The chapter consists of Expected Utility Theory [EUT] and Rational Thought: Decision Making under Risk and Uncertainty - Expected Utility as a basis for Decision-Making – Theories Based on Expected Utility Concept – Investor Rationality and Market Efficiency. Self Deception – Forms of Over Confidence, Causes of Over Confidence, and other Forms of Self-Deception. Prospect Theory, Difference between EUT and Prospect Theory; Agency Theory; SP/A Theory; Framing, Mental Accounting; Error in Bernoulli’s Theory. Expected utility theory and its examples. Making decisions under certainty is easy. The cause and effect are known, and the risk involved is minimal. What’s tough is making decisions under risk and uncertainty. The outcome is unpredictable because you don’t have all the information about the alternatives. Before we learn deeper about decision-making under risk and uncertainty, let’s look at each of these situations such as certainty, risk and uncertainty. Despite all the data crunching and predictive technology, businesses these days have to deal with a lot of uncertainty and the ‘what if’ scenarios. The recent pandemic outbreak has dramatically altered the business landscape globally. Today, decision-making has become more complicated due to the uncertainty all around us.

1. Behavioural Finance
Unit-III: Foundation of Rational Finance
Expected Utility Theory [EUT] and Rational Thought: Decision
Making under Risk and Uncertainty - Expected Utility as a basis for
Decision-Making – Theories Based on Expected Utility Concept –
Investor Rationality and Market Efficiency. Self Deception – Forms
of Over Confidence, Causes of Over Confidence, and other Forms
of Self-Deception. Prospect Theory, Difference between EUT and
of Self-Deception. Prospect Theory, Difference between EUT and
Prospect Theory; Agency Theory; SP/A Theory; Framing, Mental
Accounting; Error in Bernoulli’s Theory.
Prepared by
Mr. Dayananda Huded M.Com NET 2 Times, KSET
Teaching Assistant,
Rani Channamma University, PG Centre, Jamkhandi, Karnataka
1
Mr. Dayananda Huded

2. Expected Utility Theory
• "Expected utility" is an economic term summarizing the utility that an entity or
aggregate economy is expected to reach under any number of circumstances. The
expected utility is calculated by taking the weighted average of all possible outcomes
under certain circumstances. With the weights being assigned by the likelihood or
probability, any particular event will occur.
• Expected utility is a theory in economics that estimates the utility of an action when
the outcome is uncertain. It advises choosing the action or event with the maximum
expected utility. At any point in time, the expected utility will be the weighted average
of all the probable utility levels that an entity is expected to reach under specific
circumstances.
circumstances.
• Expected utility refers to the utility of an entity or aggregate economy over a future
period of time, given unknowable circumstances.
• Expected utility theory is used as a tool for analyzing situations in which individuals
must make a decision without knowing the outcomes that may result from that
decision
• The expected utility theory was first posited by Daniel Bernoulli who used it to solve
the St. Petersburg Paradox.
• Expected utility is also used to evaluate situations without immediate payback, such
as purchasing insurance.
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3. • The expected utility hypothesis states that under uncertainty, the weighted
average of all possible levels of utility will best represent the utility at any
given point in time.
• Expected utility theory is used as a tool for analyzing situations in which
individuals must make a decision without knowing the outcomes that may
result from that decision, i.e., decision making under uncertainty. These
individuals will choose the action that will result in the highest expected
utility, which is the sum of the products of probability and utility over all
utility, which is the sum of the products of probability and utility over all
possible outcomes. The decision made will also depend on the agent’s risk
aversion and the utility of other agents.
• This theory also notes that the utility of money does not necessarily
equate to the total value of money. This theory helps explain why people
may take out insurance policies to cover themselves for various risks. The
expected value from paying for insurance would be to lose out
monetarily. The possibility of large-scale losses could lead to a serious
decline in utility because of the diminishing marginal utility of wealth.
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4. Example 1
• For example, suppose:
• A lottery ticket costs ₹ 200.
• The probability of winning the ₹ 20,000 prize is 0.5%
• The likely value from having a lottery ticket will be the
outcome x probability of the event occurring.
• Therefore, expected value = 0.005 x 20,000 = ₹ 100
• The expected value of owning a lottery ticket is ₹ 100. With an
• The expected value of owning a lottery ticket is ₹ 100. With an
infinite number of events, on average, this is the likely payout. Of
course, we may be lucky or maybe unlucky if we play only once.
• Since the ticket costs ₹ 200, it seems an illogical decision to buy –
because the expected value of buying a ticket is ₹ 100 – a smaller
figure than the cost of purchase ₹ 200.
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5. Example 2
• Suppose the chance of house being destroyed by lightning is 0.0001, but
if it is destroyed you lose ₹ 300,000.
• The expected value of your house is therefore 0.9999 x 300,000 = ₹
299,970.
• The expected loss of your house is just ₹ 30.
• An insurance company may be willing to insure against the loss of your
house worth ₹ 300,000 for ₹ 100 a year.
• According to the expected value, you should not insure your house. The
• According to the expected value, you should not insure your house. The
cost of insurance ₹ 100 is far greater than the expected loss ₹ 30 from the
house being destroyed.
• However, the expected utility is different.
• If you are wealthy, paying ₹ 100 only has a small marginal decline in
utility.
• However, if you were unlucky and lost your house the loss of everything
would have a corresponding greater impact on utility.
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6. Expected Utility Theory and Rational Thought
• We must often make decisions under conditions of uncertainty.
• This is logic that prescribes how decisions should be made.
• the utility of a money is not necessarily the same as the total value of money. This
explains why people may take out insurance. The expected value from paying for
insurance would be to lose out monetarily. But, the possibility of large-scale losses could
lead to a serious decline in utility because of the diminishing marginal utility of wealth.
• The expected utility theory takes into account that individuals may be risk-averse.
• The expected utility theory considers it a logical choice to choose the event with the
maximum expected utility. However, in case of risky outcomes, decision-makers may not
choose the action with a higher expected utility. The decision to choose an action will also
depend on the entity’s risk aversion and other entities’ utility.
• Example: A doctor's appointment may result in the early detection and treatment of a
disease
• Applications of Expected Utility
• 1. Public and Economics Policy: The expected utility theory finds application in public
policy, as it explains that the social arrangement that maximizes the total welfare across
society is the most socially right arrangement.
• 2. Ethics: Utilitarians believe that the result of an act determines whether or not the right
action is taken. However, it is extremely difficult to establish the long-term consequence
of an act. Mr. Dayananda Huded 6

7. Decision Making under Risk and Uncertainty
• Making decisions under certainty is easy. The cause and effect are known, and the risk
involved is minimal. What’s tough is making decisions under risk and uncertainty. The
outcome is unpredictable because you don’t have all the information about the
alternatives. Before we learn deeper about decision-making under risk and uncertainty,
let’s look at each of these situations:
• CERTAINTY
• Sometimes we have enough facts and evidence to know the possible results of a decision.
These are the most conducive situations for decision-making because the outcomes are
quite obvious. For instance, if you drop a glass full of milk, the milk will definitely spill.
Such an environment is known as certainty.
• RISK
• Risk is where you are unsure of what can happen, but you know the likelihood of a
• Risk is where you are unsure of what can happen, but you know the likelihood of a
particular outcome. Let’s say you invest in a promising stock and the stock market is on a
surge. In such a scenario, you see a higher chance that your investment will grow.
However, you don’t know the extent to which it can grow. It might double or increase by
10% and in the worst-case scenario, you might even lose money if the market crashes.
Taking a decision under such circumstances is known as decision-making under risk.
• UNCERTAINTY
• In case of an uncertain environment, you can’t predict the outcomes as you have no
information or data available. You have no control over what might happen and don’t even
know the options you have.
• It is like driving blindfolded where you know you need to move but don’t know the type
of vehicle or the road you will be taking. Such a scenario will lead to decision-making
under uncertainty.
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8. • Depending on the amount and degree of knowledge you have, the
conditions are;
• 1. Making decisions under pure uncertainty (I don’t know): You are
ignorant or have absolutely no knowledge, not even about the likelihood
of occurrence for an event. Your behaviour is purely based on your
attitude toward the unknown.
• 2. Making decisions under risk (I know the probability estimates): You
have some knowledge and can assign subjective probabilities regarding
have some knowledge and can assign subjective probabilities regarding
each event.
• 3. Making decisions by acquiring more information (I can acquire reliable
information): You acquire more information and knowkedge to reach a
certain level of certainty.
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9. Decision Making Under Risk
• There are times when you need to make decisions even when you
don’t have adequate or credible information or when the
information obtained from different sources doesn’t match up.
• This happens when you don’t know for sure how each of the
alternatives will pan out and whether you will be able to achieve the
goal by taking a particular decision. However, you have enough
understanding to know how likely each option is to be successful.
• It is this likelihood or probability of each of the options that a
manager needs to take into account and apply experience, expertise,
and gut feeling to the process of decision-making.
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10. Decision Making Under Uncertainty
• Despite all the data crunching and predictive technology, businesses these days have
to deal with a lot of uncertainty and the ‘what if’ scenarios.
• The recent pandemic outbreak has dramatically altered the business landscape
globally. Today, decision-making has become more complicated due to the
uncertainty all around us.
• Let’s say you want to open a couple of new stores for your retail chain, and you have
an idea about the average footfall or the earning that an average outlet generates. Yet,
there is a lot of uncertainty as the operational procedures and customer behavior has
become unpredictable.
become unpredictable.
• Hence, you are compelled to undertake decision-making under uncertainty.
• However, decisions under uncertainty are different from decision-making under risk.
In the latter case, you are not even aware of all the options you have, the risks that
each alternative poses, and the outcomes of all of these options. In fact, you are not
even aware of the probabilities when you opt for decision-making under risk.
• It becomes imperative for managers to use their experience and make assumptions
about the situation and the outcomes while making decisions under uncertainty.
However, they have to rely less on their individual judgment while indulging in
decision making under risk.
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11. Investors Rationality & Market Efficiency
• Definition of rationality, Vriend states: “Rationality in economics means that an
individual agent chooses (one of) the most advantageous options, given his
preferences, in his perceived opportunity set.” and he adds: “such that all
perceived costs and benefits are taken into account; in particular, information,
decision-making and transaction costs”.
• Rationality is a key assumption in many economic models. By assuming that
investors are rational, the volatility, dynamics and unpredictability of human
behavior is constricted. This makes human behavior more static and controllable
allowing for economic models to explain relationships, behavior, market
allowing for economic models to explain relationships, behavior, market
phenomena and such.
• When investors assess the value of stocks and are rational they will find its
theoretical value by calculating the net present value of all future cash flow and
discounting them based on their risk adjusted required return.
• Then if new information arrives the rational investors will rapidly adjust to this
news by buy or selling stocks depending on the nature of the news.
• This will lead to efficiency as stock prices will reflect all existing public
information in the market and continuously adjust to new information.
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12. Irrationality
• So if rationality creates efficiency, rational investors would do best with a
passive strategy of buying and holding the index.
• Yet we observe investors doing things quite contrary to this logic some
examples of this include:
• “Investors follow the advice of financial gurus, fail to diversify, actively
trade stocks and churn their portfolios, sell winning stocks and hold on to
losing stocks thereby increasing their tax liabilities, buy and sell actively
and expensively managed mutual funds, follow stock price patterns and
and expensively managed mutual funds, follow stock price patterns and
other popular models.” (Shleifer, 2000, p.10).
• These common observed types of irrational behavior certainly raise
questions towards assumptions of full rationality of all investors. Still
there are many more anomalies within rationality to be discussed.
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13. Anomalies within Rationality
• 1. Many anomalies concerned with the rational behavior of investors have
been identified. One of these is the endowment effect identified by Thaler
which can be described as that people will value an asset they have higher
than what they themselves would pay to acquire this asset (Kahneman et
al., 1991
• 2. Another type of irrational behavior is seen in Prospect Theory.
• If investors were rational they would aggregate the net effect of gains and
losses associated with an alternative and decide which is more preferable.
losses associated with an alternative and decide which is more preferable.
• However a study in 1979 showed that investors are not that rational in this
way and developed the concept of prospect theory.
• This theory asserts that investors value gains and losses differently.
• Consequently when an investor is faced with two alternatives with equal
expected results but one is conveyed as a possible loss and the other as a
possible gain, the investors will select the latter.
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14. Difference between Expected Utility Theory & Prospect Theory
Expected Utility Theory Prospect Theory
Logic that describes how decisions can
be made
Depicts how humans actually makes risky choices, without
assuming anything about their rationality
Rational Almost irrational
Choices are coherently & consistently
made by weighing outcomes of actions
Prefers more only on gains
Emotions are controlled Emotions, feelings are influencing decision with uncertainty
aggregate economy is expected to
reach under any number of
Loss aversion: losses looms larger than gains
reach under any number of
circumstances.
Mathematical terms and actual losses
and gains are considered
Evaluation is relative to your current reference point (to gain &
losses)
Sometimes absolute values may be
considered while taking decisions
People choices or make decisions not on absolute value but on
psychological values of outcome
Focuses on absolute values. Diminishing sensitivity
Ex. 1. (Gain Point of view) Value Increases from 5000 to 1000
Value increases from 35000 to 40000
2. (Loss point of view) Decreases from 10000 to 5000 and
decreasing 40000 to 35000
The first option looks like vary worst.
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15. • EUT: Marginal utility decreases as increase in wealth (risk aversion)
• PT: Marginal value decreases over gains but increases over losses (risk
aversion for gains, risk seeking for losses).
• EUT: Utility is measured as a function of absolute wealth.
• PT: Value is measured over gains and losses relative to a reference point.
• Ex. Mr. A bought microsoft share @ ₹ 25 and now it is ₹ 35 and Mr. B
bought the same micro-soft share ₹ 45 & he is in loss of ₹ 10 per share.
(loss aversion for Mr. A and risk seeking for Mr. B)
(loss aversion for Mr. A and risk seeking for Mr. B)
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16. Agency Theory
• Agency theory is a principle that is used to explain and resolve issues in the
relationship between business principals and their agents. Most commonly, that
relationship is the one between shareholders, as principals, and company
executives, as agents.
• Agency theory attempts to explain and resolve disputes over the respective
priorities between principals and their agents.
• Principals rely on agents to execute certain transactions, which results in a
difference in agreement on priorities and methods.
• The difference in priorities and interests between agents and principals is known
• The difference in priorities and interests between agents and principals is known
as the principal-agent problem.
• Resolving the differences in expectations is called "reducing agency loss."
• Performance-based compensation is one way that is used to achieve a balance
between principal and agent.
• Agency Theory is a management and economic theory that explains the
• various relationships and areas of self-interest in companies.
• Common principal-agent relationships include shareholders and management,
financial planners and their clients, and lessees and lessors.
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17. • Agency theory assumes that the interests of a principal and an agent are
not always in alignment. The lack of perfect alignment between the
interests of managers and shareholders results in agency costs which
may be defined as the difference between the value of an actual firm
and value of a hypothetical firm in which management and shareholder
interests are perfectly aligned.
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18. Areas of Dispute in Agency Theory
• Agency theory addresses disputes that arise primarily in two key areas: A
difference in goals or a difference in risk aversion.
• For example, company executives, with an eye toward short-term
profitability and elevated compensation, may desire to expand a business
into new, high-risk markets. However, this could pose an unjustified risk
to shareholders, who are most concerned with the long-term growth of
earnings and share price appreciation.
• Another central issue often addressed by agency theory involves
• Another central issue often addressed by agency theory involves
incompatible levels of risk tolerance between a principal and an agent.
For example, shareholders in a bank may object that management has set
the bar too low on loan approvals, thus taking on too great a risk
of defaults.
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19. What Disputes Does Agency Theory Address
• Agency theory addresses disputes that arise primarily in two key areas: A
difference in goals or a difference in risk aversion. Management may desire to
expand a business into new markets, focusing on the prospect of short-term
profitability and elevated compensation. However, this may not sit well with a
more risk-averse group of shareholders, who are most concerned with long-term
growth of earnings and share price appreciation.
• There could also be incompatible levels of risk tolerance between a principal and
an agent. For example, shareholders in a bank may object that management has
set the bar too low on loan approvals, thus taking on too great a risk of defaults.
set the bar too low on loan approvals, thus taking on too great a risk of defaults.
• What Are Effective Methods of Reducing Agency Loss?
• Agency loss is the amount that the principal contends was lost due to the agent
acting contrary to the principal's interests. Chief among the strategies to resolve
disputes between agents and principals is the offering of incentives to corporate
managers to maximize the profits of their principals. The stock options awarded
to company executives have their origin in agency theory and seek to optimize
the relationship between principals and agents. Other practices include tying
executive compensation in part to shareholder returns.
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20. Case Studies (Examples)
• 1. The Enron Scandal
• One particularly famous example of the agency problem is that of Enron.
Enron's directors had a legal obligation to protect and promote investor
interests but had few other incentives to do so. But many analysts believe
the company's board of directors failed to carry out its regulatory role in
the company and rejected its oversight responsibilities, causing the
company to venture into illegal activity. The company went under
following an accounting scandal that resulted in billions of dollars in
following an accounting scandal that resulted in billions of dollars in
losses.
• Enron was, at one point, one of the largest companies in the United States.
Despite being a multi-billion dollar company, Enron began losing money
in 1997. The company also started racking up a lot of debt. Fearing a drop
in share prices, Enron's management team hid the losses by
misrepresenting them through tricky accounting—namely special purpose
vehicles (SPVs), or special purposes entities (SPEs)—resulting in
confusing financial statements.
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21. • The problems started to unfold in 2001. There were questions about
whether the company was overvalued, leading to a drop in share prices
from over ₹ 90 to under ₹ 1.1
• The company ended up filing for bankruptcy in December 2001. Criminal
charges were brought up against several key Enron players including
former chief executive officer (CEO) Kenneth Lay, chief financial officer
(CFO) Andrew Fastow, and Jeffrey Skilling, who was named CEO in
February 2001 but resigned six months later.
February 2001 but resigned six months later.
• The collapse of energy giant Enron in 2001 showed how catastrophic the
agency problem can be. The company's officers and board of directors,
including Chairman Kenneth Lay, CEO Jeffrey Skilling and CFO Andy
Fastow, were selling their Enron stock at higher prices due to false
accounting reports that made the stock seem more valuable than it truly
was. After the scandal was uncovered, thousands of stockholders lost
millions of dollars as Enron share values plummeted.
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22. • 2. Executive Compensation and WorldCom
• When an executive uses company assets to underwrite personal loans, the agency
problem occurs as the company takes on debts to provide its executives with
higher incomes. In 2001, WorldCom CEO Bernard Ebbers took out over ₹ 400
million in loans from the company at the favorable interest rate of 2.15 percent.
WorldCom did not report the amount on its executive compensation tables in its
annual report. Details of the loans did not come out until the company's
accounting scandal hit the news late that year.
• 3. The Boeing Buyback
• 3. The Boeing Buyback
• Aerospace leader Boeing offers an instructive example of how the agency
problem occurs in capital markets. From 1998 to 2001, Boeing had more than
130,000 shareholders. Most of those shareholders were Boeing employees who
purchased company stock through their 401(k) retirement plans. At the same
time, Boeing was planning on buying back much of its stock, driving down its
share price.
• The actions of the executives in charge of caring for the company damaged the
value of its employees' retirement accounts.
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23. Resolving Agency Conflicts
• 1. Creating incentives for employees: If agents are acting in their
own interests, changing incentives to redirect these interests may be
beneficial for principals. “For example, establishing incentives for
achieving sales quotas may result in more sales people reaching
daily sales goals. If the only incentive available to sales people is
hourly pay, employees may have an incentive discouraging sales”.
• 2. Using the market for corporate control: The most frequent
example of market discipline for corporate managers is the hostile
example of market discipline for corporate managers is the hostile
takeover, in which bad managers damage shareholders’ interests by
failing to realize a corporation’s potential value. The solution is to
provide an incentive for better management to take over and
improve operations. Even better:
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24. 3. Block-chain Solutions for Agency Problems
• Blockchain technology allows for the non-existence of internal and external monitoring
that is necessary in corporate governance. The technology allows for guarantees to build
trust to overcome agency problems. It's easier for a company to be efficient by lowering
agency costs and relationship.
• Blockchain offers solutions to agency problems by moving former supervisor tasks to a
decentralized computer network that is not depended on human mistake or
greed. Blockchain eliminates agency costs such as supervising agents by creating a
trusting relationship between the agent and the principal.
• The participating principals and agents will have guarantees that directly address corporate
governance problems. Given the blockchain guarantees, this kind of technology allows for
governance problems. Given the blockchain guarantees, this kind of technology allows for
a different solution to agency problems.
• Blockchain and its security system are immutable, which creates trust between the parties
in their contractual relationship. Therefore, no party can bend the rules in the blockchain
code. The principal has no reason to monitor agency costs since blockchain addresses the
agency problems in corporate governance.
• Agency governance continues without intermediaries in the blockchain such as principal
control, third-party risk, and intermediaries, as well as market performance and private
investors. Controls and verifications, including regular meeting with shareholders, finance
disclosures, financial press, and hedge fund investors, are no longer needed in the
blockchain.
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25. SP/A Theory
• SPA theory, a psychologically based theory of choice among risky
alternatives, was proposed by Lola Lopes and further developed by Lopes
and Oden.
• Lopes’ 1987 article, “The Psychology of Risk : Between Hope and Fear”
captures the idea that the emotions of hope and fear influence the choice
among risky alternatives.
• According to SPA theory, people evaluate risky alternatives by using an
objective function which has three arguments, viz., security (S), potential
objective function which has three arguments, viz., security (S), potential
(P) and aspiration (A).
• Let us consider two decision-makers who are faced with an identical risk,
or prospect D. However, they experience different degrees of fear.
Understandably, the decision maker who experiences more fear will
attach greater importance to the probability of unfavourable events,
compared to the decision maker who experiences less fear. In Lopes’
framework, the h-function for a person who experiences neither fear nor
hope is simply the identity function h(D) = D.
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26. • For a person who experiences only fear, and no hope, the h-function is strictly
convex in D. It is flat in the neighborhood of 0 and steep in the neighborhood of I
. It may be represented as:
• hs(D) = q > 1
• For a person who experiences only hope, the h-function is strictly concave in D.
It may be represented as a power function.
• h(D) = 1–(1–D), p > 1
• For a person who experiences both fear and hope, the h-function has an inverse-S
shape.
• Formally, Lopes uses a convex combination of the power functions hs and hp to
• Formally, Lopes uses a convex combination of the power functions hs and hp to
represent the case. Graphically, the four h-functions are shown below.
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27. Framing
• There can be different ways of presenting a decision problem and it
appears that people’s decisions are influenced by the manner of
presentation. A decision frame represents how a decision maker views
the problem and its possible consequences.
• Framing effect is a cognitive bias in which the brain makes decisions
about information depending upon how information is presented. It is
often used to influence decision makers and purchases. It takes advantage
of tendency for people to view the same information but respond to it in
of tendency for people to view the same information but respond to it in
different ways depending on whether a specific option is presented in a
positive frame or in a negative frame.
• To demonstrate frame dependence, Tversky and Kahneman posed simple
problems like the following to their students. The government estimates
that 600 people will die due to a deadly outbreak of Asian flu, if nothing
is done. To tackle this problem, the government is considering two
alternative programmes.
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28. • Programme A : Develop a vaccine which can save 200 lives.
• Programme B : Develop a vaccine which will stop anyone from dying provided it
works. The probability that it will work is one-third. If it doesn’t work no one
will cured.
• When students were asked to choose one of the two programmes 75% of them
chose programme A. The risk of seeing all 600 victims die was considered too
much to be compensated by the hope that all would be saved.
• Kahneman and Tversky reformulated the question and posed it to a different
group of students. To tackle the same health problem two choices were offered:
group of students. To tackle the same health problem two choices were offered:
• Programme C : Accept that 400 victims of the flu will die.
• Programme D : Cure all the 600 victims of the flu with a probability of one-third.
• When students were asked to choose between these two options, two-thirds of the
students chose programme D. The statement ‘400 would die’ scared most
students, even though it has actually the same outcome as that of programme A
above, but expressed in more dire terms, it is evident that what matters it is not
just what you ask but also how you ask.
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29. Mental Accounting
• In reality, however, people do not have the computational skills and will power to evaluate
decisions in terms of their impact on overall wealth. It is intellectually difficult and
emotionally burdensome to figure out how every short-term decision (like buying a new
phone or throwing a party) will bear on what will happen to the wealth position in the long
run.
• So, as a practical expedient, people separate their money into various mental accounts and
treat a rupee in one account differently from a rupee in another because each account has a
different significance to them.
• The concept of mental accounting was proposed by Richard Thaler, one of the brightest
stars of Behavioural finance.
stars of Behavioural finance.
• Mental accounting tends to describe the process whereby people code, categorize and
evaluate economic outcomes. It deals with budgeting and categorization of expenditures.
• Businesses, governments and other establishments use accounting to track, separate and
categorise various financial transactions. People, on the other hand, use a system of mental
accounting. The human brain is similar to a file cabinet in which there is a separate folder
(account) for each decision, which contains the costs and benefits associated with that
decision. Once an outcome is assigned to a mental account, it is difficult to view it in any
other way.
• While money does not come with labels, the human mind puts labels on it.
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30. Bernoulli Theory
• To solve St. Peters Bung Paradox, famous mathematician Daniel
Bernoulli proposed a theory.
• According to which “a person should not, accept a highly risky
investment choice if the potential returns will provide little utility or
value.”
• It further states that a person accepts risk not only on the basis of possible
losses or gains but also based upon the utility gained from the risky action
itself.
itself.
• The St. Petersburg Paradox was a question that asked, essentially, why
people are reluctant to participate in fair games where the chance of
winning is as likely as the chance of losing.
• Bernoulli’s Hypothesis solved the paradox by introducing the concept of
expected utility and stating that the amount of utility from playing a
game is a significant decision factor in whether or not to participate.
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31. Error in Bernoulli’s Theory
• 1. The longevity of the theory of expected utility proposed by Bernoulli is
all the more remarkable because it is seriously erroneous. The error in his
theory is not in what is states explicitly; rather, it lies in what it ignores or
tacitly assumes.
• To understand this, consider the following scenarios.
• Ex. Today Ram and Shyam have a wealth of ₹ 10 lakh. Yesterday, Ram
had ₹ 5 lakh and Shyam had ₹ 15 lakh. Is their happiness the same? (Do
they have the same utility?)
they have the same utility?)
• According to Bernoulli’s theory, utility depends on wealth and since Ram
and Shyam have the same wealth, they should be equally happy. Your
common sense, however, tells you that today Ram will be elated and
Shyam despondent.
• Thus, Bernoulli’s theory must be wrong.
• The happiness that Ram and Shyam experience is a function of the recent
change in wealth, in relation to the different states of wealth that define
their reference points.
Mr. Dayananda Huded 31

32. • 2. Here is another example of what Bernoulli’s theory misses. Consider Ravi
and Geeta:
• Ravi’s current wealth is ₹ 2 million.
• Geeta’s current wealth is ₹ 5 million.
• Both of them are offered a choice between a gamble and a sure thing, in lieu
of their current wealth, and they have to opt for one of them.
• Gamble : It has two equiprobable outcomes: ₹ 2 million or ₹ 5 million
• OR
• OR
• Sure Things ₹ 3 million for sure As per Bernoulli’s analysis. Ravi and Geeta
face the same choice: expected wealth of ₹ 2 million, if they opt for the
gamble or a certain wealth of ₹ 3 million, if they opt for the something.
Bernoulli would expect Ravi and Geeta to make the same choice assuming
that their utility function is the same. However, this prediction is not correct.
Bernoulli’s theory fails here as it does not allow for the different reference
points from which Ravi and Geeta evaluate their options. Imagine yourself to
be in Ravi’s and Geeta’s shoes and are likely to think as follows.
Mr. Dayananda Huded 32

33. • The sure thing of ₹ 3 million will increase my wealth (which is currently
₹ 2 million) Ravi: by 50 per cent with certainty and this is quite attractive.
The gamble provides an equal chance of increasing my wealth to ₹ 5
million or gain nothing.”
• Geeta: “The sure thing of ₹ 3 million will decrease my wealth (which is
currently ₹ 5 million) by 40 per cent with certainty, which is awful.
• The gamble provides an equal chance of not losing anything or losing 60
per cent of my wealth.”
per cent of my wealth.”
• Ravi is most likely to choose the “sure thing” whereas Geeta is most
likely to choose to gamble.” The “sure thing” makes Ravi happy but
Geeta miserable.
• Ravi is happy with the “sure thing because it guarantees an increase of 50
per cent whereas the gamble may mean that he has a 50 per cent chance
that he will gain nothing.
Mr. Dayananda Huded 33

34. • Geeta does not like the “sure” thing because it means that she will suffer
40 per cent erosion of her wealth. The “gamble” apppeals to her because
it offers a 50 per cent chance that she can protect her wealth.
• Neither Ravi nor Geeta thinks in terms of states of wealth. Ravi thinks of
gains, Geeta thinks of losses.
• While the possible states of wealth they face are the same, the
psychological outcomes they assess are entirely different.
• Since Bernouilli’s model lacks the idea of a reference point, expected
• Since Bernouilli’s model lacks the idea of a reference point, expected
utility theory ignores the fact that the outcome that appeals to Ravi is not
acceptable to Geeta.
• Bernouilli’s model can explain Ravi’s risk aversion but it cannot, explain
Geeta’s preference for a gamble. Her risk-seeking behaviour is similar to
what is often observed in entrepreneurs and military generals when all the
options they face are bad.
Mr. Dayananda Huded 34

35. 7 R theory
• 1. Remuneration (salary)
• 2. Rate of return on business income
• 3. Return on investment
• 4. Rent on house (Rental income)
• 5. Rights or royalty on books or patents
• 6. Royalty
• 7. Franchising fees (Replication)
• 7. Franchising fees (Replication)
Mr. Dayananda Huded 35

36. Mr. Dayananda Huded 36
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