Behavioural biases and evaluating sources: how investors go wrong, and how to check a claim
What an investor earns depends on what the investor does, and on whom the investor believes. This lesson sets out the behavioural patterns documented in research for the US SEC, such as loss aversion, the disposition effect and herd behaviour, then tests the cost of reacting to a bad year with real market data. It ends with a practical guide to evaluating investment claims, built on the SEC's red-flag checklist and its warnings about social media and paid promotion.
- Level
- Beginner
- Reading time
- About 26 minutes
- Know this first
- Fees, taxes and net returns
By the end you will be able to:
- name common behavioural biases and describe how each can hurt returns
- test a reactive selling rule against staying invested, and read the result honestly
- list the main red flags of investment fraud
- compare a promised return with the record of a broad index
- apply a short checklist to any investment claim
The investor is part of the system
The earlier lessons in this module treated returns, risk and costs as numbers. But the return an investor actually earns also depends on what the investor does. A fund can earn a good return while the person who owns it buys late and sells in a panic. And before any decision there is a question about information: whose claims can be trusted?
This lesson has two parts. The first covers the habits of mind that study of investors has documented, and measures the cost of one of them with real market data. The second is a practical guide to evaluating a claim about an investment, drawn from the US Securities and Exchange Commission's warnings about fraud and social media. It closes the module on investments and markets, and it draws on the lessons on risk and return and fees.
Behavioural biases
Behavioural finance studies how people actually make financial decisions, as opposed to how a perfectly rational person would. A report prepared for the SEC by the Library of Congress's Federal Research Division, Behavioral Patterns and Pitfalls of U.S. Investors (2010), summarises the research of many scholars. The table lists some of the patterns it describes, using its wording where possible.
| Pattern | What the research says | A practical counter |
|---|---|---|
| Overconfidence | Common among investors and triggers a wide range of investment errors | Keep a record of past decisions and their results |
| Loss aversion | Attaching more importance to avoiding losses than to achieving gains | Decide the plan before a fall, not during it |
| Myopic loss aversion | The tendency of loss-averse investors, even long-term ones, to evaluate their portfolios frequently | Review on a set date |
| Disposition effect | The tendency to sell winning positions and hold on to losing ones | Ask whether you would buy it today |
| Familiarity bias | Preferring to invest in what is familiar: one's own country, region and company | Check how much rides on one employer or country |
| Herd behaviour and momentum | Buying securities with high recent returns and selling those with low recent returns, described as herd behaviour | Be wary of "everyone is buying it" |
| Excessive trading | Active trading linked to overconfidence and underperformance | Count the costs of each trade |
| Past returns over costs | Investors may disregard the costs of actively managed plans, focusing on annualised returns | Compare returns after costs |
| Inertia and defaults | People tend to do nothing when they must opt in, and to accept the default options | Choose your options on purpose |
These are tendencies, not laws, and they describe averages across many investors. They are worth knowing because each one has a counter-habit: a written plan, a fixed rebalancing date, a cost check before buying, and a pause before trading on an impulse.
What reacting to a bad year costs
Loss aversion and herd behaviour both push an investor toward selling after a fall. The calculator tests one such rule on the real data from the earlier lessons: US stocks and 10-year Treasury bonds, 2000 to 2024. The steady investor stays in stocks throughout. The reactive investor moves to bonds for the following year whenever stocks have just had a year worse than the level you set, and goes back to stocks the year after that. In the first year of the data, the reactive investor is in stocks. Set the trigger, the first year, and how many years to cover. At the starting settings the trigger is a fall worse than −10% and the period is 2015 to 2024.
Staying in stocks from 2015 to 2024 returned 12.98% a year and turned $10,000 into $33,874. An investor who moved to bonds for the next year after a year worse than −10% spent 1 year in bonds, returned 10.81% a year and ended with $27,914, $5,960 less.
Four experiments. First, at the starting settings the only trigger is 2022, when stocks fell 18.04%. The reactive investor sits in bonds in 2023, misses the 26.06% rebound for that year, and finishes $5,960 behind. Second, set the trigger to any loss. Now 2018 also triggers, and the reactive investor ends $10,549 behind. Third, set the first year to 2000 and the history to 5 years. The rule now finishes $1,368 ahead, because bonds' +15.12% in 2002 more than made up for stocks' −21.97% that year, even though the investor then missed the rebound in 2003. Fourth, set the first year to 2000 and the history to 10 years. The same rule now ends $1,688 behind: bonds lost in 2009 and the investor missed that year's recovery in stocks.
Across all the settings the calculator allows, the rule was never triggered at all in 155 of them, finished ahead in 36 and behind in 289. It helps only if the investor happens to leave before a fall and return before the recovery, and the calendar rarely cooperates. The table shows the three periods used above:
| Reactive rule: move to bonds after a fall worse than −10% | 2015 to 2024 | 2000 to 2004 | 2000 to 2009 |
|---|---|---|---|
| Steady investor, compounded | 12.98% | −2.32% | −0.95% |
| Reactive investor, compounded | 10.81% | 0.52% | −2.97% |
| Years in bonds | 1 | 2 | 3 |
| Steady: $10,000 becomes | $33,874 | $8,894 | $9,086 |
| Reactive: $10,000 becomes | $27,914 | $10,262 | $7,398 |
| Reactive versus steady | −$5,960 | $1,368 | −$1,688 |
This is one rule on one dataset. It does not show that no timing strategy can ever work. It shows how easily a plausible-sounding rule can lose, and that the outcome depends heavily on the particular years.
Evaluating a claim about an investment
The second part of the lesson is about information. Anyone can publish an investment claim online, and the SEC's alert on social media notes that social media lets fraudsters contact many different people at a relatively low cost, and that it is easy to create a site, account, email, direct message or webpage that looks and feels legitimate. It also warns that some companies pay online newsletters to tout their stocks, and that fraudulent promoters may claim to give independent, unbiased recommendations when they are in fact insiders or paid promoters who stand to gain from selling their shares.
The SEC's checklist of red flags of investment fraud is the best short guide. It lists:
| Red flag from the SEC checklist | A quick check |
|---|---|
| Unlicensed investment professionals | Check the person on your regulator's register |
| Aggressive sellers who may give exaggerated or false credentials | Verify the credentials independently |
| Offers that sound too good to be true | Compare the promise with a broad index |
| "Risk-free" investment opportunities | Every investment has some risk |
| Promises of great wealth and guaranteed returns | No honest seller can guarantee returns |
| "Everyone is buying it" pitches | Popularity is not evidence |
| Pressure to invest right now | Take time and ask questions |
| Over-the-top pitches with fake testimonials | Never rely on a testimonial |
| Unsolicited pitches seeking your personal information | Do not share it; contact the firm yourself |
| Asked to pay by credit card, gift card, or by wiring money abroad or to a personal account | Treat any unusual payment method as a warning |
The SEC's advice is to ask questions, research every investment thoroughly before investing, and run a background check on any investment professional. It also advises checking whether an offering is registered. In the United States that can be done through the SEC's EDGAR filing system, your state's securities regulator, and FINRA's BrokerCheck website. Other countries have their own regulators and registers, and your own national regulator's website is the place to look.
Test a promise against the data
The SEC also advises comparing any promised return with the returns on well-known stock indexes. The real data from this module gives a benchmark. US stocks including dividends returned 7.62% a year compounded over the 25 years 2000 to 2024, and 10-year Treasury bonds 3.66%. Suppose someone offers a guaranteed 20% a year. Over ten years, $10,000 at 20% a year would become $61,917, compared with $33,874 in US stocks over 2015 to 2024, which was a very good decade for them. A promise that beats the best stock market decade, with a guarantee attached, is the kind of offer the SEC describes as sounding too good to be true. Stocks' best single year in this dataset was 32.15%, in 2013, so a promise of 20% every year, with no bad years, is outside anything in the record.
A short checklist for any claim:
What this lesson cannot tell you
- Biases are tendencies. The research describes patterns across groups of investors, not what any one person will do.
- The calculator tests one rule. It uses annual data, one country and two assets, and a single trigger. Other rules and other years could give other answers.
- Windows are short. Five to ten years of annual data is a small sample.
- Costs and taxes are ignored. Switching in and out would add trading costs and possibly tax.
- A red flag is a warning, not proof. The checklist helps you decide when to investigate further.
- Regulators differ by country. The registers named come from the US. Look up your own country's regulator.
- This is education, not advice. It does not say what any person should buy or sell.
Common mistakes
Selling after a fall and buying back after the recovery
The best and worst years often sit close together. An investor out of the market for the rebound can lose far more than the fall avoided.
Following the crowd because everyone is buying
The SEC lists "everyone is buying it" pitches among the red flags.
Judging a fund by its recent return alone
The report notes that investors may focus on annualised returns and disregard costs. Look at the fees too.
Trusting a testimonial
The SEC says never to rely on a testimonial or take a promoter's word at face value.
Holding too much of one company
Familiarity bias leads people to favour their own country, region and employer. A job and a large share holding in the same company concentrates risk.
Try it yourself
1. An investor holds Stock A, up 20%, and Stock B, down 20%, and needs cash. Which does the disposition effect suggest she will sell?
Show the working
The disposition effect is the tendency to sell winning positions and to hold on to losing ones, so she is likely to sell Stock A. Whether that is the right choice depends on the outlook for each, not on whether it is up or down.
2. An offer promises a guaranteed 20% a year. What would $10,000 become after ten years, and how does that compare with US stocks in 2015 to 2024?
Show the working
10,000 × 1.2^10 = $61,917. US stocks turned $10,000 into $33,874 over 2015 to 2024. A guarantee of more than that, with no risk, is a red flag.
3. After 2022, stocks were worth $8,196 per original $10,000. In 2023 stocks returned 26.06% and bonds 3.88%. What are the two investors worth at the end of 2023?
Show the working
Staying in stocks: 8,196 × 1.2606 = $10,332. Moving to bonds: 8,196 × 1.0388 = $8,514. The one who left after the fall was behind by the difference, about $1,818.
4. A friend sends a message: "A new coin is going up fast, everyone is buying it, you must decide today." Which red flags from the SEC's list appear?
Show the working
"Everyone is buying it" pitches and pressure to invest right now. Both appear on the SEC's list. Before doing anything, check who is selling, whether it is registered, and whether the promised outcome is realistic.
5. The report describes myopic loss aversion as the tendency of loss-averse investors, even long-term ones, to evaluate their portfolios frequently. Why might that lead to worse decisions?
Show the working
Each time an investor checks, a fall is visible and feels painful, which makes selling more tempting. A plan that sets a fixed review date, such as once a year, reduces the number of moments at which a panic sale can happen.
Where this is used
- An adviser helps a client write down a plan, with rules for when to rebalance, so that decisions are not made in a panic.
- A retirement plan sets sensible default options, because the research notes that many people accept the default.
- A regulator publishes red-flag checklists and registers so the public can check sellers.
- A reader of financial news or social media asks who is speaking and whether they are paid.
Key terms
- Behavioural finance
- The study of how psychology affects financial decisions.
- Overconfidence
- Believing one's judgement or skill is better than it is.
- Loss aversion
- Giving more weight to avoiding losses than to achieving gains.
- Disposition effect
- The tendency to sell winning positions and hold on to losing ones.
- Herd behaviour
- Following what other investors are doing.
- Familiarity bias
- Preferring to invest in what is familiar, such as one's own country or employer.
- Touting
- Paid promotion of a stock, which is lawful only when the payment is disclosed.
- Red flag
- A warning sign that an investment offer may be fraudulent.
Questions people ask
Can I remove these biases?
Not entirely. The practical response is to set rules in advance, such as a plan, a review date and a check of costs, so that decisions are not made in the heat of the moment.
Does the calculator prove market timing never works?
No. It tests one simple rule on one dataset and finds that it finished behind more often than ahead. Some settings favour it, and it is shown above.
Are all online investment sources unreliable?
No, but anyone can publish, so the burden is on the reader to check who is speaking, whether they are paid and whether the claim can be verified elsewhere.
Where do I report a suspected scam?
To your national financial regulator. In the United States, the SEC accepts tips and complaints through its website.
Sources and review
- Federal Research Division, Library of Congress, for the US Securities and Exchange Commission, Behavioral patterns and pitfalls of U.S. investors (August 2010), for the descriptions of overconfidence, loss aversion, myopic loss aversion, the disposition effect, familiarity bias, herd behaviour and momentum, excessive trading, attention to past returns over costs, and inertia and defaults.
- US Securities and Exchange Commission, Investor.gov, Red flags of investment fraud checklist, for the list of red flags and the advice to ask questions, research every opportunity and run a background check on any investment professional.
- US Securities and Exchange Commission, Investor.gov, Updated investor alert: social media and investing, avoiding fraud, for how fraudsters use social media, paid touting, the advice not to rely on testimonials, the registration checks and the advice to compare promised returns with well-known stock indexes.
- Aswath Damodaran, NYU Stern, Historical returns on stocks, bonds and bills: 1928-2024 (last updated 5 January 2026), for the annual returns of the S&P 500 including dividends and of the 10-year US Treasury bond for 2000 to 2024. The page names its data source as multiple data services.
How the numbers were checked: the returns of the two investors, the years spent in bonds and the dollar differences were recomputed in plain code, and the calculator, which runs separately, was compared with that code for every combination of settings it allows. The counts of settings are from the same code. The market returns come from the dataset cited above, and the descriptions of biases and red flags are taken from the cited SEC documents.