SlideShare una empresa de Scribd logo
1 de 18
Descargar para leer sin conexión
Prospect Theory
PERCEPTION BASIS
Section IV
Markets
Describe two insights from
prospect theory
 Describe the single greatest
limitation of prospect theory
Perception Basis
A perception bias arises when an individual has difficulty figuring out what
the problem is that needs to be solved. Perception biases come in many
forms.
Saliency Framing
Anchoring
Sunk Cost
Basis
Saliency
 we have a tendency to ignore that thing even if it is important to an upcoming
decision.
 No one seems interested in buying flood insurance unless there has been a
recent flood.
Saliency works in two ways.
1. If an event has not occurred recently, then that event tends to be perceived
as having zero or negligible probability of occurring in the future.
2. If the same event has occurred very recently, the perceived probability of a
future occurrence becomes overstated.
the occurrence of “bad” economic states seems to be perceived as almost
impossible when the economy is strong and the demand for credit is high.
Framing
 The simplest setting for framing is the consideration of alternative policies that
involve an unavoidable loss of life
Problem 1.
Imagine that the country is preparing for the outbreak of an unusual disease, which is
expected to kill 600 people. Which of the following programs would you favor?
Program A: Has the effect of saving 200 people.
Program B: Has a 1/3 chance of saving 600 people and a 2/3 chance that no one will be
saved.
(Most people will choose Program A when given the choice)
 Program C: 400 people will die for certain.
Program D: 1/3 chance that no one will die and 2/3 chance that 600 people will die.
(Most people will choose Program A & C)
Framing
In Problem 1, respondents think of each person they save as a gain, and therefore
make the risk-averse choice—saving 200 people for sure is more palatable than
taking the chance that everyone might die.
In Problem 2, respondents think of each person that dies as a loss, so they make
the risk-loving choice. Sending 400 people to their deaths seems rather
Draconian when the other option presents a reasonable chance that all might
live.
Framing
Problem 3
Program E: 25 percent chance to win $240 and 75 percent chance to lose $760.
Program F: 25 percent chance to win $250 and 75 percent chance to lose $750.
In Problem 3, virtually everyone will choose F over E since F dominates E.
The rational and proper choice is F.
Problem 4
Imagine that you face the following pair of concurrent decisions. First, examine both
decisions, then indicate the options you prefer.
Decision (i)—choose between:
A. sure gain of $240.
B. 25 percent chance to gain $1,000 and 75 percent chance to gain nothing.
Decision (ii)—choose between:
C. A sure loss of $750.
D. 75 percent chance to lose $1,000 and 25 percent chance to lose nothing.
Framing
Framing is doing is exploiting our attitude toward bad events.
In the first example, respondents do not wish to do harm. Therefore, when the
choice is between saving people and rolling the dice, respondents want to save
people. But when the identical choice set is presented and framed as if the
respondent is choosing that 400 people will die with certainty, respondents go for
the choice that presents the possibility of saving everyone, even though all 600
might die. Perception is the key.
In Monetary Position Framing is taking advantage of loss aversion in Problems 3
and 4. Most respondents choose A, expressing risk aversion, and D expressing
risk seeking. Such choices are routine to loss aversion.
Anchoring
Anchoring bias in decision-making. Anchoring or focalism is a term used in
psychology to describe the common human tendency to rely too heavily, or
"anchor," on one trait or piece of information when making decisions.
the investor is anchoring on a recent "high" that the stock has achieved and
consequently believes that the drop in price provides an opportunity to buy the
stock at a discount.
For instance, suppose that XYZ stock had very strong revenue in the last year,
causing its share price to shoot up from $25 to $80. Unfortunately, one of the
company's major customers, who contributed to 50% of XYZ's revenue, had
decided not to renew its purchasing agreement with XYZ. This change of events
causes a drop in XYZ's share price from $80 to $40.
Anchoring
By anchoring to the previous high of $80 and the current price of $40, the
investor erroneously believes that XYZ is undervalued. Keep in mind that XYZ is
not being sold at a discount, instead the drop in share value is attributed to a
change to XYZ's fundamentals (loss of revenue from a big customer). In this
example, the investor has fallen prey to the dangers of anchoring.
Successful investors don't just base their decisions on one or two benchmarks,
they evaluate each company from a variety of perspectives in order to derive the
truest picture of the investment landscape.
Sunk Cost Basis
• A sunk cost is a cost that has already been incurred and thus cannot
be recovered.
• A sunk cost differs from future costs that a business may face, such
as decisions about inventory purchase costs or product pricing.
• The decision to pay for a ticket to attend a future event is based on
expectations about the utility of that future event.
• Having paid for the ticket, once the future event arrives, you must
make a new decision—should you attend or not?
• What you paid for the ticket earlier should be irrelevant, economists
argue, to the decision to attend.
Sunk Cost Basis
• Sunk costs involve regret, the bias that results is similar to the bias an investor
shows when reluctant to purchase a stock after missing the opportunity to buy
the stock at a cheaper price.
• Investors who “go to cash” in the midst of a financial crisis are sometimes
disappointed that, after they sell out, stocks rally to higher prices.
• Will they get back in? Often, the answer is no.
• The investor will wait and hope that stocks fall back to the levels at which they
had made their earlier exit.
• What if that never happens? Then investors may wait until the regret they feel
from not getting back in goes away.
• Once the feeling of regret is no longer present simply because of the passage of
time, the investor might invest again, often at much higher prices.
Inertia Effect
Section IV
Markets
Endorment Effect
Status Quo Effect
Disposition Effect
Endowment Effect
• Imagine two identical people making a choice between two options, option A
and option B. The only difference between the two people is that the first starts
at A and is asked whether or not he or she would like to move to B, whereas the
second starts at B and is offered the ability to move to A.
• The endowment effect, in behavioral finance, describes a circumstance in which
an individual values something that they already own more than something
that they do not yet own.
• Investors, therefore, tend to stick with certain assets because of familiarity &
comfort, even if they are inappropriate or become unprofitable. The
endowment effect is an example of an emotional bias.
Status Quo Effect
• Status quo bias is evident when people prefer things to stay the same by doing
nothing (see also inertia) or by sticking with a decision made previously
• In economics, status quo bias can cause individuals to make seemingly non-
rational decisions to stay with a sub-optimal situation.
• Examples of status quo bias
- Choosing default option
- Preference for old plans
- Brand allegiance
Why people prefer the Status Quo
• Endowment effect - In behavioural
economics, we can observe a preference
for people to give a higher weighting to
what they already have. We become
attached to our current situation and
goods.
• Fear of unknown - Psychologically people
may express a feeling of ‘better the devil
you know.’ In other words, people dislike
uncertainty and are risk averse at making
a choice.
• Costs of making choices - Suppose every
day you drink at Starbucks. The Coffee is
good. It could be better, but it could be
worse.
Why people prefer the Status Quo
• Inertia. - People may simply not want the hassle of changing.
• Repeated exposure gives familiarity and attachment - If we experience
something every day, we develop an attachment to the good. For example, if we
take a daily paper, we become a loyal reader
• Loyalty - An aspect of human nature is loyalty. If we support one sports team,
we have a reluctance to change.
Is status quo bias rational or irrational?
• If we stick with current choices to avoid costs of making decisions, then it can
be seen as a rational choice as we save calculation costs. However, if we refuse
to consider alternatives on the basis we only want to stay with what we have
then it becomes more irrational.
Disposition Effect
• The disposition effect is an anomaly discovered in behavioral finance.
• It relates to the tendency of investors to sell shares whose price has increased,
while keeping assets that have dropped in value.
• It is possible to minimize the disposition effect by using a concept called
hedonic framing to change your mental approach.
For example, in situations where you have a choice of thinking of something as
one large gain or as a number of smaller gains (such as finding $100 versus
finding a $50 bill from two places), thinking of the latter can maximize the
amount of positive utility.

Más contenido relacionado

La actualidad más candente

Behavioural economics introduction
Behavioural economics introductionBehavioural economics introduction
Behavioural economics introductionEton College
 
Behavioural Economics in Advertising Planning
Behavioural Economics in Advertising PlanningBehavioural Economics in Advertising Planning
Behavioural Economics in Advertising PlanningPhilip De Meulemeester
 
Principles of behavioural economics
Principles of behavioural economics  Principles of behavioural economics
Principles of behavioural economics Terry Corby
 
Behavioral Economics and Decision Making
Behavioral Economics and Decision MakingBehavioral Economics and Decision Making
Behavioral Economics and Decision Makingneerupaharia
 
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...The Hunting Dynasty
 
Behavioral Biases
Behavioral BiasesBehavioral Biases
Behavioral BiasesSnawer Gill
 
How to convince your boss to use insights and strategies from Behavioral Econ...
How to convince your boss to use insights and strategies from Behavioral Econ...How to convince your boss to use insights and strategies from Behavioral Econ...
How to convince your boss to use insights and strategies from Behavioral Econ...beworks
 
Behavioral economics overview presentation at TGAS
Behavioral economics overview presentation at TGASBehavioral economics overview presentation at TGAS
Behavioral economics overview presentation at TGASKurt Nelson, PhD
 
Behavioural Economics
Behavioural EconomicsBehavioural Economics
Behavioural EconomicsHugo OGrady
 
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015clmagana
 
Behavioural economics and digital marketing
Behavioural economics and digital marketingBehavioural economics and digital marketing
Behavioural economics and digital marketingVyshnavi Doss
 
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral Finance
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral FinanceStanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral Finance
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral FinanceAdam Nash
 
Introduction to Behavioural Economics
Introduction to Behavioural EconomicsIntroduction to Behavioural Economics
Introduction to Behavioural EconomicsGraymatter
 
Personal Finance for Engineers (Twitter, 2013)
Personal Finance for Engineers (Twitter, 2013)Personal Finance for Engineers (Twitter, 2013)
Personal Finance for Engineers (Twitter, 2013)Adam Nash
 

La actualidad más candente (17)

Behavioural economics introduction
Behavioural economics introductionBehavioural economics introduction
Behavioural economics introduction
 
Overconfidence bias
Overconfidence biasOverconfidence bias
Overconfidence bias
 
Behavioural Economics in Advertising Planning
Behavioural Economics in Advertising PlanningBehavioural Economics in Advertising Planning
Behavioural Economics in Advertising Planning
 
Principles of behavioural economics
Principles of behavioural economics  Principles of behavioural economics
Principles of behavioural economics
 
Behavioral Economics and Decision Making
Behavioral Economics and Decision MakingBehavioral Economics and Decision Making
Behavioral Economics and Decision Making
 
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...
Creating Sustainable Behaviour, for Forum for the Future Master's scholars an...
 
Behavioral Biases
Behavioral BiasesBehavioral Biases
Behavioral Biases
 
How to convince your boss to use insights and strategies from Behavioral Econ...
How to convince your boss to use insights and strategies from Behavioral Econ...How to convince your boss to use insights and strategies from Behavioral Econ...
How to convince your boss to use insights and strategies from Behavioral Econ...
 
Learning session 2nd
Learning session 2ndLearning session 2nd
Learning session 2nd
 
Behavioral economics overview presentation at TGAS
Behavioral economics overview presentation at TGASBehavioral economics overview presentation at TGAS
Behavioral economics overview presentation at TGAS
 
Behavioural Economics
Behavioural EconomicsBehavioural Economics
Behavioural Economics
 
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015
Investment Policy Statement PPT Northwest Planned Giving Roundtable Nov 13 2015
 
Behavioural economics and digital marketing
Behavioural economics and digital marketingBehavioural economics and digital marketing
Behavioural economics and digital marketing
 
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral Finance
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral FinanceStanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral Finance
Stanford CS 007-2 (2019): Personal Finance for Engineers / Behavioral Finance
 
Introduction to Behavioural Economics
Introduction to Behavioural EconomicsIntroduction to Behavioural Economics
Introduction to Behavioural Economics
 
Personal Finance for Engineers (Twitter, 2013)
Personal Finance for Engineers (Twitter, 2013)Personal Finance for Engineers (Twitter, 2013)
Personal Finance for Engineers (Twitter, 2013)
 
behavioral biases and investment decisions
behavioral biases and  investment decisionsbehavioral biases and  investment decisions
behavioral biases and investment decisions
 

Similar a Cmt learning objective 20 inertia effect

Chapter 3 risk aversion and risk management by individuals and corporations
Chapter 3 risk aversion and risk management by individuals and corporationsChapter 3 risk aversion and risk management by individuals and corporations
Chapter 3 risk aversion and risk management by individuals and corporationsDr Riyaz Muhmmad
 
Wscc behaviour change capacity building workshop
Wscc behaviour change capacity building workshopWscc behaviour change capacity building workshop
Wscc behaviour change capacity building workshopThe Hunting Dynasty
 
Key Principles of Behavioural Finance
Key Principles of Behavioural FinanceKey Principles of Behavioural Finance
Key Principles of Behavioural FinanceJawwad Siddiqui
 
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...Rohit Singh
 
Behavioral Finance
Behavioral FinanceBehavioral Finance
Behavioral FinancePRIYA M.M
 
Behavioral Finance
Behavioral FinanceBehavioral Finance
Behavioral Financehus gary
 
Foundations of Rational Finance.pdf
Foundations of Rational Finance.pdfFoundations of Rational Finance.pdf
Foundations of Rational Finance.pdfDayanand Huded
 
The Economic Way of Thinking, part 2
The Economic Way of Thinking, part 2The Economic Way of Thinking, part 2
The Economic Way of Thinking, part 2Matthew Caggia
 
Behavioural Finance Final Ppt
Behavioural Finance Final PptBehavioural Finance Final Ppt
Behavioural Finance Final Pptsharadaiyer
 
FINAL MICRO PAPER
FINAL MICRO PAPERFINAL MICRO PAPER
FINAL MICRO PAPERGreg Poapst
 
The Economic Way of Thinking
The Economic Way of ThinkingThe Economic Way of Thinking
The Economic Way of ThinkingMatthew Caggia
 
Common investment mistakes
Common investment mistakesCommon investment mistakes
Common investment mistakesGerry Gatawa
 

Similar a Cmt learning objective 20 inertia effect (20)

Chapter 3 risk aversion and risk management by individuals and corporations
Chapter 3 risk aversion and risk management by individuals and corporationsChapter 3 risk aversion and risk management by individuals and corporations
Chapter 3 risk aversion and risk management by individuals and corporations
 
Endownment effect
Endownment effectEndownment effect
Endownment effect
 
Wscc behaviour change capacity building workshop
Wscc behaviour change capacity building workshopWscc behaviour change capacity building workshop
Wscc behaviour change capacity building workshop
 
Key Principles of Behavioural Finance
Key Principles of Behavioural FinanceKey Principles of Behavioural Finance
Key Principles of Behavioural Finance
 
Investment Decision Making
Investment Decision MakingInvestment Decision Making
Investment Decision Making
 
Cmt learning objective 18 prospects theory
Cmt learning objective 18   prospects theoryCmt learning objective 18   prospects theory
Cmt learning objective 18 prospects theory
 
Risk and Return
Risk and ReturnRisk and Return
Risk and Return
 
Behavioral finance (2008)
Behavioral finance (2008)Behavioral finance (2008)
Behavioral finance (2008)
 
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...
Behavioral Finance (Prospect Theory, Mental Accounting, Regret Aversion & Sel...
 
Behavioral Finance
Behavioral FinanceBehavioral Finance
Behavioral Finance
 
Behavioral Finance
Behavioral FinanceBehavioral Finance
Behavioral Finance
 
Psychological biases
Psychological biasesPsychological biases
Psychological biases
 
Foundations of Rational Finance.pdf
Foundations of Rational Finance.pdfFoundations of Rational Finance.pdf
Foundations of Rational Finance.pdf
 
The Economic Way of Thinking, part 2
The Economic Way of Thinking, part 2The Economic Way of Thinking, part 2
The Economic Way of Thinking, part 2
 
Behavioural Finance Final Ppt
Behavioural Finance Final PptBehavioural Finance Final Ppt
Behavioural Finance Final Ppt
 
Representativeness Bias.pptx
Representativeness Bias.pptxRepresentativeness Bias.pptx
Representativeness Bias.pptx
 
FINAL MICRO PAPER
FINAL MICRO PAPERFINAL MICRO PAPER
FINAL MICRO PAPER
 
The Economic Way of Thinking
The Economic Way of ThinkingThe Economic Way of Thinking
The Economic Way of Thinking
 
chap008.ppt
chap008.pptchap008.ppt
chap008.ppt
 
Common investment mistakes
Common investment mistakesCommon investment mistakes
Common investment mistakes
 

Más de Professional Training Academy

Lecture E - Standard V Investment Analysis, Recommendations, and Actions
Lecture E - Standard V Investment Analysis, Recommendations, and ActionsLecture E - Standard V Investment Analysis, Recommendations, and Actions
Lecture E - Standard V Investment Analysis, Recommendations, and ActionsProfessional Training Academy
 
SECTION VII - CHAPTER 42 - Being Right or making money
SECTION VII - CHAPTER 42 - Being Right or making moneySECTION VII - CHAPTER 42 - Being Right or making money
SECTION VII - CHAPTER 42 - Being Right or making moneyProfessional Training Academy
 
SECTION VII - CHAPTER 41 - Objective Rules & Evaluation
SECTION VII - CHAPTER 41 - Objective Rules & EvaluationSECTION VII - CHAPTER 41 - Objective Rules & Evaluation
SECTION VII - CHAPTER 41 - Objective Rules & EvaluationProfessional Training Academy
 
SECTION VI - CHAPTER 39 - Descriptive Statistics basics
SECTION VI - CHAPTER 39 - Descriptive Statistics basicsSECTION VI - CHAPTER 39 - Descriptive Statistics basics
SECTION VI - CHAPTER 39 - Descriptive Statistics basicsProfessional Training Academy
 
SECTION V- CHAPTER 38 - Sentiment Measures from External Data
SECTION V- CHAPTER 38  - Sentiment Measures from External  DataSECTION V- CHAPTER 38  - Sentiment Measures from External  Data
SECTION V- CHAPTER 38 - Sentiment Measures from External DataProfessional Training Academy
 
SECTION V - CHAPTER 37 - Sentiment Measures from Market Data
SECTION V - CHAPTER 37 - Sentiment Measures from Market DataSECTION V - CHAPTER 37 - Sentiment Measures from Market Data
SECTION V - CHAPTER 37 - Sentiment Measures from Market DataProfessional Training Academy
 
SECTION V - CHAPTER 36 - Market Sentiment & Technical Analysis
SECTION V - CHAPTER 36 - Market Sentiment & Technical AnalysisSECTION V - CHAPTER 36 - Market Sentiment & Technical Analysis
SECTION V - CHAPTER 36 - Market Sentiment & Technical AnalysisProfessional Training Academy
 
SECTION V - CHAPTER 35 - Academic Approaches to Technical Analysis
SECTION V - CHAPTER 35 - Academic Approaches to Technical AnalysisSECTION V - CHAPTER 35 - Academic Approaches to Technical Analysis
SECTION V - CHAPTER 35 - Academic Approaches to Technical AnalysisProfessional Training Academy
 
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdf
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdfSECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdf
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdfProfessional Training Academy
 
SECTION V - CHAPTER 33 - Noise Traders & Law of One Price
SECTION V - CHAPTER 33 - Noise Traders & Law of One PriceSECTION V - CHAPTER 33 - Noise Traders & Law of One Price
SECTION V - CHAPTER 33 - Noise Traders & Law of One PriceProfessional Training Academy
 
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdf
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdfSECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdf
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdfProfessional Training Academy
 

Más de Professional Training Academy (20)

Chapter D - Knowledge Domains and Weightings
Chapter D - Knowledge Domains and WeightingsChapter D - Knowledge Domains and Weightings
Chapter D - Knowledge Domains and Weightings
 
Lecture F - Standard VI Conflicts of Interest
Lecture F - Standard VI Conflicts of InterestLecture F - Standard VI Conflicts of Interest
Lecture F - Standard VI Conflicts of Interest
 
Lecture E - Standard V Investment Analysis, Recommendations, and Actions
Lecture E - Standard V Investment Analysis, Recommendations, and ActionsLecture E - Standard V Investment Analysis, Recommendations, and Actions
Lecture E - Standard V Investment Analysis, Recommendations, and Actions
 
Lecture D - Standard IV Duties to Employers
Lecture D - Standard IV Duties to EmployersLecture D - Standard IV Duties to Employers
Lecture D - Standard IV Duties to Employers
 
Lecture C - Standard III Duties to Clients
Lecture C - Standard III Duties to ClientsLecture C - Standard III Duties to Clients
Lecture C - Standard III Duties to Clients
 
Lecture B - Standard II Integrity of Capital Markets
Lecture B - Standard II Integrity of Capital MarketsLecture B - Standard II Integrity of Capital Markets
Lecture B - Standard II Integrity of Capital Markets
 
Lecture A - Standard I Professionalism
Lecture A - Standard I ProfessionalismLecture A - Standard I Professionalism
Lecture A - Standard I Professionalism
 
SECTION VII - CHAPTER 44 - Relative Strength Concept
SECTION VII - CHAPTER 44 -  Relative Strength ConceptSECTION VII - CHAPTER 44 -  Relative Strength Concept
SECTION VII - CHAPTER 44 - Relative Strength Concept
 
SECTION VII - CHAPTER 43 - Model Building Process
SECTION VII - CHAPTER 43 - Model Building ProcessSECTION VII - CHAPTER 43 - Model Building Process
SECTION VII - CHAPTER 43 - Model Building Process
 
SECTION VII - CHAPTER 42 - Being Right or making money
SECTION VII - CHAPTER 42 - Being Right or making moneySECTION VII - CHAPTER 42 - Being Right or making money
SECTION VII - CHAPTER 42 - Being Right or making money
 
SECTION VII - CHAPTER 41 - Objective Rules & Evaluation
SECTION VII - CHAPTER 41 - Objective Rules & EvaluationSECTION VII - CHAPTER 41 - Objective Rules & Evaluation
SECTION VII - CHAPTER 41 - Objective Rules & Evaluation
 
SECTION VI - CHAPTER 40 - Concept of Probablity
SECTION VI - CHAPTER 40 - Concept of ProbablitySECTION VI - CHAPTER 40 - Concept of Probablity
SECTION VI - CHAPTER 40 - Concept of Probablity
 
SECTION VI - CHAPTER 39 - Descriptive Statistics basics
SECTION VI - CHAPTER 39 - Descriptive Statistics basicsSECTION VI - CHAPTER 39 - Descriptive Statistics basics
SECTION VI - CHAPTER 39 - Descriptive Statistics basics
 
SECTION V- CHAPTER 38 - Sentiment Measures from External Data
SECTION V- CHAPTER 38  - Sentiment Measures from External  DataSECTION V- CHAPTER 38  - Sentiment Measures from External  Data
SECTION V- CHAPTER 38 - Sentiment Measures from External Data
 
SECTION V - CHAPTER 37 - Sentiment Measures from Market Data
SECTION V - CHAPTER 37 - Sentiment Measures from Market DataSECTION V - CHAPTER 37 - Sentiment Measures from Market Data
SECTION V - CHAPTER 37 - Sentiment Measures from Market Data
 
SECTION V - CHAPTER 36 - Market Sentiment & Technical Analysis
SECTION V - CHAPTER 36 - Market Sentiment & Technical AnalysisSECTION V - CHAPTER 36 - Market Sentiment & Technical Analysis
SECTION V - CHAPTER 36 - Market Sentiment & Technical Analysis
 
SECTION V - CHAPTER 35 - Academic Approaches to Technical Analysis
SECTION V - CHAPTER 35 - Academic Approaches to Technical AnalysisSECTION V - CHAPTER 35 - Academic Approaches to Technical Analysis
SECTION V - CHAPTER 35 - Academic Approaches to Technical Analysis
 
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdf
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdfSECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdf
SECTION V - CHAPTER 34 - Noise Traders as technical Traders.pdf
 
SECTION V - CHAPTER 33 - Noise Traders & Law of One Price
SECTION V - CHAPTER 33 - Noise Traders & Law of One PriceSECTION V - CHAPTER 33 - Noise Traders & Law of One Price
SECTION V - CHAPTER 33 - Noise Traders & Law of One Price
 
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdf
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdfSECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdf
SECTION V - CHAPTER 32 - Forerunners to Behavioural Finance.pdf
 

Último

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfJayanti Pande
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppCeline George
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991RKavithamani
 

Último (20)

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Staff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSDStaff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSD
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website App
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
 

Cmt learning objective 20 inertia effect

  • 2. PERCEPTION BASIS Section IV Markets Describe two insights from prospect theory  Describe the single greatest limitation of prospect theory
  • 3. Perception Basis A perception bias arises when an individual has difficulty figuring out what the problem is that needs to be solved. Perception biases come in many forms. Saliency Framing Anchoring Sunk Cost Basis
  • 4. Saliency  we have a tendency to ignore that thing even if it is important to an upcoming decision.  No one seems interested in buying flood insurance unless there has been a recent flood. Saliency works in two ways. 1. If an event has not occurred recently, then that event tends to be perceived as having zero or negligible probability of occurring in the future. 2. If the same event has occurred very recently, the perceived probability of a future occurrence becomes overstated. the occurrence of “bad” economic states seems to be perceived as almost impossible when the economy is strong and the demand for credit is high.
  • 5. Framing  The simplest setting for framing is the consideration of alternative policies that involve an unavoidable loss of life Problem 1. Imagine that the country is preparing for the outbreak of an unusual disease, which is expected to kill 600 people. Which of the following programs would you favor? Program A: Has the effect of saving 200 people. Program B: Has a 1/3 chance of saving 600 people and a 2/3 chance that no one will be saved. (Most people will choose Program A when given the choice)  Program C: 400 people will die for certain. Program D: 1/3 chance that no one will die and 2/3 chance that 600 people will die. (Most people will choose Program A & C)
  • 6. Framing In Problem 1, respondents think of each person they save as a gain, and therefore make the risk-averse choice—saving 200 people for sure is more palatable than taking the chance that everyone might die. In Problem 2, respondents think of each person that dies as a loss, so they make the risk-loving choice. Sending 400 people to their deaths seems rather Draconian when the other option presents a reasonable chance that all might live.
  • 7. Framing Problem 3 Program E: 25 percent chance to win $240 and 75 percent chance to lose $760. Program F: 25 percent chance to win $250 and 75 percent chance to lose $750. In Problem 3, virtually everyone will choose F over E since F dominates E. The rational and proper choice is F. Problem 4 Imagine that you face the following pair of concurrent decisions. First, examine both decisions, then indicate the options you prefer. Decision (i)—choose between: A. sure gain of $240. B. 25 percent chance to gain $1,000 and 75 percent chance to gain nothing. Decision (ii)—choose between: C. A sure loss of $750. D. 75 percent chance to lose $1,000 and 25 percent chance to lose nothing.
  • 8. Framing Framing is doing is exploiting our attitude toward bad events. In the first example, respondents do not wish to do harm. Therefore, when the choice is between saving people and rolling the dice, respondents want to save people. But when the identical choice set is presented and framed as if the respondent is choosing that 400 people will die with certainty, respondents go for the choice that presents the possibility of saving everyone, even though all 600 might die. Perception is the key. In Monetary Position Framing is taking advantage of loss aversion in Problems 3 and 4. Most respondents choose A, expressing risk aversion, and D expressing risk seeking. Such choices are routine to loss aversion.
  • 9. Anchoring Anchoring bias in decision-making. Anchoring or focalism is a term used in psychology to describe the common human tendency to rely too heavily, or "anchor," on one trait or piece of information when making decisions. the investor is anchoring on a recent "high" that the stock has achieved and consequently believes that the drop in price provides an opportunity to buy the stock at a discount. For instance, suppose that XYZ stock had very strong revenue in the last year, causing its share price to shoot up from $25 to $80. Unfortunately, one of the company's major customers, who contributed to 50% of XYZ's revenue, had decided not to renew its purchasing agreement with XYZ. This change of events causes a drop in XYZ's share price from $80 to $40.
  • 10. Anchoring By anchoring to the previous high of $80 and the current price of $40, the investor erroneously believes that XYZ is undervalued. Keep in mind that XYZ is not being sold at a discount, instead the drop in share value is attributed to a change to XYZ's fundamentals (loss of revenue from a big customer). In this example, the investor has fallen prey to the dangers of anchoring. Successful investors don't just base their decisions on one or two benchmarks, they evaluate each company from a variety of perspectives in order to derive the truest picture of the investment landscape.
  • 11. Sunk Cost Basis • A sunk cost is a cost that has already been incurred and thus cannot be recovered. • A sunk cost differs from future costs that a business may face, such as decisions about inventory purchase costs or product pricing. • The decision to pay for a ticket to attend a future event is based on expectations about the utility of that future event. • Having paid for the ticket, once the future event arrives, you must make a new decision—should you attend or not? • What you paid for the ticket earlier should be irrelevant, economists argue, to the decision to attend.
  • 12. Sunk Cost Basis • Sunk costs involve regret, the bias that results is similar to the bias an investor shows when reluctant to purchase a stock after missing the opportunity to buy the stock at a cheaper price. • Investors who “go to cash” in the midst of a financial crisis are sometimes disappointed that, after they sell out, stocks rally to higher prices. • Will they get back in? Often, the answer is no. • The investor will wait and hope that stocks fall back to the levels at which they had made their earlier exit. • What if that never happens? Then investors may wait until the regret they feel from not getting back in goes away. • Once the feeling of regret is no longer present simply because of the passage of time, the investor might invest again, often at much higher prices.
  • 13. Inertia Effect Section IV Markets Endorment Effect Status Quo Effect Disposition Effect
  • 14. Endowment Effect • Imagine two identical people making a choice between two options, option A and option B. The only difference between the two people is that the first starts at A and is asked whether or not he or she would like to move to B, whereas the second starts at B and is offered the ability to move to A. • The endowment effect, in behavioral finance, describes a circumstance in which an individual values something that they already own more than something that they do not yet own. • Investors, therefore, tend to stick with certain assets because of familiarity & comfort, even if they are inappropriate or become unprofitable. The endowment effect is an example of an emotional bias.
  • 15. Status Quo Effect • Status quo bias is evident when people prefer things to stay the same by doing nothing (see also inertia) or by sticking with a decision made previously • In economics, status quo bias can cause individuals to make seemingly non- rational decisions to stay with a sub-optimal situation. • Examples of status quo bias - Choosing default option - Preference for old plans - Brand allegiance
  • 16. Why people prefer the Status Quo • Endowment effect - In behavioural economics, we can observe a preference for people to give a higher weighting to what they already have. We become attached to our current situation and goods. • Fear of unknown - Psychologically people may express a feeling of ‘better the devil you know.’ In other words, people dislike uncertainty and are risk averse at making a choice. • Costs of making choices - Suppose every day you drink at Starbucks. The Coffee is good. It could be better, but it could be worse.
  • 17. Why people prefer the Status Quo • Inertia. - People may simply not want the hassle of changing. • Repeated exposure gives familiarity and attachment - If we experience something every day, we develop an attachment to the good. For example, if we take a daily paper, we become a loyal reader • Loyalty - An aspect of human nature is loyalty. If we support one sports team, we have a reluctance to change. Is status quo bias rational or irrational? • If we stick with current choices to avoid costs of making decisions, then it can be seen as a rational choice as we save calculation costs. However, if we refuse to consider alternatives on the basis we only want to stay with what we have then it becomes more irrational.
  • 18. Disposition Effect • The disposition effect is an anomaly discovered in behavioral finance. • It relates to the tendency of investors to sell shares whose price has increased, while keeping assets that have dropped in value. • It is possible to minimize the disposition effect by using a concept called hedonic framing to change your mental approach. For example, in situations where you have a choice of thinking of something as one large gain or as a number of smaller gains (such as finding $100 versus finding a $50 bill from two places), thinking of the latter can maximize the amount of positive utility.