Behavioral Biases Part 2 - Emotions and Debiasing
This is a retelling of Chapter 2 (second half) from “Behavioral Finance for Private Banking” by Thorsten Hens, Enrico G. De Giorgi, and Kremena K. Bachmann (Wiley, 2018).
In Part 1, we covered heuristics and judgment traps. The biases that mess with how you gather and interpret information. Now we get to the emotional side. The biases that hit you in the gut. Loss aversion, mental accounting, regret, herding. And at the end, actual strategies you can use to fight back.
Present Bias: “I Want It Now”
Here is a simple test. Would you prefer $100 in two weeks, or $102 in two weeks and one day? Most people pick the $102. Easy choice. But now ask: $100 right now, or $102 tomorrow? Suddenly most people grab the $100 today.
Same math. Different answer. That is present bias.
It is the reason people struggle to start saving for retirement, quit smoking, or begin a diet. The pain is now, the benefit is far away. For investors, this means procrastination on important financial decisions.
The fix? Commit in advance. The Save More Tomorrow (SMarT) program works exactly this way. People agree now to save more when their next salary increase comes. They never feel the loss because they commit before the money is in their hands.
Probability Weighting: Why People Buy Lottery Tickets
Kahneman and Tversky found something interesting about how we handle probabilities. We overweight rare events and underweight common ones.
The jump from 0% to 1% feels huge psychologically. “Impossible” to “possible” is a big deal in your brain. But the jump from 49% to 50%? Just “likely” to “slightly more likely.” Nobody cares.
This is why people buy lottery tickets even when the math is clearly against them. The tiny chance of a giant win feels bigger than it actually is. And for investors, this means overreacting to rare market disasters. You might avoid stocks entirely because of some small probability crash scenario that your brain treats like it is much more likely than it really is.
Loss Aversion: Losses Hurt Twice as Much
This one is probably the most famous finding in behavioral finance. You lose $100, and to feel better you need to gain not $100, but about $200. Losses feel roughly twice as painful as equivalent gains feel good.
But here is the problem. Whether something counts as a “gain” or “loss” depends on your reference point. And your reference point is not fixed. It moves. After a winning streak, you raise your expectations. After losses, you are reluctant to lower them. So the same portfolio performance can feel like a win or a loss depending on where you mentally set the bar.
For investors, this matters a lot. The same economic situation looks different depending on when you bought in, what price you remember, or what return you expected. And loss aversion pushes you toward different decisions in each case.
Mental Accounting: Money in Invisible Boxes
Richard Thaler described mental accounting back in 1985. It is the way people put money into invisible categories. “This is my vacation fund.” “This is my emergency fund.” “This is my play money.”
Here is a good example from the research. Two groups of people were asked if they would buy a theater ticket. One group had just spent $50 on a basketball game. The other group had just paid a $50 parking ticket. Same $50 gone from both groups. But the basketball group was much less likely to buy the theater ticket. Why? Because in their mental ledger, the basketball game and the theater were in the same “entertainment” account. The budget felt used up. The parking fine went into a different mental box.
For investing, mental accounting leads to trouble. People sort assets into buckets for different goals (safety, growth, retirement) and then ignore how those buckets relate to each other. They miss the correlations between assets in different “accounts.” The result is an inefficient portfolio. One that looks organized but actually wastes money.
Myopic Loss Aversion: Stop Checking Your Portfolio
This one is a combination of loss aversion and short-term thinking. And it might be the most practical insight in the entire chapter.
Imagine two investors. Both hold the same portfolio. One checks it every day. The other checks it once every ten years.
On any given day, stocks go up or down roughly equally. So the daily checker sees losses about half the time. With loss aversion, every single loss feels terrible. After a while, stocks look like a horrible investment.
The ten-year checker? Over a decade, stocks almost always go up. Loss aversion barely kicks in. Same portfolio, completely different experience.
The book gives a concrete example. An investment with 50% chance of +20% and 50% chance of -10%. After one period, you face a loss 50% of the time. After two periods? Only 25% of the time (one scenario out of four is actually below your starting value).
So here is the takeaway: the more often you check your portfolio, the more losses you see, and the more tempted you are to abandon your strategy for no good reason. Financial advisors should talk about progress toward long-term goals, not last month’s performance.
Narrow Framing: Looking at Trees Instead of the Forest
Narrow framing is when investors evaluate each stock in isolation instead of looking at the overall portfolio. You obsess over one losing position while ignoring that the rest of your portfolio is doing fine.
Research shows that narrow framers hold fewer risky assets. Because when you look at each stock separately, you miss the diversification benefit. The risk of the whole portfolio is less than the sum of individual risks. But narrow framing makes you blind to that.
This is why good reporting matters. If your broker shows you each position separately with red and green arrows, you are basically being pushed toward narrow framing. A better approach shows overall portfolio performance relative to your goals.
The Disposition Effect: Selling Winners, Holding Losers
This is one of the most well-documented mistakes individual investors make. They sell stocks that went up and hold stocks that went down.
Why? Because of mental accounting. You have two invisible ledgers: “realized gains/losses” and “paper gains/losses.” When a stock is down, keeping it as a “paper loss” feels less painful than selling and making it a “real” loss. When a stock is up, selling feels great because you lock in a “real” win.
But here is the problem. This is backward-looking. You are making decisions to feel better about past choices, not to make the best choice going forward. A losing stock does not know you own it. If the reasons you bought it are no longer valid, sell it. If the reasons are still valid, keep it. That is the only question that matters.
Stop-loss orders can help with the symptom (holding losers too long), but the real cure is asking yourself: “Would I buy this stock today at this price?” If the answer is no, why are you still holding it?
The House-Money Effect
After a winning streak, people take bigger risks. Casino players know this feeling. “I’m playing with the house’s money now.”
But it is the same money. A dollar you won is worth exactly the same as a dollar you earned. The house-money effect makes investors take excessive risk after gains because the mental accounting separates “original money” from “winnings.” Dangerous thinking.
Affinity Bias and Home Bias
People buy stocks of companies they like personally. Green energy because they care about environment. A brand they use. A company with a familiar CEO.
The most common version is home bias. Swiss investors hold way more Swiss stocks than the 4% that Swiss stocks represent in global markets. American investors overweight American stocks. Russian investors overweight Russian stocks. Everyone thinks their home country is special.
Sometimes there are good reasons for home bias (currency risk, local knowledge). But often it is just comfort and familiarity dressed up as investment strategy.
Regret Aversion: The Fear of “I Knew It”
Regret is a powerful emotion. And it affects investing decisions in interesting ways.
The book uses a great example. George, John, and Paul all end up in bonds while the stock market goes up 30%. George switched from stocks to bonds based on his own analysis. John switched based on his advisor’s recommendation. Paul always held bonds and thought about switching to stocks but did not.
Who feels the worst? 70% of people say George. Only 12% say John. Nobody says Paul.
Why? Errors of action cause more regret than errors of inaction. And if someone else told you to do it (like John’s advisor), you can blame them. The book calls this a “psychological call option.” Having an advisor to blame protects your ego.
But here is the problem. Fear of regret keeps investors on the sidelines. After a loss, the fear of regretting another bad move keeps people out of the market, sometimes for years. They miss buying opportunities when prices are low.
The fix is to define your investment strategy in advance. Set rules for when you buy, when you sell, when you increase exposure. Follow the rules. Remove emotion from the equation.
Biases After Receiving Feedback
Once you make a decision and see the result, a whole new set of biases kicks in.
Hindsight Bias: “I Knew It All Along”
After something happens, your brain rewrites history. You remember yourself as having predicted the outcome, even when you did not. The 2008 crash? “Oh, I saw that coming.” No, you did not. Almost nobody did.
The worst part is that knowing about hindsight bias does not protect you from it. Your brain automatically integrates new information into your existing knowledge and makes it feel like you always knew.
The fix? Write things down. Document your predictions and your reasoning before the outcome is known. Then compare. You will be surprised how wrong you were.
Self-Attribution Bias: “I’m Smart When I Win, Unlucky When I Lose”
People take credit for good outcomes and blame others for bad ones. Your stock pick goes up? Brilliant analysis. It goes down? The market is irrational, or your advisor gave bad advice.
This is especially toxic in advisor-client relationships. Clients claim the winners and blame the advisor for the losers, even when the advisor recommended against the losing trade in the first place.
Solution: document every decision and who made it. Keep a paper trail.
Outcome Bias: Judging Decisions by Results
A good decision can have a bad outcome. A bad decision can have a good outcome. That is just probability.
But people judge the quality of decisions by what happened, not by the quality of reasoning behind them. If a fund manager has a good year, investors pile in. If the next year is bad, they pull out. This buy-high-sell-low cycle costs investors 4% to 6% per year according to a Dalbar study.
The fix: evaluate investment strategies on long-term track records and process quality, not on last quarter’s returns.
Herding: Are More Heads Smarter Than One?
You would think that groups make better decisions than individuals. More information, more perspectives, errors cancel out. Right?
Not really.
The research shows that group decision-making can actually amplify biases:
- Confirmation bias gets worse. If most group members already agree, the group seeks even more confirming information. Only balanced groups reduce this effect.
- Representativeness bias gets worse. Groups tend to rely on stereotypes even more than individuals when the information feels descriptive.
- Overconfidence does not improve. Even with a “devil’s advocate,” groups are just as overconfident as individuals. Worse, there is a group polarization effect where discussion pushes everyone toward more extreme positions. Cautious groups become more cautious. Risk-taking groups take even more risk.
An interesting finding about team composition: mixed-gender investment teams actually underperform both all-male and all-female teams. The reason is not what you would expect. Mixed teams (especially majority-male or balanced) take more risk than all-male teams, which leads to worse outcomes.
Fighting Your Biases: A Summary of Strategies
Here is the practical part. The book summarizes every bias with its consequence and a suggested fix. Let me give you the highlights:
For information biases (attention, confirmation, availability): decide in advance what information matters. Actively seek opinions that contradict yours. Compare overestimated dangers with actual evidence.
For judgment biases (representativeness, anchoring, overconfidence): use statistical methods. Think about arguments against your expected outcome. Keep track of your unsuccessful decisions, not just the wins.
For emotional biases (loss aversion, regret, disposition effect): adopt a broader time frame. Follow a pre-defined strategy. Use stop-loss orders as a safety net. Ask yourself “would I buy this today?” for every position you hold.
For feedback biases (hindsight, self-attribution, outcome): document everything. Write down your reasoning before you know the outcome. Analyze long-term data, not recent performance.
For group biases: make sure groups are balanced in opinion. Do not assume that more people in the room means better decisions.
My Take
This second half of Chapter 2 hits different than the first. Part 1 was about thinking errors. Part 2 is about emotions. And emotions are harder to fix.
You can learn statistics to fight representativeness bias. You can use checklists to fight anchoring. But loss aversion? Regret? That stuff is wired into your nervous system. You cannot just read about it and be cured.
The most practical advice from this chapter, the one thing I would tell everyone: stop checking your portfolio so often. Myopic loss aversion is real, it is measurable, and it costs you money. Check once a quarter at most. Set your strategy, follow it, and go live your life.
The next chapter covers cultural differences in investor behavior. Turns out, not all biases are universal. Where you grew up changes how you invest.
Previous: Behavioral Biases Part 1 - Heuristics and Judgment Traps