Try this before reading further. Choice one: a guaranteed gain of ₹5,000, or a coin toss that pays ₹10,000 or nothing. Most people take the sure ₹5,000. Choice two: a guaranteed loss of ₹5,000, or a coin toss that costs you ₹10,000 or nothing. Most people now take the coin toss. The expected value is identical in every option. The only thing that changed is whether the outcome is framed as a gain or a loss.

That flip is the core of prospect theory, Kahneman and Tversky's model of how people actually decide under uncertainty. It explains why you hold a falling stock for years, why you sell a rising one in weeks, and why so many traders who are down for the month reach for the cheapest, riskiest option on expiry day. I see the same flip on trading desks and in retail accounts. The size of the account does not change it.

2.25

times: how much more a loss weighs than an equal gain, median estimate

Tversky and Kahneman, 1992

1.5x

more readily winners were sold than losers in 10,000 brokerage accounts

Odean, Journal of Finance, 1998

59%

of index options turnover traded on expiry day in FY26

SEBI study, Aug 2026

Prospect Theory, the actual model

Prospect theory was published in 1979 and refined in 1992 as cumulative prospect theory. It replaced the textbook expected utility model with a description of real behaviour. Four features matter for investors.

  • Reference point: you judge outcomes as gains or losses against a reference, usually what you paid, not against your total wealth. A stock bought at ₹500 and now at ₹450 feels like a loss, even if ₹450 is a fair price.
  • Loss aversion: losses weigh more than gains. The 1992 paper estimated the ratio at 2.25. Losing ₹10,000 feels roughly as bad as gaining ₹22,500 feels good.
  • Diminishing sensitivity: the first ₹10,000 of gain or loss moves you more than the tenth. This makes people cautious with gains and willing to gamble with losses.
  • Probability weighting: people overweight small probabilities. A 2% chance of a big payout feels bigger than 2%. That is the psychology of a lottery ticket, and of a far out of the money option bought on expiry morning.
A ₹50,000 loss feels more than twice as big as a ₹50,000 gain

Felt value of a gain or loss, x axis in ₹ thousand. The curve is steeper on the loss side.

On the prospect theory value function a ₹50,000 gain scores about 31 and a ₹50,000 loss about minus 70. The curve bends at zero and is steeper for losses.

Tversky and Kahneman (1992), Journal of Risk and Uncertainty: v(x) = x^0.88 for gains, minus 2.25 times (minus x)^0.88 for losses. Illustration of the model, not a measurement of any one person.

Nobel Prize, Daniel Kahneman, 2002 (prospect theory)

How loss aversion destroys Indian investor returns

Loss aversion shows up in two habits that work against each other, and together they quietly rebuild your portfolio in the wrong shape.

Holding losers too long

Say you buy shares of a large private bank at ₹1,800 and they fall to ₹1,500. Selling now makes the ₹300 loss real. Holding keeps it on paper. So you hold. If the reason you bought has broken, the stock can keep falling, and the money stays locked in it instead of working somewhere else. Prospect theory predicts this: in the loss zone, people become risk seekers. They prefer the gamble of waiting over the certainty of booking the loss.

Selling winners too early

Now say you buy an IT services stock at ₹1,400 and it rises to ₹1,700. The urge to "lock it in" is strong, because in the gain zone people become risk averse. You sell. If the business keeps compounding, you have kept the small win and handed the big one to someone else.

Do both for a few years and the portfolio fills up with the stocks you could not bear to sell and empties of the ones you could not wait to sell. Odean's 1998 study of 10,000 brokerage accounts found exactly this: investors realised gains about 1.5 times as readily as losses, and the winners they sold went on to beat the losers they kept by about 3.4 percentage points over the next year. Module 8.5 covers that study in detail.

The break even trap

Loss aversion has a mathematical accomplice. A fall needs a bigger rise to recover, because the rise starts from a smaller base. The table uses real 2026 numbers.

FallRise needed to get backIndian example
10%11.1%A routine correction
15.6%18.4%Nifty 50, 26,328.55 (2 Jan 2026) to 22,231.80 (8 Oct 2026)
26.1%35.4%Nifty Smallcap 250, 18,623.15 (23 Sep 2024, its record) to 13,755.90 (3 Mar 2025)
50%100%A stock that halves

The Smallcap 250 has nearly made that 35.4% back. It closed at 18,527.20 on 8 September 2026, 34.7% above the low and 0.5% short of the record, though on 12 October 2026 it was still 4.6% below. Investors who sold in March 2025 to stop the pain locked in the 26.1% and missed the 34.7%.

The trap is the urge to get back to even fast. Thaler and Johnson's 1990 experiments found that people who have lost money often take bets they would normally refuse, if the bet offers a chance to break even. In Indian markets that urge has a favourite instrument: the short dated option. SEBI's August 2026 study found that 59% of index options turnover in FY26 happened on expiry day itself, and 97% within a week of expiry. Options produced 92% of individual traders' aggregate losses, and 87.7% of individual options traders lost money in FY26, against 66.0% in futures.

Most index options trading happens on expiry day

Share of index options turnover by time left to expiry, FY26 (FY25 in brackets).

  1. Expiry day (70%)59%
  2. Within 1 day (80%)75%
  3. Within 7 days (98%)97%

SEBI, Profitability of Individual Traders in the Equity Derivatives Segment, FY25 to FY26, Aug 2026. Options were 92% of individual losses in FY26.

SEBI, Profitability of Individual Traders in the Equity Derivatives Segment, FY25 to FY26, Aug 2026

The reference point problem, why purchase price is a trap

For most investors the reference point is the purchase price of each holding. From a finance point of view that number is irrelevant. The stock does not know what you paid. The market does not care. The only live question is whether this is the best use of this money from today's price.

Yet the purchase price colours everything. A stock bought at ₹1,000, now at ₹600, with a broken business, becomes "a temporary loss to ride out". A stock bought at ₹500, now at ₹600, with earnings still rising, becomes "a profit to book". Rationally the two decisions should be made on the same test. Emotionally they are made on opposite tests.

A simple reset I use: cover the buy price column. Look at each holding at today's price and ask one question. If I had this money in cash today, would I buy this, at this price, in this size? If the answer is no, the purchase price is not a reason to keep it.

The mental accounting trap

Mental accounting is Thaler's term for treating money differently depending on where it came from or which "account" you file it in. With loss aversion it causes three classic errors.

  • House money: treating profits as "not really mine" and taking bigger risks with them. A rupee of profit buys exactly as much as a rupee of salary.
  • The temporary account: parking a losing stock in a mental drawer labelled "long term" so you never have to look at it.
  • Refusing tax help: not selling a loser even when booking the loss would cut your tax, because selling makes the loss "real".

Worked example: what refusing to book a loss costs

In FY27 you sell a stock held for eight months at a gain of ₹80,000. Short term capital gains on listed equity are taxed at 20%, so the tax is ₹16,000 before cess. You also hold another stock bought six months ago, now ₹50,000 under water, and you no longer believe in it.

Hold the loserSell the loser before 31 March
Short term gain₹80,000₹80,000
Short term loss set off₹0₹50,000
Taxable short term gain₹80,000₹30,000
Tax at 20% (before cess)₹16,000₹6,000

Result: booking a loss you would have exited anyway saves ₹10,000 of tax in this example. Loss aversion says no. Arithmetic says yes. Long term gains above ₹1.25 lakh a year are taxed at 12.5%; Path 11 covers the set off rules in full.

Income Tax Department, Help for individual taxpayers, returns and capital gains

Loss aversion in Indian retail data

SEBI's F&O studies give an unusually clear view of the pattern. In FY26 the average loss among individual loss makers was ₹1.47 lakh, while the average profit among profit makers was ₹1.22 lakh. Losses were 21% larger than profits. That is what a book looks like when small gains get taken quickly and losing positions are held, rolled or doubled.

The same study shows the asymmetry in futures. Individuals made money in futures in rising quarters, ₹3,741 crore in Q1 FY25 when the Nifty rose 7%. They lost far more in falling quarters: ₹8,081 crore in Q4 FY26 when the Nifty fell about 15%. SEBI notes that losses in market declines were substantially larger than profits in comparable rallies.

How big a gain cancels this loss, and how far back is even?

Gain that feels equal, simple ratio ₹22,500
With diminishing sensitivity ₹25,130
Rise needed to get back to the peak 18.5%

Tversky and Kahneman (1992) median parameters, 2.25 and 0.88. Recovery = 1 / (1 minus fall) minus 1. The Nifty 50 fell 15.6% from 2 Jan to 8 Oct 2026 (NSE).

Two field tested defences

Reading about loss aversion does not cure it. Two structural fixes have research behind them.

Look less often. Benartzi and Thaler's 1995 paper on myopic loss aversion showed why. Over short windows, an equity portfolio shows a loss on a large share of days, close to half. Over a year, far fewer years are negative; over five or ten years, fewer still. Each look at a red number is a small dose of loss pain. Investors who look daily feel many more losses than investors who look quarterly, for the same underlying return, and experiments show they then hold less equity. In the 24 months to September 2026, a weak stretch for Indian large caps, the Nifty 50 closed lower on 252 of 487 trading days. A daily checker felt every one of them.

Decide before the moment. Write the rule when no position is live: "I exit when the reason I bought is no longer true", or "I rebalance on the first Monday of every quarter whatever has moved". The decision gets made calmly. The execution is mechanical. That is the whole premise of systematic investing, applied to a behavioural problem.

In the moment

The market decides your mood

  • You see a red number and feel the loss
  • You wait for break even
  • You add to the loser to lower the average
Decided in advance

The rule decides, the mood watches

  • Exit rule written before entry
  • Review date fixed in the calendar
  • Position size capped before you feel sure
Tap a side or swipe across the card.

Common mistakes

Mistake: averaging down without a reason. Adding to a loser to lower the average price feels like action, but it only moves your reference point. Add only if you would buy the stock fresh at today's price, in that size.

  • Waiting for break even. The market has no memory of your entry. "I will sell when it gets back to my price" is a rule written by loss aversion.
  • Treating a stop as a defeat. A pre set exit is risk control, not a confession.
  • Swapping a loss for an option bet. The urge to win it back fast is strongest right after a loss. SEBI's FY26 numbers show how that usually ends.
  • Ignoring tax set off. Booking a loss you would exit anyway can lower your tax in the same financial year.

MythIt is not a loss until I sell.

FactYour wealth is what the holding is worth today. Selling only changes the tax and frees the money. In Odean's 1998 data, losers kept trailed winners sold by about 3.4 points the next year.

How this shows up in RupeeCase

RupeeCase index algos exit a stock when the rule says it no longer qualifies, for example when its momentum or quality score drops below the cut off, and never because of the price someone bought it at. The algo has no entry price to anchor to. You can see every model exit, winners and losers alike, on the rebalance history page, and the full lineup on strategies. Figures there are model, back tested.

Questions readers ask

Is loss aversion always irrational?

No. If a loss would damage your life, such as money needed for a home loan payment, caution is sensible. The bias is applying that same fear to small, survivable swings in a long term portfolio, where it makes you hold the wrong stocks and sell the right ones.

Is 2.25 a fixed number for everyone?

No. It is a median estimate from experiments. Later studies find a wide spread across people and situations, often between 1.5 and 2.5. The direction, losses weigh more than gains, is the robust finding.

Does a stop loss solve loss aversion?

It solves the exit decision if you set it in advance and do not move it. It does not solve the urge to re enter immediately or to cancel the stop when price gets close. Write the stop and the re entry rule at the same time.