Fin Maverick
Foundations VocabularyAccounting & ReportingEconomics & MacroQuant Methods & ProgrammingBusiness & Company AnalysisCorporate Finance & ValuationBehavioural Finance
Banking & Market InfrastructureFixed Income & RatesDerivatives & Structured ProductsPublic EquitiesTransactions & DealsPortfolio ConstructionFunds & AMCs
Private Markets & AlternativesRisk, Treasury & ControlAI & Digital FinanceStochastic Calculus & PricingWealth & Personal FinanceIndian Markets & RegulationProfessional Practice
CalculatorComparison
Frameworks
Explore Bootcamps
Equity ResearchPortfolio ManagementMutual Fund MasteryFinancial LiteracyInvestment Banking Analyst
Private Equity AnalystHedge Funds AnalystBreaking Into VCBreaking Into QuantsAI For Finance
Financial Analyst ProgramRisk Management ProgramPrivate Wealth ManagementDebt Capital MarketsDerivatives Foundation
Explore Internships
Equity Research InternMutual Fund Intern
Portfolio Management InternFinancial Literacy Intern
Explore Micro Courses

Equity Research6

Writing an Investment ThesisBuilding a Discounted Cash FlowReading an Annual Report FastReading a Sector Before a CompanySpotting Quality of Earnings Red FlagsBuilding a Revenue Forecast From Drivers

Portfolio Management3

Rebalancing: When, Why and What It CostsStrategic and Tactical Asset AllocationMeasuring Risk in a Portfolio

Mutual Fund Mastery3

Comparing Funds Without Being FooledHow a NAV Is Struck and Which Day You GetReading a Fund Factsheet Properly

Derivatives Unlocked4

Hedging a Real ExposureThe Greeks, PracticallyFutures, the Basis and What Moves ItReading an Option Payoff

AI For Finance2

Retrieval and Grounding for FinanceDocument Extraction in Finance

Breaking Into Quants4

Backtesting a StrategyHypothesis TestingCleaning Financial DataRegression for Finance

Breaking Into VC3

Sizing a MarketReading a Term Sheet as a FounderHow a Venture Round Actually Works

Financial Analyst Program4

Common Size and Trend AnalysisReading a Cash Flow StatementRatio Analysis That Says SomethingBuilding a Working Capital Schedule

Risk Management Program2

Credit Exposure and How It Is ReducedValue at Risk and What It Hides

Investment Banking Analyst3

Precedent Transactions and Why They DifferReading a Term Sheet StructurallyBuilding a Comparable Companies Table

Private Wealth Management3

Tax Aware Portfolio DecisionsBuilding a Client Risk ProfileGoal Based Planning Arithmetic

Debt Capital Markets3

Analysing an Issuer's CreditDuration and What It Does Not Tell YouBond Pricing and Yield Mechanics

Private Equity Analyst2

Fund Waterfalls and CarryThe LBO in Structure

Hedge Funds Analyst2

Short Selling MechanicsLong Short Mechanics
Courses
Explore Career Roadmaps
Investment Banking AnalystEquity Research AnalystVC AnalystPrivate Equity AnalystHedge Funds Analyst
Quant AnalystAI For FinanceFinancial Analyst ProgramPrivate Wealth ManagementDebt Capital Markets
Risk Management ProgramDerivatives FoundationPortfolio ManagementMutual Fund Mastery
PartnershipsShowdown
Log inSign up
Behavioural Finance & Investor Decision-Making
1Foundations
The Rational InvestorJudgment Under UncertaintyPreferencesBehavioural FinanceInvestor and Market BehaviourFinancial Well-BeingBounded RationalityHeuristics and Biases
2Cognitive Biases, Emotion and Attention
Limited AttentionRepresentativenessThe Affect HeuristicAnchoring and AdjustmentEmotion and Decision QualityOverconfidence and OptimismAmbiguity and Complexity AversionAvailability and SalienceHome Bias, Local Bias…FramingThe Halo EffectHindsight BiasThe Narrative FallacyPresent Bias and Hyperbolic DiscountingBase-Rate NeglectStatus Quo Bias and the Default Effect
3Preferences and Prospect Theory
Prospect TheoryRegretThe Endowment EffectMental AccountingThe Sunk Cost FallacyLoss AversionRisk Seeking in Losses
4Social Behaviour
HerdingNarrative EconomicsFear of Missing OutGroupthinkSocial Proof
5Investment and Trading Behaviour
Excess TradingNaive DiversificationThe Disposition EffectLottery PreferencesNoise TradersPortfolio InertiaRecency Bias
6Markets and Anomalies
Mania, Panic and CapitulationMarket EfficiencyEfficient Market Hypothesis vs…Speculative BubblesReflexivityInvestor SentimentMarket AnomaliesShort-Sale ConstraintsPrice DiscoveryLimits to Arbitrage
7Decision, Research and Debiasing
The Decision JournalDebiasingChoice Architecture, Defaults and…The Pre-Mortem and Process QualityDecision Quality
8Advice, Conduct and Communication
Communication ConductSuitability and AppropriatenessChoice OverloadComplaint BehaviourRisk DisclosureVulnerable Investors

Limited Attention: Buying What You Happened to Notice

Attention is the input every decision needs and nobody has enough of. Attention does not change what a person prefers. Attention changes what ever gets considered. Considering comes earlier than comparing, and it matters more. Something that never reaches notice is not rejected on its merits. The unnoticed thing was never a candidate at all, and a filter on candidates is a quieter and much larger effect than any preference.

Almost everything ever written about deciding well starts at the same moment: the options are on the table, and now a choice has to be made between them. Weighing this against that, scoring them, ranking them, picking. Comparing is a useful thing to teach and it is not where most of the damage happens. The options got onto the table by some process, and that process is doing more work than the comparison everybody argues about. Every individual bias arrives only after that earlier step has already run. The earlier step therefore comes first.

The reason the filter goes first is structural rather than rhetorical. A preference can be argued with. Two things can be put beside each other, a person can be shown that one of them was scored wrongly, and a mind can change on the spot. An option that never reached a person offers nothing to argue about, and so cannot be argued with. The filter is never experienced as running. A shortlist is experienced instead, and it feels like it arrived on its own.

Why is attention the scarcest input to a decision?

AttentionThe limited capacity to take in and hold information while deciding. feels free. Money is obviously limited, time is obviously limited, and both can be watched running out. Attention is the one input that is just as limited and has no meter on it, and having no meter is exactly why nobody budgets for it. Daniel Kahneman set this out formally in Attention and Effort in 1973, treating attention not as a switch that is on or off but as a limited pool that gets allocated across whatever is competing for it. More to one thing means less to something else, whether or not the trade was noticed being made.

Take it out of finance first. A person walks into a vegetable market with forty stalls in it. The shopper will not compare forty stalls. The shopper walks down one side, looks properly at four or five, and buys. Ask them afterwards why they did not buy from the stall at the far end and they will not say it was worse. The answer will be that they did not get to it. The thirty-five stalls they never reached were not judged and found wanting. None of the thirty-five was ever in the running. The shopper walked out feeling they had chosen carefully, and within the five stalls they did reach, they had.

Forty stalls in the market. Five of them got looked at properly. Walking down one side is a filter, and it ran before any stall was compared. reached, 5 stalls never reached, 35 12.5% of the market was looked at, and 87.5 per cent of it was never in the running 5 divided by 40 is 12.5 per cent. The 35 unshaded stalls were not judged and found wanting. The shopper walked out feeling they had chosen carefully, and within the five they had.
Five stalls out of forty is 12.5 per cent, and the thirty-five never reached were never judged at all.

Herbert Simon made the same point about decisions generally in the Quarterly Journal of Economics in 1955, arguing that a real decider works with a small, manageable slice of the world rather than the whole of it. The whole of it will not fit. Scarcity of attention is not a flaw in a particular person; it is a fact about any decider with a finite head and a world that is larger than it. The difference between people is not how much attention they have. The difference is what gets in front of them, and who decided that.

Scarcity of attention matters more the larger the world of options is. A person choosing between two schools for a child can genuinely look at both. A person choosing where to put a monthly saving is facing something in the thousands, and no amount of effort closes that gap. So the interesting question stops being how carefully somebody compared, and becomes what reached them in the first place.

The same head, two sizes of world. FIVE OPTIONS EXAMINED This capacity is the same in both rows below. It is the one thing effort cannot raise. A WORLD OF 2 two schools for a child 100% of the world got examined A WORLD OF 2,000 where a monthly saving goes 0.25% of the world got examined 5 of 2 is the whole of it. 5 of 2,000 is 0.25 per cent, a share 400 times smaller. The 2,000 is taken for the arithmetic only and the boxes are not drawn to scale. Invented figures.
One fixed capacity covers all of a two option world and a quarter of one per cent of a two thousand option one.

What is a consideration set, and what decides what gets into it?

The consideration setThe options actually on the table when a choice is made. is the short list of options that are actually on the table when a choice gets made. The consideration set sits between two other things. Behind it is the candidate setEverything that could in principle have been chosen at that moment., meaning everything that could in principle have been chosen at that moment. In front of it is the single thing that was chosen. Three stages, and the arithmetic of a decision is usually taught as though the first two did not exist.

Think about a household choosing a caterer for a wedding. There are perhaps two hundred caterers who could do the job. The household will consider four. The four arrived because a cousin mentioned one, a hall recommended two, and one had a board outside a shop the household walks past. Nobody in that household believes they surveyed the market. Rejecting requires having looked, so the household does not experience the other one hundred and ninety-six as rejected either. The four were selected by a process that involved no comparison at all, and the comparison everybody remembers making happened entirely inside that four.

Two hundred caterers could have done the job. Four were considered. The four shaded cells arrived from a cousin, a hall and a board outside a shop. 4 divided by 200 is 2.0 per cent, and the comparison everybody remembers happened inside those four. The other 196 were not rejected, because rejecting something requires having looked at it. Invented figures, and nothing here describes any real household or any real caterer.
Four caterers out of two hundred reached the table, and the other one hundred ninety six were never compared.
Four stages. Almost all teaching about deciding starts at the third. 1 THE ELIGIBLE LIST everything that could in principle have been chosen 2 WHAT REACHED NOTICE the small part that was mentioned, seen or talked about 3 THE CONSIDERATION SET the options actually on the table when the choice was made 4 WHAT WAS BOUGHT one line in the decision log, with a date on it THE FILTER, AND NOBODY WATCHES IT RUN THE COMPARISON, AND EVERYBODY ARGUES Something that never leaves the first box is not rejected. It is never compared with anything. The measured 11.0 per cent below is how much of box one reached box two in a week. Invented figures.
The filter between the eligible list and what reached notice runs before any comparison, so it stays invisible to anybody watching the comparison and arguing about it.
Try it out

Does attention change what a person prefers, or what a person considers?

Financial Literacy Bootcamp — Fin Maverick

What is Attention Bias, and how is it not the same thing as a preference?

Attention biasA filter that decides what is considered, before anything is compared. is the name for a systematic tilt in what reaches the consideration set. A tilt in how the options are scored once they are there would be a preference. Attention bias is instead a tilt in which ones arrive at all, and a tilt in which ones arrive is a filterAnything that removes options before they are judged on their merits. rather than a ranking. The difference between those two words is the whole of the subject.

One clean test tells a filter and a preference apart, and the test is worth holding on to. Everything a person values is held completely fixed: their tolerance for risk, their view of the future and their sense of what a good holding looks like all stay as they were. Only what happens to reach them in a given week changes, and what they buy is then observed. No preference was touched, so if the choice moves, a preference did not cause the move. The set the preference was applied to is what moved, and a moving set is attention bias in one experiment.

The clean test: change nothing about the person, change only the week. HELD COMPLETELY FIXED IN BOTH WEEKS BELOW tolerance for risk, view of the future, what a good holding looks like WEEK ONE 11.0 per cent of the list reached her that week THREE NAMES ARRIVED what got bought: one of those three WEEK TWO a different 11.0 per cent reached her that week THREE OTHER NAMES ARRIVED what got bought: one of those three No preference was touched, so no preference can have caused the purchase to move. What moved was the set the preference got applied to. Invented figures throughout.
Holding every preference fixed and changing only what arrived that week is enough to move what gets bought.

Attention bias is hard to spot from the inside. Asked why they bought a thing, somebody will give a genuine, coherent answer about its merits. The answer is usually true. The answer is simply about stage three of the four stages above, and a question about stage two would have caught the effect. Nobody can report on a filter they did not watch operating, and this is not a failure of honesty. The failure is one of access.

A filter changes what is there. A ranking changes only the order. A FILTER, RUNNING BEFORE ANY SCORING 11 of every 100 admitted, at the base rate of notice of 11.0 per cent A RANKING, RUNNING AFTER IT first third second first third fourth fourth second 4 went in and 4 came out The filter removed 89 of every 100 before anything was scored against anything else. The ranking removed nothing at all. Only one of these two is a preference. Invented figures.
A filter admitting 11.0 per cent removes 89 of every 100 before scoring, while a ranking leaves all four standing.

Attention bias is worth defining by what it is not. Attention bias is not a claim that noticed things are worse than unnoticed things. Nor is it a claim about anybody in particular. Cutting thousands down to a handful is a job that has to be done by something, as the section below on when the shortcut is correct sets out, so attention bias is not a criticism of shortcuts in general.

Try it out

What is a consideration set?

Portfolio Management Bootcamp — Fin Maverick

What does Attention-Driven Buying look like in one line of a log?

Attention-Driven Buying is the name for what happens when notice does the selecting: the option that reached a person becomes the option that gets bought, without any step in between that examined the alternatives. Brad Barber and Terrance Odean introduced it in finance in All That Glitters, published in the Review of Financial Studies in 2008, where they set out both the buying pattern and the asymmetry between buying and selling that is taken apart below.

The Palash decision log, an invented record of 240 decisions taken by 60 investors over eight quarters, carries one line that shows the mechanism with unusual clarity. On 19 February a television segment named Suvarna Chemicals Limited. The same evening, Meera Sundaram added Rs 1,00,000/- to the holding, taking its cost from Rs 3,00,000/- to Rs 4,00,000/- and her total cost from Rs 12,00,000/- to Rs 13,00,000/-. She already held it, so this was not a discovery. She simply put more money into the one of her four holdings that had been in front of her that evening.

One dated line, and everything the mechanism needs. PALASH DECISION LOG, ONE EXTRACT, INVENTED THROUGHOUT DATE 19 February WHAT REACHED NOTICE a television segment WHAT WAS ADDED Rs 1,00,000/- COST BEFORE Rs 3,00,000/- COST AFTER Rs 4,00,000/- WHOLE COST AFTER Rs 13,00,000/- WHAT CHANGED ABOUT THE HOLDING ITSELF nothing at all, on that day or the one before Rs 3,00,000/- plus Rs 1,00,000/- is Rs 4,00,000/-, and the whole cost moves to Rs 13,00,000/-. What moved was not the holding. It was the fact that this one, out of four, was in front of her.
A single dated log entry carries the whole mechanism, because money moved on an evening when nothing inside the holding itself had changed.

Notice how little this needs. No claim that the segment was wrong, no claim that Suvarna Chemicals Limited was a poor thing to hold, and no claim about what happened to its price afterwards. The mechanism is complete once it is observed that money moved on a day when the only thing that changed was what was in front of her. One dated line is enough to show the mechanism for that reason, and a hundred lines would be needed to measure it.

What one evening did to the shape of the whole cost. Both bars are drawn as the whole cost, so they are the same length. BEFORE Rs 12,00,000/- 25.0% Rs 3,00,000/- the other three holdings, Rs 9,00,000/- AFTER Rs 13,00,000/- 30.8% Rs 4,00,000/- the other three, unchanged at Rs 9,00,000/- 3,00,000 of 12,00,000 is 25.0 per cent. 4,00,000 of 13,00,000 is 30.8 per cent, a rise of 5.8 points. Nothing about any of the four changed. Only what was in front of her that evening did. Invented figures.
One evening moved this holding from 25.0 per cent of the whole recorded cost to 30.8 per cent of it.
Try it out

On 19 February a segment named Suvarna Chemicals Limited and Rs 1,00,000/- was added the same evening. What changed about the holding itself?

How large is the effect once it is measured against the base rate?

One evening is an anecdote. A claim rather than a story becomes possible because the same log records what happened across all 240 decisions, and a share only means something when it is set beside the share to be expected anyway. The share to be expected anyway is the base rate of noticeHow much of the available list gets mentioned at all in a period., and skipping it is the single commonest way this whole subject gets reported badly.

Start with the composition. The 240 logged decisions break into 96 buys, 84 sells, 36 switches and 24 pauses of a standing instruction, and those four sum back to 240 with nothing left over. Of the 96 buys, 41 followed a media mention within three days. Work that out rather than reading it: 41 divided by 96 is 42.7 per cent.

The counting rule, drawn as a window. A buy counts as following a mention only if it falls within three days of it. COUNTED AS FOLLOWING A MENTION 41 of the 96 buys fell in here NOT COUNTED 55 buys 0 24 hours 48 hours 72 hours 96 hours the 19 February buy, taken the same evening Separately, 71 of the 240 decisions, being 29.6 per cent, fell within 48 hours of a news item. Three days is the rule that produced the count of 41. Invented figures throughout.
A buy counts only inside a three day window, and this one fell on the same evening as the mention.
240 logged decisions, and then the 96 buys opened up. 96 BUYS 84 SELLS 36 SWITCHES 24 PAUSES 41 OF 96 FOLLOWED A MENTION within three days, being 42.7 per cent 55 DID NOT being 57.3 per cent of the buys 96 plus 84 plus 36 plus 24 is 240, and the four kinds of decision do not overlap. Every figure here belongs to the invented Palash decision log and describes no real market.
Splitting the 240 decisions and then opening the 96 buys shows that 41 of them followed a mention within three days.

Now the number that turns this into a measurement. Across the same period, 11.0 per cent of the eligible list was mentioned at all in a given week. If notice had nothing to do with buying, buys would be drawn from the mentioned part of the list roughly in proportion to its size, so about 11.0 per cent of 96. Working that out gives 10.6 buys, call it eleven. Forty-one is what actually happened. The finding is not that 42.7 per cent is a large number; it is that 42.7 per cent sits nearly four times above the 11.0 per cent that proportion alone would give.

The stepThe workingValue
Buys in the log60 investors over eight quarters, out of 240 decisions in all96
Buys that followed a media mention within three dayscounted line by line from the log41
Share of buys that followed a mention41 divided by 9642.7 per cent
Share of the eligible list mentioned in a weekthe base rate of notice, measured separately11.0 per cent
Buys expected to follow a mention if notice did no selecting11.0 per cent of 96about 11
The gap that has to be explained41 against about 11, being 42.7 per cent against 11.0 per centabout 30 buys
The distance between these two numbers is the whole finding. 0 10 20 30 40 50 per cent 11.0 PER CENT 42.7 PER CENT of the eligible list was mentioned in the week of the 96 buys followed a mention within three days 31.7 POINTS OF DIFFERENCE nearly four times the base rate of notice On proportion alone about 11 of the 96 buys would have followed a mention. 41 did. Invented figures.
Setting the share of buys that followed a mention against the base rate of notice turns an impression into a measured gap of 31.7 points.
Try it out

11.0 per cent of the eligible list was mentioned in a week and 42.7 per cent of buys followed a mention. What would the second figure be if notice did no selecting at all?

What does the whole range between no effect and total capture look like?

The 42.7 per cent reads better as a point on a scale than as a fact on its own. Put the strength of the effect on one axis, running from zero, where notice does no selecting whatever, to one, where nothing unmentioned is ever bought. At zero strength the mentioned part still supplies buys in proportion to its own size, so the share of buys coming from the mentioned part of the list runs from 11.0 per cent up to 100 per cent in a straight line.

The floor of that scale is 11.0 per cent rather than zero, and the control below is built around that floor. A reader who expects zero at zero has quietly assumed that the mentioned part of the list would otherwise be bought by nobody. A base rate does not mean that. The answer is worth predicting before the control is moved.

Try it out

Before the control is moved: at zero attention effect, what share of buys comes from the mentioned part of the list?

Play with it

Move the strength of the effect and watch where the log sits

One variable moves: how strongly notice does the selecting, from 0 to 1. Everything else is held still. The mentioned part of the eligible list stays at 11.0 per cent, the number of buys stays at 96, and the share of buys is 11.0 plus 89.0 times the strength. The log itself measured 41 of 96, being 42.7 per cent. A share of 42.7 per cent corresponds to a strength of 0.356, rounding to 0.36.

0, notice does no selecting0.3561, nothing unmentioned is bought
Share of buys drawn from the mentioned part of the list. 0 25 50 75 100 BASE RATE OF NOTICE, 11.0 PER CENT WHAT THE LOG MEASURED, 42.7 PER CENT 42.7 per cent 0 0.25 0.50 0.75 1.00 how strongly notice does the selecting
Strength, what moves
0.356
Share of buys from the mentioned part
42.7 per cent
Held constant, base rate of notice
11.0 per cent
Buys out of 96
41

At a strength of 0.356 the mentioned part of the list supplies 42.7 per cent of buys, which is 41 of the 96 in the log, against 11.0 per cent if notice did no selecting at all.

Educational illustration. The eligible list is assumed fixed over the week and every mention is treated as equally likely to reach any given person. Both are simplifications and neither holds exactly.
Three readings on one scale, and the floor is not zero. 11.0% strength 0, no selecting 42.7% strength 0.356, the log 100% strength 1, total capture A reading of 11.0 per cent means notice did no selecting, not that nothing mentioned was bought. The log sits about a third of the way up a scale whose bottom is already 11.0 per cent. Invented.
Reading the log at 42.7 per cent against a floor of 11.0 per cent rather than zero is what keeps the measurement honest.
Private Wealth Management Bootcamp — Fin Maverick

Why does the buying side show this and the selling side barely at all?

Here is where most readers form the wrong idea, and it is worth slowing down. The natural explanation for a buying effect is enthusiasm: buying is exciting, selling is dull, so notice bites on the exciting side. The enthusiasm explanation is available, it is intuitive, and it is not what is happening. The real reason is arithmetic about set sizes, and it has nothing to do with mood.

When Meera Sundaram buys, her candidate set is everything she could possibly buy. Her buying candidate set runs to thousands of things, and no filter she can apply will ever consider more than a handful of them. Almost all of the removing had to be done by something, so a filter that admits only what reached her notice is doing almost all of the selecting. When she sells, her candidate set is the four holdings she already has. She does not need reminding that she holds them; they are on her own statement. A filter has nearly nothing left to remove. AsymmetryAn effect that runs strongly in one direction and weakly in the other. here is a property of the two sets, not of the person standing in front of them.

Put the same 11.0 per cent rate against two sizes of set. THE BUY SIDE about 2,000 candidates 220 220 of the 2,000 get admitted, so the filter is removing nearly the whole set before any comparison. THE SELL SIDE four holdings 0.44 of one candidate the same rate admits less than one whole holding, so notice cannot be what does the selecting on this side. 11.0 per cent of 2,000 is 220. 11.0 per cent of 4 is 0.44, which is not a set anybody can choose from. All four are on her own statement each time she looks, so nothing ever needed admitting. Invented figures.
The same 11.0 per cent rate admits 220 candidates on one side and less than one whole holding on the other.
A filter matters in proportion to what it is filtering. The two panels are not drawn to the same scale. If they were, the right one would be invisible. THE BUY SIDE: THOUSANDS OF CANDIDATES MENTIONED IN THE WEEK, 11.0 PER CENT everything else, never reached and therefore never compared THE SELL SIDE: FOUR CANDIDATES Vindhya index scheme Nilgiri mid-cap scheme Suvarna Chemicals Limited Kesari Logistics Limited a filter admitting 11 in 100 removes almost the entire set a filter has almost nothing left to remove, so it changes almost nothing Same person, same week, same attention. The difference is the size of the set. Invented figures.
The buying side and the selling side face sets of wildly different sizes, which is why one shows the effect and the other has almost no room to.

Barber and Odean framed the asymmetry this way in the 2008 paper, and framing it structurally is what makes it testable rather than merely plausible. The size of the set being filtered decides how much a filter matters, so the same person with the same attention in the same week shows the effect strongly in one direction and barely at all in the other. Nothing about enthusiasm predicts that. Set size predicts it exactly.

Two readings of the same asymmetry. Only one of them predicts anything. THE READING THAT GETS MADE buying is where the excitement is, so notice bites on the exciting side WHAT IT PREDICTS a calmer person on the selling side, and a mood that could be measured GETS THE MECHANISM BACKWARDS WHAT THE STRUCTURE SAYS a filter matters in proportion to the size of the set it is filtering WHAT IT PREDICTS strong where the set is thousands, weak where the set is four NO MOOD REQUIRED ANYWHERE The log measures the buying side, at 41 of 96 against a base rate of 11.0 per cent. On the selling side there are four candidates, so there is barely a filter left to measure.
Reading the asymmetry as enthusiasm predicts a mood, while reading it as set size predicts the pattern actually seen in the log.

The error that gets made, and what it costs

The error is expecting the same effect on the selling side, then concluding that something is wrong with the measurement when it does not appear. From there it is a short step to explaining the difference with a story about temperament: people get excited when they buy and sober when they sell.

The cost is the ability to predict anything. A temperament story says the effect should follow the person, so a calm person should show less of it everywhere and an excitable one more of it everywhere. The structural account says the effect follows the set, so the very same person shows it strongly where the set is thousands and hardly at all where the set is four. The temperament story and the structural account disagree about what would happen if nothing about the person changed and only the size of the list in front of them changed. Their disagreement is exactly the test that separates them.

There is a second, quieter cost. If the cause is believed to be excitement, the fix reached for is a calming one: wait a day, sleep on it, decide nothing while worked up. If the cause is set size, the shortlist slept on is the same shortlist that would have been decided on, so the calming fix leaves the filter running untouched. The decision has been delayed without anything changing about what was up for decision.

Try it out

Why does the effect barely appear on the selling side?

Derivatives Foundation Bootcamp — Fin Maverick

What can a person do about a filter they cannot feel operating?

The honest starting point is that the usual advice does not work here. Trying harder to notice more is not a thing attention can do on command. There is no volume control, and a person who resolves to be more observant this week has changed nothing about the size of the world. The world is still larger than they are. Kahneman's 1973 treatment of attention as a limited pool implies exactly that: the allocation can be moved around, but the total cannot be raised.

The only move available is structural: deciding what to look at before looking. A written list settled in advance, an order in which things get examined, a rule that a decision waits until at least two options nobody put in front of the decider have been added to the set. None of these require noticing more. Each of them changes the set itself, and the set was always beyond the reach of effort.

Two moves are imaginable. Only one of them is available. FEWER DECISIONS DECIDED BY WHAT HAPPENED TO REACH THE DECIDER TRY HARDER TO NOTICE MORE work at it, stay alert, read more widely DECIDE WHAT TO LOOK AT FIRST a written list, settled before looking attention has no volume control, so the set stays exactly as it was the set changes, and the effort spent deciding does not have to change at all What changes is the set, not the effort. Whether either move improves any result is a separate question.
The correction available for a filter that cannot be felt is structural rather than mental, because the set can be changed and the effort cannot be raised.

The Palash log has one measurement close to this, and it needs stating carefully. Twenty of the 60 investors adopted a written checklist on 4 November. Across the four quarters that followed they recorded a written reason on 34 of 41 decisions, being 82.9 per cent, against 19 of 63 for the other forty, being 30.2 per cent. The comparison measures whether a reason got written down, and it measures nothing else at all. Eight quarters and 60 investors could not support a claim about returns, so no difference in returns follows from these two shares.

What the checklist measured, and what it did not. This counts whether a reason got written down. It counts nothing else at all. THE 20 WHO ADOPTED THE CHECKLIST 82.9%, being 34 of 41 THE OTHER 40, WITH NO CHECKLIST 30.2%, being 19 of 63 0 25 50 75 100 per cent of decisions carrying a written reason 34 divided by 41 is 82.9 per cent. 19 divided by 63 is 30.2 per cent. The two are over fifty points apart. No difference in any result is claimed, measured or implied. Invented figures throughout.
A written reason was recorded on 82.9 per cent of decisions with a checklist against 30.2 per cent without one.
Try it out

What is the only real correction available for a filter that cannot be felt operating?

Cleaning Financial Data — free micro-course from Fin Maverick

When is filtering by what reached notice the right thing to do?

The alternative is examining thousands, and nobody has ever done that and nobody ever will. So something has to cut thousands of possibilities down to a handful. Notice is a free filter. Notice costs nothing to apply, it runs whether or not anybody asks it to, and it delivers a workable shortlist in no time at all. Judged as a filter rather than as a judgement, it is doing a job that must be done by something.

The conditions under which it is a reasonable filter can be stated plainly. First, the cost of examining any one option is high relative to how much better the best option is than an average one. Second, what reaches notice is not systematically related to whether the option is any good, so the filter is behaving like a cheap random sample rather than a biased one. Under those two conditions a shortlist drawn from whatever happened to be seen is a sensible economy, and calling it an error would be a mistake.

Two conditions decide whether the free filter is a sensible one. NOTICE UNRELATED TO QUALITY NOTICE CHOSEN BY SOMEBODY ELSE EXAMINING AN OPTION IS COSTLY EXAMINING IS CHEAP A SENSIBLE ECONOMY the shortlist behaves like a cheap sample of the list THE TROUBLE STARTS HERE the set is being drawn on the decider's behalf by a party wanting something NO FILTER NEEDED look at them, since looking costs almost nothing LOOK ANYWAY cheap looking removes the reason to lean on notice The case in this guide sits in the top row, where examining thousands of options is not available. This describes how a filter can go wrong. It is not a claim about anything that appeared anywhere.
Filtering by notice is a sensible economy only where examining is costly and notice is unrelated to quality.

The second condition fails whenever what reaches notice is being chosen by somebody with an interest in that choice being made, and the trouble starts precisely there. Then the filter stops resembling a random sample and starts resembling a selection made on the decider's behalf by a party whose objective is a different one. A filter goes wrong in exactly that way, whoever is doing the choosing and whatever is being chosen.

Try it out

Is filtering by what reached notice ever the right thing to do?

Cleaning Financial Data teaches you to find the errors that survive every check and break every model. Fund Waterfalls and Carry — free micro-course from Fin Maverick

How does an adviser use this without telling anybody what to hold?

Devika Rao, the adviser at the invented Palash Advisory Services Private Limited, does not use any of this to form a view about a holding. She uses it to ask a different question in the meeting, and the question is about stage two rather than stage three. When a client arrives having decided, the usual question is why this one. Her question is what else was on the list, and where did these three come from.

The two questions get very different answers. The first produces a reasoned case, usually genuine and telling her nothing about the filter. The second produces either a source she can look at, such as a screen or a list somebody keeps, or a shrug. A shrug is the finding. A shrug does not mean the choice is bad; it means the choice was made inside a set that assembled itself, and that fact is now on the table where it can be discussed.

Two questions, and only one of them reaches the filter. THE QUESTION THAT GETS ASKED why this one? produces a reasoned case, which is usually genuine and reveals nothing at all about the filter an answer about stage three only THE QUESTION THAT REACHES IT what else was on the list? produces either a source to look at or a shrug, and a shrug is itself the finding an answer about stage two Stage two is what reached notice. Stage three is the set that actually got compared. Neither question is about whether the choice was any good, and neither one produces advice.
Asking why this one produces a reasoned case, while asking what else was on the list finds the filter.

For a person deciding alone, with no adviser and no committee, the same move works with a pen. Before deciding, write down the three or four things being compared and, beside each, one line saying how it came to be on the list. The exercise takes two minutes and its whole value is that it makes stage two visible. Stage two is the one stage nobody can recall without being asked. If every line says the same thing, the filter has been found.

Two habits follow from this in practice, and both are about the set rather than about anybody's judgement. One is keeping a standing list that gets updated on a schedule rather than in response to events, so the set exists before the moment of deciding rather than being assembled at it. Decisions taken within a few days of something reaching notice are the population where the filter has most room to have operated, so the other habit is a rule that every such decision gets its written reason recorded. In the log, 71 of 240 decisions, being 29.6 per cent, were taken within 48 hours of a news item, and a written reason existed on only 84 of 240, being 35.0 per cent, so the overlap between those two groups is where an adviser would look first.

Two counts out of the same 240 decisions, and one unknown. each bar runs across all 240 decisions in the log 71, being 29.6% taken within 48 hours of a news item 84, being 35.0% carrying a written reason HOW MANY DECISIONS SIT IN BOTH GROUPS AT ONCE anywhere from 0 to 71. The log carries the two counts and not the overlap. 71 divided by 240 is 29.6 per cent and 84 divided by 240 is 35.0 per cent. The overlap is where an adviser would look first, and it is the number the log does not hold.
The log records both counts out of 240 and not their overlap, which could be anywhere from none to 71.
Building a Client Risk Profile teaches you to turn a client conversation into a documented risk profile, and to separate capacity from tolerance.

What else decides which options reach a person?

Attention is one of several things that decide which options reach a person, and only one of them is what arrives from outside and reaches notice. Memory supplies a second route and a display supplies a third: what comes back when a person tries to think of options, and what makes one item on a screen stand out against the others around it, are both set out under availability and salience. The distinction is genuinely useful: one is about what got through to a person, the other is about what can be retrieved or what a display emphasises.

Attention bias also stops well short of the aggregate. A great deal of interesting work asks what happens when many people are subject to the same filter in the same week, and that question belongs to market behaviour. How one decision got made and what happens to a price are two different questions, and the second one cannot be answered from a single decider. Every individual bias is likewise a statement about a decision rather than about a price.

Several things decide what reaches a person. This guide takes one of them. TAUGHT HERE, AND ONLY THIS what arrived from outside and reached notice TAKEN LATER, SEPARATELY what comes back from memory when a person tries to think of options TAKEN LATER, SEPARATELY what makes one item on a screen stand out from the ones around it TAKEN ELSEWHERE AGAIN what happens when many people share one filter in the very same week Everything in this guide is a statement about how one decision got made, and nothing more. Nothing here is a statement about what attention does to any price. Invented figures throughout.
Attention bias covers what arrived from outside and reached notice, and the three neighbouring questions are covered separately.
Memory and display are two further routes into a consideration set, and both are set out under availability and salience with their own original papers. The effect of attention on a price is an aggregate question and belongs to market behaviour. The arithmetic of set sizes does not care who holds the list, so the mechanism is the same for a person deciding alone and for a professional deciding on behalf of others. A mention carries no information about whether a holding is good or bad; the filter decides what got looked at, not what was worth looking at.

Sources

SourceDocumentSite
Daniel KahnemanAttention and Effort, 1973, in which attention is set out as a limited resource that gets allocated rather than a capacity that can be raisedbook, not a repository
Brad Barber and Terrance OdeanAll That Glitters, Review of Financial Studies, 2008, introducing attention-driven buying and the asymmetry between the buying and selling sidesssrn.com
Amos Tversky and Daniel KahnemanJudgment under Uncertainty: Heuristics and Biases, Science, 1974, the paper that set out the heuristics-and-biases programmessrn.com
Herbert Simonthe 1955 paper in the Quarterly Journal of Economics setting out a decider who works with a manageable slice of the world rather than all of itssrn.com

Meera Sundaram, Devika Rao, Palash Advisory Services Private Limited, the Palash decision log, the Palash 100 index, the Vindhya index scheme, the Nilgiri mid-cap scheme, Suvarna Chemicals Limited and Kesari Logistics Limited are invented.
Educational material. Not advice on any investment, tax, budget or market position.

Covered in this topic

Subtopics

Attention BiasAttention-Driven Buying
Next →
Fin Maverick Micro CoursesExplore Micro Courses
Fin Maverick BootcampsExplore Bootcamps
Fin Maverick

Finance education that ends in a job, not a certificate that gathers dust. Built for young India.

LEARN
CalculatorsFrameworksComparisonsCareersShowdown
RESOURCES
All CoursesMicro CoursesBootcampsInternships
COMPANY
AboutJob openingPartnership
LEGAL
Privacy PolicyTerms & ConditionsContent LicenseReturn & Refund Policy
© 2026 FIN MAVERICK / BUILT FOR INDIA.DO FINANCE, DO NOT JUST READ ABOUT IT.