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Lesson 2 of 4 8–12% of the exam

Cognitive errors: belief perseverance and information processing

Belief perseverance biases keep us holding on to what we already think: conservatism, confirmation, representativeness, illusion of control and hindsight. Information-processing biases distort how we use numbers and facts: anchoring, mental accounting, framing and availability. Each has a tell-tale behavior and a fix.

8 min cram, 40 min full read. Based on the 2027 CFA® Program Level I curriculum, Portfolio Construction, Learning Module 5. Also part of the 2026 curriculum, so it applies to the November 2026 exam too.

Tailor this to you: take the self-assessment

Before this: Cognitive errors vs emotional biases

On the exam

  • Discuss commonly recognized behavioral biases and their implications for financial decision making

Discuss the biases and their implications for financial decisions. Expect a vignette that describes one behavior and offers three bias names, sometimes with a base-rate calculation.

How deeply to learn each part
Know the idea
Understand it in general. It frames other topics, but you will not calculate with it.
Use it
Understand it well enough to solve a question with it. Recognize when it applies.
Memorize
Learn it by heart. The exam will not give it to you.

You know this one. The full lesson is folded away. The takeaways, formulas and checkpoint below are your quick refresher, and the checkpoint is a fair test of whether you still do.

You tested strong here. The full lesson is folded away. The takeaways, formulas and checkpoint below are your quick refresher, and the checkpoint is a fair test of whether you still know it.

Cram mode: the one-screen version of this lesson. Switch to Full for the explanations, worked examples and interactives.

Why do beliefs persist?

Belief perseverance biases come from the mental discomfort of meeting information that conflicts with what we already believe. That discomfort is called cognitive dissonance . To resolve it, people ignore, modify or explain away the conflicting information, using statistical, processing or memory errors to do so. Five biases fall in this group.

Belief perseverance biases and their tells
Belief perseverancecognitive dissonance: conflicting information is uncomfortable
  • Conservatism Memorize slow to update; underreacts to news
  • Confirmation Memorize seeks and notices only agreeing evidence
  • Representativeness Memorize classifies by resemblance to a familiar type
    • Base-rate neglect ignores how common the event is
    • Sample-size neglect treats a small sample as typical
  • Illusion of control Memorize believes they can influence outcomes
  • Hindsight Memorize past events seem to have been predictable
BiasTell-taleInvestor consequenceFix
Conservatismslow to update a forecast after new informationunderreacts to newsweigh new information properly; ask what it really changes
Confirmationseeks only evidence that agreesignores warnings; concentrated positionsactively look for the opposite case
Representativenessjudges by resemblance; ignores base rate or small sample“good company means good stock”; chasing last year’s top fundcheck base rates; use more data
Illusion of controlbelieves they can influence outcomestrades too much; under-diversifiesremember investing is probabilistic; seek contrary views
Hindsight“I knew it all along”overestimates ability to predictwrite decisions and reasons down at the time

Conservatism. Conservatism bias is maintaining a prior view by inadequately incorporating new, conflicting information. In Bayesian terms, the person overweights the prior probability and underweights the new evidence. It is worst for information that is technical or statistical, because processing it costs effort. The fix is to ask, each time: “How does this information change my forecast?”

Confirmation. Confirmation bias is looking for, and noticing, what supports an existing belief while ignoring or undervaluing what contradicts it. A client who researches a holding and reads only the bullish articles is a typical case. The consequences are one-sided analysis, screens that overlook contrary data, and concentrated, under-diversified positions. Seek out the opposite case, and corroborate a decision with a second source.

Representativeness. Representativeness bias is sorting new information into a familiar category because it looks like that category, even when the resemblance is misleading. It has two forms. Base-rate neglect lets specific information about a case override how common the event is in its wider group. Sample-size neglect treats a small sample as if it described the whole population. The fix is to compare the group the investment looks like with the group it most often turns out to belong to, then gather base-rate data or a wider sample before deciding.

Illusion of control. Illusion of control bias is believing that you can control or influence outcomes when you cannot. It leads to inadequate diversification (a big stake in your own employer), too much trading, and forecasts and models that are overly detailed in the belief that detail controls uncertainty. The fix is to accept that investing is a probabilistic activity and to seek contrary viewpoints.

Hindsight. Hindsight bias is believing that past events were predictable and reasonable to expect. People also remember their own predictions as more accurate than they were. It breeds overconfidence and unfair assessment of managers, who are judged on what happened instead of on what could be known at the time. The fix is to record decisions and their reasons in writing when they are made.

How does base-rate neglect work with numbers?

Use it

Base-rate neglect is a Bayes error. A signal, such as a screen flag, has a hit rate and a false-positive rate. The probability that a flagged case really has the event also depends on how rare the event is, and that is the base rate.

Probability of an event after a flag (base rate with Bayes) Use it
P(E∣F)=P(E) P(F∣E)P(E) P(F∣E)+[1−P(E)] P(F∣not E)P(E \mid F) = \frac{P(E)\,P(F \mid E)}{P(E)\,P(F \mid E) + [1 - P(E)]\,P(F \mid \text{not } E)}

Here P(E)P(E) is the base rate, P(F∣E)P(F \mid E) is the hit rate and P(F∣not E)P(F \mid \text{not } E) is the false-positive rate.

Rearrange itProbability after a flag: solve for any input
The question asks for
2.00% of the companies in a sector face the event. A screen flags 80.00% of the companies that will face it and also flags 10.00% of those that will not. For a flagged company, the probability of the event is closest to:

(0.02 × 0.8) ÷ (0.02 × 0.8 + 0.98 × 0.1) = 14.04%

Probability of the event, given a flag14.04%

On your calculator
  1. 0.02×0.8=STO1numerator
  2. (1−0.02)×0.1+RCL1=denominator
  3. 1/x×RCL1=a decimal, ×100 for percent

STO store · RCL recall a stored number · 1/x reciprocal

  1. 0.02ENTER0.8×STO1numerator
  2. 1ENTER0.02−0.1×RCL1+denominator
  3. 1/xRCL1×a decimal, ×100 for percent

ENTER enter (on the HP, puts the number on the stack) · STO store · RCL recall a stored number · 1/x reciprocal

Exam tip Counting 1,000 companies is faster than the formula on a tight clock. Flagged and real, divided by all flagged.

How do information-processing biases differ?

Information-processing biases are not about clinging to a belief. They are about using facts and numbers illogically. There are four.

Information-processing biases and their tells
Information processingfacts and numbers used illogically
  • Anchoring and adjustment Memorize starts from an initial number and adjusts too little
  • Mental accounting Memorize treats money differently by bucket or source
  • Framing Memorize the answer depends on how the question is posed
    • Narrow framing looks at one or two points, loses the big picture
  • Availability Memorize likelihood judged by how easily examples come to mind
    • Retrievability the first idea to come to mind wins
    • Categorization familiar search sets bias the estimate
    • Narrow range of experience one country, one sector, one product
    • Resonance close to my own situation
BiasTell-taleInvestor consequenceFix
Anchoring and adjustmentsticks to an initial number (the purchase price, last year’s forecast) and adjusts too littleholds until “back to what I paid”ask whether you would buy it today at today’s price
Mental accountingtreats money differently by bucket or sourcea “safe” pot and a “fun” pot; correlations between pots ignoredcombine all assets and look at the whole portfolio
Framingthe answer depends on how the question is posedrisk-tolerance answers swing with wordingrestate neutrally; ignore gains and losses so far
Availabilityjudges likelihood by how easily examples come to mindbuys what is in the news; narrow opportunity setwritten policy, disciplined research, long-term data

Anchoring and adjustment. Anchoring and adjustment bias is relying on an initial piece of information, an anchor, and adjusting from it too little. A retailer’s same-store sales forecast nudged down 2% from this year’s figure after a key supplier has failed is anchored on this year’s number; the estimate should be rebuilt from the new conditions. A price paid is irrelevant to the market’s view of the future, yet investors anchor on it.

Mental accounting. Mental accounting bias is dividing money into mental accounts that influence decisions, even though money is fungible. Consequences: missing the chance to reduce risk by combining assets with low correlations, treating income and capital gains as different things (chasing income and risking principal), and “playing with house money”. A good detection exercise is to list all holdings together, with the account names removed, and look at the combined allocation.

Framing. Framing bias means answering a question differently depending on how it is posed. “Seven in ten new restaurants survive their first year” and “three in ten new restaurants close within a year” say the same thing, yet they draw different answers. With a gain frame people become more risk-averse, and with a loss frame more risk-seeking. Narrow framing is a special case: attending to one or two points, such as a single product launch, and losing the big picture of industry, financial results and valuation.

Availability. Availability bias is estimating the probability or importance of something by how easily it comes to mind. It can restrict the investment opportunity set, lead to choosing funds by advertising or news coverage, and cause a failure to diversify. The four sources in the tree are worth knowing by name.

Loading the interactive

Match each short vignette to its bias. The second tab runs the base-rate example with sliders, so you can see the posterior fall when the base rate falls.

Go deeper Conservatism or anchoring?

Both underreact, and the curriculum notes that anchoring and adjustment is closely related to conservatism. For the exam, use the clue. Conservatism is about beliefs and probabilities: the person does not revise a view enough when evidence arrives. Anchoring is about a number, such as a price paid or last year’s figure, from which the estimate is adjusted too little.

Go deeper Why framing matters for risk questionnaires

If a client sees returns first and risk second, or sees a 95% return range instead of a standard deviation, the chosen portfolio can change even though nothing about the portfolios has changed. An adviser who relies on one questionnaire may misidentify the client’s risk tolerance. Asking the same question in more than one form is a simple safeguard.

Go deeper When mental accounting helps

Separate buckets can help a saver stay disciplined: a pot labeled “house deposit” is harder to raid. The problem arises in portfolio construction, where treating the buckets as independent hides their correlation and the total risk. The cure is to keep the budgeting benefit and still view the whole portfolio.

Memorize this

MemorizeNine cognitive errors: the tell and the fix

BiasTell-taleFix
Conservatismforecast barely moves after big newsask "how does this change my forecast?"
Confirmationreads only agreeing reportsseek the opposite case; corroborate
Representativenessignores base rate or small sampleask the base-rate probability; more data
Illusion of control"my timing makes it work"; overtradesinvesting is probabilistic; seek contrary views
Hindsight"it was obvious"write decisions and reasons down at the time
Anchoringwaits for the purchase price or last year's numberwould I buy it today at today's price?
Mental accountingseparate "safe" and "fun" pots, house moneycombine all assets in one unlabeled view
Framinganswer flips with gain or loss wordingrestate neutrally; ignore gains and losses so far
Availabilitybuys what is in the news or advertisedwritten policy, disciplined research, long-term data

Memory hook Each bias has a tell. Learn the tell, not the definition, because the exam describes the behavior and hides the name.

Know it cold Conservatism = slow to update (a belief). Anchoring = stuck on a number. Confirmation = filters evidence. Do not swap them.

MemorizeBase-rate neglect and the four sources of availability

Memory hook Think of 1,000 companies: count who is flagged and what share of the flagged really have the event. Sources of availability: Retrievability, Categorization, Narrow range of experience, Resonance (R-C-N-R).

Know it cold P(E∣F)P(E \mid F) = true flags ÷ all flags. Ignoring the base rate and answering with the hit rate is representativeness.

Belief perseverance biases and their tells
Belief perseverancecognitive dissonance: conflicting information is uncomfortable
  • Conservatism Memorize slow to update; underreacts to news
  • Confirmation Memorize seeks and notices only agreeing evidence
  • Representativeness Memorize classifies by resemblance to a familiar type
    • Base-rate neglect ignores how common the event is
    • Sample-size neglect treats a small sample as typical
  • Illusion of control Memorize believes they can influence outcomes
  • Hindsight Memorize past events seem to have been predictable
Information-processing biases and their tells
Information processingfacts and numbers used illogically
  • Anchoring and adjustment Memorize starts from an initial number and adjusts too little
  • Mental accounting Memorize treats money differently by bucket or source
  • Framing Memorize the answer depends on how the question is posed
    • Narrow framing looks at one or two points, loses the big picture
  • Availability Memorize likelihood judged by how easily examples come to mind
    • Retrievability the first idea to come to mind wins
    • Categorization familiar search sets bias the estimate
    • Narrow range of experience one country, one sector, one product
    • Resonance close to my own situation
Probability of an event after a flag (base rate with Bayes) Use it
P(E∣F)=P(E) P(F∣E)P(E) P(F∣E)+[1−P(E)] P(F∣not E)P(E \mid F) = \frac{P(E)\,P(F \mid E)}{P(E)\,P(F \mid E) + [1 - P(E)]\,P(F \mid \text{not } E)}
Quick example

Base rate 4%, hit rate 75%, false-positive rate 12%. (0.04 × 0.75) ÷ (0.04 × 0.75 + 0.96 × 0.12) = 0.03 ÷ 0.1452 = 20.7%, not 75%.

On your calculator
  1. 0.04×0.75=STO1 numerator 0.03
  2. (1−0.04)×0.12+RCL1= denominator 0.1452
  3. 1/x×RCL1= 0.2066

STO store · RCL recall a stored number · 1/x reciprocal

  1. 0.04ENTER0.75×STO1 numerator 0.03
  2. 1ENTER0.04−0.12×RCL1+ denominator 0.1452
  3. 1/xRCL1× 0.2066

ENTER enter (on the HP, puts the number on the stack) · STO store · RCL recall a stored number · 1/x reciprocal

How it is asked

  1. Slow to update after news

    An analyst leaves forecasts almost unchanged after the loss of the largest customer.

    Conservatism. Trap: confirmation, which is about filtering evidence, not about slow updating.

  2. Buckets of money

    A "safe" bond pot and a "play money" account, never considered together.

    Mental accounting. Consequence: correlations between pots are ignored.

  3. Flagged company, what probability?

    Base rate 3%, hit rate 85%, false positives 20%.

    0.0255 ÷ (0.0255 + 0.194) = 11.6%. Trap: 85% (base-rate neglect).

  4. Holding until the purchase price

    The vignette stresses the price paid as the reference point.

    Anchoring and adjustment when the number is the clue; loss aversion when the pain of realizing a loss is the clue.

Exam traps

  • Confusing conservatism (slow to update) with confirmation (filters information to agree).
  • Missing the clue in "hold until I get back to what I paid". If the vignette stresses the purchase price as a number to reach, it points to anchoring (cognitive); if it stresses the pain of realizing a loss, it is loss aversion (emotional).
  • Labeling news-driven buying as representativeness. Judging likelihood by what is easy to recall is availability.
  • Answering a base-rate question with the hit rate. The flagged share must be weighed against how rare the event is.

Checkpoint

5 exam-style questions. About 90 seconds each.

  1. 1An analyst keeps a buy rating and leaves earnings forecasts almost unchanged after a company announces the loss of its largest customer. The analyst most likely shows:

  2. 2An investor keeps a separate "safe" portfolio of bonds for retirement and a "play money" account of speculative shares, and never considers how the two together affect total risk. This is best described as:

  3. 3In a sector, 5% of companies cut their dividend each year. A model flags 90% of companies that will cut, and also flags 15% of those that will not. For a flagged company, the probability of a dividend cut is closest to:

  4. 4A portfolio manager who owns a stock reads only the bullish research on it and dismisses the sell-rated reports as "uninformed". The manager most likely shows:

  5. 5A client chooses a fund because its advertisements are everywhere and because it is the first name that comes to mind. The client most likely shows:

Key takeaways

  • Belief perseverance: conservatism, confirmation, representativeness (base-rate and sample-size neglect), illusion of control, hindsight.
  • Information processing: anchoring and adjustment, mental accounting, framing, availability.
  • Base-rate neglect is a Bayes error: weigh the flag against how rare the event is.
  • Cognitive errors can be reduced with process, data and education.
Probability of an event after a flag (base rate with Bayes) Use it
P(E∣F)=P(E) P(F∣E)P(E) P(F∣E)+[1−P(E)] P(F∣not E)P(E \mid F) = \frac{P(E)\,P(F \mid E)}{P(E)\,P(F \mid E) + [1 - P(E)]\,P(F \mid \text{not } E)}
Quick example

Base rate 4%, hit rate 75%, false-positive rate 12%. (0.04 × 0.75) ÷ (0.04 × 0.75 + 0.96 × 0.12) = 0.03 ÷ 0.1452 = 20.7%, not 75%.

On your calculator
  1. 0.04×0.75=STO1 numerator 0.03
  2. (1−0.04)×0.12+RCL1= denominator 0.1452
  3. 1/x×RCL1= 0.2066

STO store · RCL recall a stored number · 1/x reciprocal

  1. 0.04ENTER0.75×STO1 numerator 0.03
  2. 1ENTER0.04−0.12×RCL1+ denominator 0.1452
  3. 1/xRCL1× 0.2066

ENTER enter (on the HP, puts the number on the stack) · STO store · RCL recall a stored number · 1/x reciprocal

All Portfolio Construction formulas, every lesson

Practice exam-style questions on The Behavioral Biases of Individuals

Questions about this lesson?

Where this comes back

Questions candidates ask

What is the difference between conservatism bias and confirmation bias?

Conservatism is being slow to update a view when new information arrives, so the person underreacts. Confirmation is filtering information: looking for and noticing what agrees with a prior belief and ignoring what contradicts it. Both protect an existing belief, but one is about speed of updating and the other about which evidence is seen.

What is base-rate neglect?

Base-rate neglect is a kind of representativeness bias in which specific information about a case outweighs how common the event is in the wider group. A model that flags 80% of failing firms says little about a flagged firm if only 2% of firms fail: the true probability may be about 14%.

What is an example of mental accounting in investing?

Treating a windfall as house money and spending it on a high-risk bet, or keeping a safe pot and a speculative pot without looking at how they combine. Money is fungible, so the risk that matters is that of the whole portfolio, including the correlations between pots.

Spotted an error? Tell us and we will fix it.

  1. Cognitive errors vs emotional biases
  2. Cognitive errors: belief perseverance and information processing
  3. Emotional biases: loss aversion, overconfidence and four more
  4. How biases show up in markets: momentum, bubbles and value

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