Behavioral Finance & Microstructure
Misbehaving: The Making of Behavioral Economics
Thaler's account of how economics learned that people are not the calculating machines its models assumed. For an investor the payoff is concrete: the money in your account is one pot, but your head keeps it in many jars, and that habit shows up in which positions you sell.
The big picture
The book is part memoir, part history of a field. Thaler walks through the small anomalies he collected as a young economist — people valuing an item more once they own it, treating a windfall differently from a salary, finishing a bad meal because it was paid for — and how they grew into behavioral economics, the study of how real people deviate from the textbook rational agent in predictable directions. The core bet: factors that standard theory calls irrelevant (how a choice is framed, which account the money sits in, what the default option is) move real decisions, and they do so consistently enough to be measured.
Why it matters for a portfolio: the same habits operate on a brokerage statement. Investors split one book into mental accounts — the safe money, the fun money, the position bought at a higher price — and then judge each jar alone. That is how a portfolio ends up selling its winners to lock in a good feeling while holding its losers to avoid admitting one. The fix is not more willpower; it is looking at the whole book as one account, on your own numbers.
The 4 strategic pillars
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Mental accounting
People sort money into separate budgets by source and purpose, even though a euro is a euro wherever it sits.
In a portfolio this shows up as buckets with their own rules — a gain in the speculative bucket gets spent on more risk, a loss in the core bucket gets frozen. Adding the buckets back into one view is the first correction; the pack's accounts sheet does exactly that.
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Endowment, sunk costs and the reference price
Owning something raises its value in the owner's eyes, and money already spent keeps steering choices it should no longer affect.
The purchase price becomes the reference point every later decision is measured against. Losses below it are felt more strongly than equal gains above it (loss aversion), so the position is held until it gets back to even. The disposition gap — the share of gains realized minus the share of losses realized — makes the habit measurable in a trade log.
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Myopic loss aversion and the markets
The more often an investor checks results, the more losses they see, and the less risk they are willing to hold.
Thaler and Benartzi used this pairing of loss aversion with short evaluation periods to explain why stocks have paid so much more than bonds historically (the equity premium puzzle). The same book covers markets that misprice in plain sight, such as closed-end funds trading away from the value of what they hold. The practical lever is the evaluation period: review less often, and on the whole book.
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Nudges and defaults
Because the way a choice is presented changes the outcome, the presentation can be designed on purpose.
Thaler's retirement-savings work showed that automatic enrolment and scheduled contribution increases outperform good intentions. Applied to one's own process: make the review the default (a fixed monthly date, a pre-written sell rule) instead of a decision taken in the moment.
What a Closelooknet reader does with it
The working use is an audit of your own trade log. Count, on each day you sold something, how many of your winners and losers you could have sold and how many you did. If you realize gains at a clearly higher rate than losses, the reference price is running the book. Then add up the mental buckets you actually keep — core, satellite, the ones you only look at when they are up — and compare the combined picture with how you judge each part. The mistake it prevents is the quiet one: a portfolio whose winners keep getting trimmed and whose losers keep getting a second chance, until the book is mostly the positions you did not want to face.
The bridge to the Closelooknet approach
Thaler builds on the psychology that Thinking, Fast and Slow maps — read the two side by side: Kahneman explains where the biased impulse comes from, Thaler shows what it does to money and markets. Closelooknet's investment diary publishes its own fills in the trade log and runs its books as named portfolios, which is mental accounting done in the open: five jars, each with a mandate, reviewed on a fixed weekly rhythm. The pack's tracker is the same audit for your own records — disposition gap on your sells, and your buckets added back into one book. For the crowd-level version of the same emotions, Money Temperature measures when the market as a whole is running hot or cold.
Action-Kit — from theory to practice
Tooling & data
| What you need | Where to get it | Cost |
|---|---|---|
| A broker trade-history export (CSV) The raw material for the disposition audit — every buy and sell with date and price | Your own broker's transactions or tax report export Most brokers offer a CSV or Excel export of realized trades; the pack reads a simple five-column version. | Free |
| Portfolio tracker with a combined view Add all accounts and buckets back into one book to see total exposure instead of jar-by-jar results | Sharesight or Portfolio Performance (open source) Portfolio Performance is free desktop software; Sharesight has a free tier with a holding limit and paid plans above it. | Freemium |
| Spreadsheet Run the pack's tracker and keep your own reference prices next to the fills | Microsoft Excel, LibreOffice Calc or Google Sheets The pack uses only standard functions, so LibreOffice and Google Sheets work. | Freemium |
The formulas
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Disposition gap (Odean)
PGR = realized gains / (realized gains + paper gains); PLR = realized losses / (realized losses + paper losses); gap = PGR − PLR- Realized gains / losses — positions sold above / below their reference price, counted on each day you sold something
- Paper gains / losses — positions you held on those same days that were above / below their reference price
A clearly positive gap means gains are being realized faster than losses. Odean's 1998 study of discount-broker accounts found it in aggregate; the pack computes it on your own log.
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Prospect-theory value function
v(x) = x^α for x ≥ 0; v(x) = −λ × (−x)^β for x < 0- x — gain or loss relative to the reference price
- α, β — curvature, about 0.88 in Tversky and Kahneman's 1992 estimates
- λ — loss-aversion coefficient, about 2.25 in the same estimates
The kink at zero is the whole story: a loss of a given size feels roughly twice as heavy as an equal gain.
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Myopic loss aversion (evaluation-period effect)
P(loss in one period) = Φ(−μT / (σ√T)) = Φ(−(μ/σ) × √T)- μ, σ — annual expected return and volatility of the portfolio
- T — evaluation period in years (1/252 daily, 1/12 monthly, 1 yearly)
- Φ — standard normal distribution function
A normal approximation. The shorter the period, the closer the chance of seeing a loss gets to a coin flip — and with λ above 2, frequent checking makes the same asset feel worse.
Applied Pack · free members
Thaler Applied Pack
A mental-accounting tracker for your own trade log: how fast you realize gains versus losses, and what your buckets look like added back into one book.
- Thaler_Mental_Accounting_Tracker.xlsx — READ ME, a trade-log sheet with live formulas for realized and paper gains and losses, PGR, PLR and the disposition gap, and a Check Your Accounts sheet that sums holdings by your own mental buckets against one combined portfolio view (EXAMPLE rows included)
- thaler_disposition.py — stdlib-only CLI: reads a CSV trade log and prints PGR, PLR, the disposition gap and a bucket-versus-one-portfolio view
- trades_sample.csv and holdings_sample.csv — EXAMPLE_ placeholder data in the expected format
- README.txt — inputs, how to run, and the educational-use disclaimer
Pack security
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Educational templates — a research diary companion, not investment advice.
Closelooknet publishes a market diary, not investment advice. This condensed read restates the book's ideas in our own words for education — for the author's full argument, go to the source.