices. These patterns are not random. They are predictable, repeatable, and rooted in how the human brain works.
What Is Behavioural Finance?
Behavioural finance is a field that studies the effects of psychological influences on financial decisions. It challenges the traditional view that markets are always efficient and that investors are perfectly rational. Instead, it accepts that people are human. They have emotions, biases, and limited attention. These factors shape their financial behaviour.
The field draws heavily from cognitive psychology and economics. Researchers like Daniel Kahneman and Amos Tversky laid the groundwork with their landmark Prospect Theory research in the 1970s. Kahneman later won the Nobel Prize in Economics in 2002 for this work. Their findings showed that people respond very differently to losses than to equivalent gains.
Specifically, losses feel roughly twice as painful as equivalent gains feel rewarding. This asymmetry has massive implications for how investors behave. It explains why so many people hold onto losing positions far too long. It also explains why they sell winners too quickly to lock in gains and avoid the emotional risk of watching profits disappear.
Furthermore, behavioural finance introduced the concept of bounded rationality. This suggests that people try to make rational decisions, but are limited by available information, cognitive capacity, and time. As a result, they rely on mental shortcuts called heuristics. These shortcuts often work well in everyday life, but they can lead to serious errors in complex financial environments.
Why Cognitive Biases Matter for Investors
Cognitive biases are systematic errors in thinking that influence judgment and decision-making. They are not the result of ignorance or stupidity. Rather, they emerge from the way our brains are wired to handle information. In the context of investment decision-making, these biases can cause investors to misinterpret data, overreact to news, and consistently underperform the market.
According to Morgan Stanley research, there are over 150 documented behavioural biases that can impact decision-making in financial markets. Many of these biases operate below conscious awareness. This makes them particularly dangerous because investors may not realise they are being influenced until after the damage is done.
Consider a typical market downturn. Rational analysis might say: hold your position or buy more at lower prices if fundamentals remain strong. Yet emotional instinct tells investors to sell everything and stop the pain. This tension between logic and emotion is at the heart of behavioural finance. It helps explain why market bubbles and crashes occur with such regularity.
Ultimately, understanding your biases does not eliminate them. However, awareness is the critical first step. Once investors know what to look for, they can build processes and habits that limit the damage these biases cause.
Confirmation Bias: Hearing Only What You Want to Hear
Confirmation bias is one of the most pervasive cognitive biases in existence. It refers to the tendency to search for, interpret, and remember information that confirms your pre-existing beliefs. At the same time, people discount or ignore contradictory evidence.
In investing, confirmation bias shows up constantly. An investor who is bullish on a particular stock will actively seek out positive analyst reports and favourable news articles. When they encounter negative data, they tend to dismiss it as biased or temporary. Over time, this creates a distorted view of reality.
This bias can be particularly damaging during extended bull markets. Investors who believe markets will keep rising will find confirmation everywhere. They may dismiss rising valuations, increasing debt levels, or slowing earnings growth as minor concerns. Eventually, the correction arrives, and the losses can be severe.
To combat confirmation bias, investors should actively seek out opposing viewpoints. Reading bear case arguments for stocks you own is a powerful exercise. Joining investment communities where healthy debate is encouraged also helps. Additionally, keeping a structured investment journal that records your original thesis and tracks how reality compares to expectations can expose gaps in your thinking.
Loss Aversion: The Painful Truth About Losing
Loss aversion is arguably the most studied bias in behavioural economics. It describes the tendency to feel the pain of losses more acutely than the pleasure of equivalent gains. As noted earlier, research suggests losses hurt approximately twice as much as gains feel good.
For investors, loss aversion manifests in several destructive ways. First, it leads to the disposition effect: the tendency to sell winning investments too early and hold losing investments too long. Investors want to avoid the emotional pain of realising a loss, so they hold on, hoping the price will recover.
Second, loss aversion can paralyse decision-making entirely. When markets are volatile, some investors freeze. They cannot bring themselves to buy because they fear the price will drop further. Equally, they cannot sell because selling locks in the loss. This inaction itself has a cost, as opportunities pass by while they wait for certainty that never comes.
Overcoming loss aversion starts with reframing how you think about losses. Instead of viewing a realised loss as failure, consider it the cost of information. Every investment teaches you something. Using stop-loss orders to automate selling decisions removes the emotional element. Pre-committing to an exit strategy before you invest can also help enormously.
Common Cognitive Biases in Investing: A Summary
| Bias | What It Means | Common Outcome | Key Remedy |
|---|---|---|---|
| Confirmation Bias | Seeking info that confirms beliefs | Ignoring warning signs | Seek opposing views actively |
| Loss Aversion | Losses feel twice as painful as gains | Holding losers, selling winners early | Use pre-set stop-loss orders |
| Overconfidence Bias | Overestimating skill and knowledge | Excessive trading, under-diversification | Track and review all decisions |
| Anchoring Bias | Over-relying on first piece of info | Poor valuation judgments | Use multiple valuation methods |
| Herd Mentality | Following the crowd | Buying peaks, selling troughs | Research independently |
| Recency Bias | Overweighting recent events | Chasing past performance | Focus on long-term data |
| Mental Accounting | Treating money differently by source | Suboptimal portfolio choices | View portfolio as a whole |
Overconfidence Bias: When Investors Think They Know Better
Overconfidence bias is the tendency to overestimate one’s own abilities, knowledge, and accuracy of predictions. Studies show that the vast majority of investors believe they are above-average at picking stocks. Statistically, of course, this cannot be true for everyone.
This bias is particularly common among investors who have experienced a period of success. After a few winning trades, it is tempting to attribute the gains to skill rather than luck or favourable market conditions. Overconfident investors tend to trade more frequently, hold more concentrated positions, and take on more portfolio risk than is prudent.
Research from Brad Barber and Terrance Odean found that individual investors who traded most actively earned the lowest returns. Overconfidence drives excessive activity, and that activity generates transaction costs and tax liabilities that erode returns.
To counter overconfidence, investors should maintain a detailed trading log. Recording every decision, including the reasoning behind it, and then reviewing outcomes honestly is humbling and educational. Comparing your returns to a simple index fund benchmark is another eye-opening exercise. Many active traders discover they would have done better by doing nothing at all.
Anchoring Bias: Stuck on the First Number You Saw
Anchoring bias occurs when investors place excessive weight on the first piece of information they receive. That initial data point, or “anchor,” then skews all subsequent judgments, even when new information suggests a very different conclusion.
A classic example involves stock prices. Suppose an investor bought a stock at $100 per share. When the price drops to $70, they anchor on the original purchase price. They keep waiting for the stock to “return to $100” before selling, even if the underlying business has deteriorated significantly. The $100 figure becomes a psychological barrier.
Similarly, anchoring affects how investors respond to analyst price targets. If an analyst sets a target of $150 for a stock currently trading at $100, that $150 figure becomes an anchor. Investors may hold the stock far past its fair value simply because they are anchored to that target.
To reduce anchoring effects, investors should rely on multiple valuation methodologies. Using discounted cash flow analysis, price-to-earnings comparisons, and book value assessments together produces a more balanced view. Regularly revisiting investment theses with fresh data also helps break the grip of initial anchors.
Herd Mentality: Why Investors Follow the Crowd
Herd mentality describes the inclination to follow and mimic the financial behaviors of a majority group. It is deeply rooted in human social instinct. In prehistoric times, following the group was often a survival strategy. In financial markets, however, it frequently leads to disaster.
Herd behaviour is what drives speculative bubbles. When investors see others making money in a particular asset, they rush in for fear of missing out. The term for this is FOMO, or Fear Of Missing Out. As prices rise, more investors pile in, pushing prices even higher, until the bubble eventually pops.
The dot-com bubble of the late 1990s is a textbook example. Investors poured money into internet companies with little or no revenue simply because everyone else was doing it. When the bubble burst in 2000, the Nasdaq lost nearly 80% of its value. Many investors suffered devastating losses that they never fully recovered from.
Moreover, herd mentality also works in reverse during market crashes. When others panic and sell, many investors follow without evaluating whether selling is actually the right choice. Breaking free from herd behaviour requires confidence, independent research, and a clearly defined investment strategy that you trust in all market conditions.
Recency Bias: Mistaking the Recent Past for the Future
Recency bias is the tendency to give disproportionate weight to recent events when making predictions. This leads investors to assume that whatever has happened recently will continue to happen. After a bull market, they expect stocks to keep rising. After a crash, they expect further declines.
This bias causes a recurring pattern: investors buy high and sell low. They buy enthusiastically after markets have risen because recent gains feel like proof of a continuing trend. Then they sell anxiously after markets fall because recent losses feel like evidence that things will only get worse.
The data tells a different story. Research on mean reversion consistently shows that asset classes which have performed poorly over recent periods often outperform in subsequent periods, and vice versa. Investors who chase recent performance systematically buy high and sell low.
Combating recency bias requires a deliberate focus on long-term historical data. Reviewing how markets have performed across full economic cycles, rather than just the past one to three years, provides crucial context. Setting a long-term asset allocation strategy and sticking to it mechanically is one of the most effective defences against this bias.
Mental Accounting: Treating Money Like It Comes in Different Colours
Mental accounting refers to the tendency to treat money differently based on its source or intended use. This concept was developed by Richard Thaler, who won the Nobel Prize in Economics in 2017 for his work in behavioural economics. While mental categories can sometimes simplify budgeting, they lead to irrational investment decisions.
For instance, many investors treat a stock market gain as “found money” that is somehow separate from their regular savings. Because it feels like a windfall, they are willing to take far greater risks with it. They might bet the windfall on speculative options or highly volatile assets they would never approach with their “real” savings.
Another common example involves dividend income. Some investors live off dividends without touching principal, even when selling a small amount of principal would be the more tax-efficient choice. They have mentally separated “income” from “capital,” even though money is fungible and a dollar is a dollar regardless of where it came from.
To overcome mental accounting, investors should evaluate their entire net worth as a single, unified portfolio. All assets and decisions should be assessed based on their overall impact on total wealth, rather than the category they fall into.
The Gambler’s Fallacy and Hot Hand Fallacy in Markets
Two closely related biases often trip up investors: the gambler’s fallacy and the hot hand fallacy. Both involve misunderstanding randomness and patterns in financial data.
The gambler’s fallacy is the belief that past independent events influence future outcomes. An investor might reason: “This stock has fallen five days in a row, so it must be due for a bounce.” In reality, each day’s price movement is influenced by new information and conditions. Past declines do not make a recovery more statistically likely.
Conversely, the hot hand fallacy assumes that a recent run of success will continue. After a fund manager delivers three consecutive years of outperformance, many investors assume the winning streak will persist. Research, however, shows that past fund performance is a poor predictor of future results. Most managers who outperform for a period revert to average or below-average returns.
Both fallacies stem from the human desire to find patterns in random data. Our brains are pattern-recognition machines. This trait is useful for many things, but it leads us astray in financial markets, where much short-term price movement is genuinely random. Acknowledging this randomness is an important step toward more disciplined investing.
Key Researchers and Their Contributions
| Researcher | Key Contribution | Year | Impact on Investing |
|---|---|---|---|
| Daniel Kahneman | Prospect Theory, heuristics and biases | 1979 | Foundation of loss aversion research |
| Amos Tversky | Prospect Theory (co-developed) | 1979 | Quantified loss vs gain asymmetry |
| Richard Thaler | Mental accounting, nudge theory | 1980s | Shaped retirement savings policy |
| Robert Shiller | Irrational exuberance, CAPE ratio | 2000 | Market valuation and bubble detection |
| Brad Barber and Terrance Odean | Overconfidence and trading activity | 2000 | Evidence that trading hurts returns |
| Andrei Shleifer | Limits to arbitrage | 1997 | Explains why mispricing persists |
Availability Heuristic: Judging Probability by What You Can Recall
The availability heuristic is a mental shortcut where people estimate the likelihood of events based on how easily examples come to mind. If something is memorable or vivid, the brain tends to judge it as more probable than it actually is.
In investing, this heuristic becomes problematic after high-profile market events. Following a dramatic stock market crash, investors often dramatically overestimate the chance of another crash happening soon. The memory of the crisis is vivid and recent, making it feel more probable than historical data suggests.
Conversely, after a long period of market calm and steady gains, investors underestimate downside risk. The lack of recent disasters makes crashes feel remote and unlikely. Both versions of this bias lead to poor risk management.
Using actual historical base rates rather than intuition is the best defence. Before making any investment decision based on perceived risk, investors should look at how frequently that type of event has actually occurred over long historical periods. Checking resources like the FRED economic database can provide objective data to counter subjective impressions.
Status Quo Bias: The Comfort of Doing Nothing
Status quo bias is the preference for the current state of affairs. People tend to view any change from the baseline as a potential loss, which triggers loss aversion. In investment portfolios, this bias shows up as a reluctance to rebalance, switch funds, or adjust strategy, even when evidence strongly supports doing so.
Many investors hold the same portfolio positions for years, not because their investment thesis remains valid, but simply because it feels safer to stay put. Changing feels risky. Inertia masquerades as prudence. Over time, this can result in a portfolio that is poorly aligned with current market conditions, risk tolerance, or financial goals.
Another manifestation is the tendency to default to employer-provided options in 401(k) plans without evaluating alternatives. Research shows that employees often simply accept whatever default contribution rate and default fund are set for them, even when better choices are available.
Setting a regular portfolio review schedule is one effective strategy. Reviewing your holdings quarterly or semi-annually with fresh eyes forces active evaluation. Automated rebalancing tools offered by most robo-advisors can also remove the friction that feeds status quo bias.
Sunk Cost Fallacy: Throwing Good Money After Bad
The sunk cost fallacy occurs when investors continue to hold or add to a losing position simply because they have already committed significant capital to it. The logic goes: “I have already lost $5,000 on this stock, so I can’t sell now.” But that $5,000 is gone regardless of what you do next.
Past costs that cannot be recovered should be irrelevant to future decisions. Only the current and prospects of an investment should drive your choices. Yet emotionally, it is very difficult to walk away from something you have invested heavily in. This applies not just to money, but to time and emotional energy as well.
In corporate finance, sunk cost thinking leads to classic strategic errors. Companies continue funding failing projects because of the resources already committed, even when discontinuation would clearly be the more rational choice. The same pattern plays out in individual stock portfolios every day.
The remedy is straightforward in theory, though difficult in practice: evaluate each investment based solely on its future expected return relative to risk. Ask yourself: “If I did not already own this position, would I buy it today at this price?” If the honest answer is no, then holding on is irrational, and exiting is the logical choice.
Framing Effects: How Presentation Shapes Your Decisions
The framing effect describes how the way information is presented influences the decisions people make, even when the underlying facts are identical. Investors are highly susceptible to framing, particularly in how financial products and media stories are packaged.
Consider two descriptions of the same fund: “This fund lost 20% in the past year” versus “This fund retained 80% of its value in a down market.” Logically, both statements say the same thing. Emotionally, however, the second framing feels far more reassuring. Investment managers know this, which is why marketing materials carefully choose their framing.
News media also exploit framing. A headline declaring “Markets plunge 3%” creates more fear than “Markets give back recent gains.” Both describe the same movement. However, one activates loss aversion, while the other provides context. Being aware of framing helps investors evaluate information on its own merits.
Practising critical media literacy is a valuable skill. Before reacting to any financial news or report, pause and ask: How else could this information be framed? What would the opposite framing look like? This simple mental exercise helps neutralise the distorting effect of presentation.
Practical Strategies to Overcome Behavioural Biases
Knowledge alone is not enough. Investors also need concrete systems and habits to counteract the pull of cognitive biases. Fortunately, several evidence-based strategies have proven effective in helping investors make better decisions.
First, creating a written investment policy statement (IPS) is highly beneficial. An IPS sets out your investment goals, risk tolerance, time horizon, and the criteria you will use to make buy and sell decisions. Having this document in writing creates an external reference that can anchor you when emotions run high.
Second, adopting a systematic, rules-based approach reduces the role of emotional judgment. Strategies like dollar-cost averaging involve investing fixed amounts at regular intervals, regardless of market conditions. This automatically removes the temptation to time the market based on fear or greed. Evidence consistently shows that this approach leads to better long-term outcomes for most retail investors.
Third, working with a qualified financial advisor provides an objective third-party perspective. A good advisor does not just manage your money. They also manage your behaviour, helping you stay disciplined during market extremes. Research from Vanguard suggests that quality behavioural coaching from an advisor can add approximately 1.5% in net returns per year.
Fourth, diversification across asset classes reduces the emotional impact of any single investment’s performance. When your portfolio is spread across stocks, bonds, real estate, and other assets, one poor performer is less likely to trigger panicked decision-making.
Strategies to Overcome Key Investment Biases
| Strategy | Biases Addressed | How It Helps | Difficulty |
|---|---|---|---|
| Investment Policy Statement | Overconfidence, loss aversion | Anchors decisions to logic, not emotion | Low |
| Dollar-Cost Averaging | Recency bias, herd mentality | Removes market timing temptation | Low |
| Portfolio Rebalancing | Status quo bias, anchoring | Forces selling high and buying low | Moderate |
| Seeking Contrary Views | Confirmation bias | Exposes blind spots in your thesis | Moderate |
| Pre-Commitment Strategies | Loss aversion, sunk cost fallacy | Decisions made before emotion spikes | Moderate |
| Working with an Advisor | Multiple biases | External accountability and coaching | Low to Moderate |
| Mindfulness and Journaling | Availability heuristic, framing | Builds self-awareness over time | Moderate to High |
The Role of Mindfulness and Self-Awareness in Investing
Beyond mechanical systems, developing genuine self-awareness is a powerful tool for any investor. Mindfulness practices have been studied extensively in the context of decision-making. They help individuals recognise emotional states before acting on them. Applied to investing, mindfulness creates a pause between impulse and action.
Keeping a decision journal is one of the most valuable practices any investor can adopt. Before making any significant investment move, write down your reasoning. Note the facts you are relying on, the expected outcome, and how you are feeling in the moment. Then, periodically review past entries and compare what you predicted with what actually happened.
This practice reveals patterns over time. You might discover that you consistently underestimate risk when markets are calm. Alternatively, you might find that your best decisions came when you waited at least 48 hours before acting on news-driven impulses. These personal insights are invaluable and cannot be found in any textbook.
Additionally, meditation and stress management techniques reduce the physiological stress response that market volatility often triggers. Lower stress levels correlate with better decision-making quality. Investors who can remain calm under pressure are far less likely to make impulsive, regret-inducing moves.
Technology and Tools to Help Manage Behavioural Biases
Modern technology offers several tools specifically designed to counteract investor behavioural biases. These platforms use automation and data to reduce the role of emotion in financial decisions.
Robo-advisors like Betterment and Wealthfront automate portfolio construction, rebalancing, and tax-loss harvesting. Because these processes run automatically, investors are not required to make manual decisions that could be distorted by bias. The platform simply executes the predefined strategy.
Behavioural portfolio management tools, such as those used by professional firms following Morningstar’s behavioural insights, analyse portfolio composition and flag when holdings deviate from the intended strategy. These alerts serve as early warning systems when bias may be creeping into decisions.
Furthermore, platforms like Personal Capital (Empower) provide a comprehensive view of all accounts in one dashboard. Having a unified view of your total financial picture helps combat mental accounting. When all assets and liabilities are visible together, it becomes easier to make holistic, rational decisions.
Behavioural Finance in Portfolio Construction
Understanding behavioural biases is not just useful for avoiding mistakes. It can also inform how you construct your portfolio proactively. This is sometimes called behavioural portfolio theory, developed by Hersh Shefrin and Meir Statman as an alternative to traditional mean-variance optimisation.
Rather than treating all assets as part of a single unified pool, behavioural portfolio theory recognises that investors naturally organise their portfolios into mental layers. Each layer serves a different emotional purpose: capital preservation, income generation, or speculative growth.
Practically, this means some investors benefit from having a small “speculation” allocation, perhaps 5% to 10% of the total portfolio, that they can actively manage. This satisfies the psychological desire for excitement and control without putting the core portfolio at risk. By acknowledging the human need for engagement, this approach reduces the temptation to tinker with the main portfolio.
Incorporating ESG investing principles or thematic strategies that align with personal values can also reduce emotional decision-making. When investors genuinely believe in what they own, they are more likely to stay the course during volatility rather than abandoning their positions at the first sign of trouble.
Institutional Investors and Behavioural Biases
Individual investors are not the only ones susceptible to behavioural biases. Professional fund managers, analysts, and institutional investors also fall prey to systematic thinking errors. In fact, group dynamics can amplify certain biases, particularly herd behaviour and overconfidence.
As noted by LNW Advisors, exploring behavioural biases is a key part of manager due diligence. During hundreds of meetings with asset managers each year, skilled allocators look for evidence of cognitive and emotional biases in investment processes, security selection, sell discipline, and portfolio construction.
Groupthink is a particularly dangerous institutional bias. When everyone around the table agrees, dissenting voices are often suppressed. Hiring for diversity of thought, encouraging structured debate, and using pre-mortem analysis techniques can help institutional investment teams maintain intellectual honesty.
Pre-mortem analysis involves asking the team to imagine that a proposed investment has failed catastrophically, and then work backwards to identify the most likely causes. This exercise forces consideration of downside scenarios and counters both overconfidence and confirmation bias effectively.
How Markets Reflect Collective Behavioural Biases
Individual biases do not just harm single investors. When aggregated across millions of market participants, they shape price dynamics and create market anomalies. Understanding these market-level effects is at the core of behavioural economics in finance.
The equity premium puzzle is one such anomaly. For decades, stocks have returned significantly more than risk-free assets like government bonds, far more than standard rational models would predict. Behavioural economists argue that loss aversion causes investors to demand an excessively high return to take on equity risk, which results in persistent overpricing of safety and underpricing of stocks.
Momentum effects are another anomaly explained by behavioural finance. Stocks that have performed well recently tend to continue outperforming in the short term. This happens partly because investors are slow to update their beliefs and partly because herd behaviour creates self-reinforcing price trends.
Value investing, championed by legends like Warren Buffett and Benjamin Graham, can be understood through a behavioural lens. Value stocks are cheap precisely because investors are irrationally pessimistic about them, often due to recency bias after a period of poor performance. Contrarian investors who can resist herd instinct and buy unloved assets often earn superior long-term returns.
Teaching Behavioural Finance: Building Better Investor Habits from the Start
One of the most effective interventions is education. Introducing financial literacy programs that include behavioural finance content from an early age can build more rational investor habits. When young people understand why biases exist and how they operate, they are better equipped to recognise them in real time.
Many universities now offer dedicated behavioural finance courses. These programs teach students to analyse financial decisions through both quantitative and psychological lenses. Graduates who understand behavioural finance enter the workforce as more reflective, disciplined investors and advisors.
Online resources have also made this knowledge widely accessible. Platforms like Coursera and edX offer courses on behavioural finance from leading universities. These courses allow anyone to study the psychological foundations of financial decision-making at their own pace.
Importantly, behavioural finance education should not stop after one course. Markets evolve. New forms of bias emerge as technology changes how information is delivered and consumed. Ongoing learning is therefore essential for investors who want to stay sharp and self-aware.
The Future of Behavioural Finance: AI, Algorithms, and Human Bias
As artificial intelligence and algorithmic trading become more prevalent, the landscape of behavioural finance is evolving. Algorithms, unlike humans, do not experience fear or greed. They execute strategies with mechanical precision. However, they are built and programmed by humans, which means they can encode human biases into their design.
Research in AI bias has shown that machine learning models can perpetuate and even amplify existing biases present in their training data. An algorithm trained on historical data that reflects past market behaviour may systematically favour certain types of assets or exclude others based on patterns that reflect human bias rather than fundamental value.
Furthermore, the rise of social media-driven investing has created new channels for bias to spread rapidly. The meme stock phenomenon of 2021, exemplified by the GameStop short squeeze, demonstrated how herd behaviour can be amplified dramatically through digital platforms. Understanding behavioural finance is therefore more relevant than ever.
Looking ahead, the most successful investors of the future will likely be those who combine the discipline of algorithmic systems with genuine self-awareness. They will use technology to reduce the noise of emotion while also remaining vigilant about the human assumptions baked into those systems.
Spend some time for your future.
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Disclaimer
This article is for educational and informational purposes only. It does not constitute financial, investment, or legal advice. Always consult a qualified financial professional before making investment decisions. Past performance is not indicative of future results. All investing involves risk, including the possible loss of principal.
References
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- [7] LNW Advisors, “Behavioural Finance: Recognising Biases and Avoiding Mistakes,” 2023. [Online]. Available: https://lnwadvisors.com/
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