CFA 2018 level 3 gostudy traditional vs behavioral finance (r5)

We then move from the theory of how a market should work to introduce some behavioral challenges to this efficient market hypothesis.. Key testable material / what you need to be able to

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Guided Notes for CFA® Level 3 – 2016

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Contents

Behavioral Finance (Study Session 3) 3

Traditional versus Behavioral Finance (Reading 5) 4

The Rational Economic Man and Efficient Markets 5

The CAPM Model 6

Tweaks of the Efficient Market Hypothesis 6

Utility Theory 7

Challenging EMH 9

Behavioral Finance Frameworks 11

Summarizing the BF Frameworks 14

Behavioral Finance (Study Session 3)

This is an important topic It will probably be tested in the morning in an IPS question, as part of

a stand-alone constructed response, and it could even show up in an item set in the afternoon accounting for up to 10% of the exam That alone would make it worth a lot of time But the themes found in the behavioral finance section also echo throughout the entire CFA L3

curriculum

Take portfolio management for example The core of L3 is knowing the basic stuff that goes into managing someone else’s money People aren’t robots after all! Thus to do a good job managing money you have to be aware of your clients’ unique financial circumstances, knowledge of

finance, and their personality traits

The overarching point of this section is that only by treating clients as unique individuals can

we, as portfolio managers, create tailored strategic asset allocation plans that also mitigate their weird quirks or sub-optimal behaviors (through education or accommodation)

Bottom line: Knowing this section cold will let you score points and save valuable time

The outline of this section

Like the CFA Institute curriculum we start from a very high level market wide perspective by defining the idea of an efficient market We then move from the theory of how a market should

work to introduce some behavioral challenges to this efficient market hypothesis From there we

think through the various challenges that people’s emotional and mental reaction to financial markets creates for managing their portfolios After that we turn to identifying and categorizing the different emotional and cognitive biases that investors (and analysts) can face Finally we end with three frameworks for classifying investors into different behavioral groups

We spend a good deal of time in the beginning of this section because understanding the basic tenants of BF will let you earn a lot of points on the test throughout seemingly unrelated subjects Specifically, as we move into the core L3 readings on Individual and Institutional Portfolio Management, your ability to relate those sections to BF will let you score a lot of points So bear with us in the lengthy chapter The payoff is worth it and we promise the notes get more concise again after

Traditional versus Behavioral Finance (Reading 5)

Note that the order in which we present material for Reading 5 is, in a few cases, quite different from the order laid out in the curriculum Key testable material / what you need to be able to do after learning this reading:

 Contrast traditional finance with behavioral finance and how that impacts investor

decision making and portfolio construction

 Compare and discuss the consequences of Weak, Semi-strong form, and strong form modifications to EMH

 Describe and compare utility and prospect theory

 Talk about bounded rationality and cognitive limitations and its impact on investment decision making (satisfice, AMH)

 Describe the consumption and savings model, BAPM, and BPT and how they differ from traditional finance

In order to set up the behavioral finance discussion it helps to take a step back and think about what exactly it is that behavioral finance is modifying—traditional finance Traditional finance,

which is what we’ve dealt with throughout L1 and L2, is built on the assumptions of:

 Rational individuals

 Perfect information

 Efficient markets that quickly absorb new information

Behavioral economic theories modify these models by relaxing certain assumptions BF

acknowledges that people aren’t economic machines We are weird We don’t always act

rationally We make mistakes in processing things On top of that, perfect information doesn’t exist It’s impossible to know everything about everything at all times This means that there are informational, cognitive, and emotional challenges to the theory of efficient markets

Another way to draw the distinction between traditional and behavioral finance lies in what each

tries to do Traditional finance is normative in that it seeks to predict actions It offers theoretical

models for how people and markets are supposed to behave in an ideal scenario

Behavioral finance is descriptive or observational It looks to explain actual behavior by

modifying traditional models to examine how we actually make decisions (both on an

individual by individual level and in terms of why markets in the macro deviate from being perfectly efficient)

Again, the L3 curriculum is about the key principles of actually managing money The ultimate goal or application of behavioral finance is prescriptive, i.e it can provide practical advice and tools to achieve results that are as close to the normative ideal as possible In other words, the overarching message being conveyed here is that combining behavioral and traditional

approaches leads us to a better understanding of clients, and that makes us better portfolio managers and financial advisors

The Rational Economic Man and Efficient Markets

If traditional finance is built on the assumption of Rational Economic Man (REM), then how

does an REM act? And what does that behavior mean for financial markets?

The rational economic man acts in accordance with a few basic theories that try to define his behaviors (derived from neoclassical economics) Basically a perfectly rational economic

human:

 Thinks more (stuff) is better than less, e.g is perfectly rational/self-interested

 Thinks less risk is better than more risk all else equal, i.e is risk averse

 Has perfect information

 Uses Bayes’ formula to make probability adjusted decisions, i.e is a mathematical

genius1

The result, as we see below, is that an REM will try to obtain the highest possible utility given their budget constraints

From a market-wide perspective, traditional finance assumes that since all of these individuals base their decisions on perfect information (including past volume, price, and market/firm data) markets as a whole are also efficient Efficient here means two things:

1 The price is right: In other words, asset prices reflect all available information and prices

adjust instantaneously to incorporate that information

2 There is no free lunch: Since prices adjust immediately it is not possible to get an

informational advantage and therefore earn above-average returns In other words no

alpha is consistently possible

The result is our good friend capital market theory as represented by the CAPM This is where there is a single efficient market frontier on which investors create their portfolio using expected returns, standard deviations, and co-variances of their investments

1 In the CFA curriculum this discussion is followed by a brief explanation of Bayes’ formula for revising

expectations given new information While unlikely to be directly tested you should recognize the probability formula from L2 where: P(A|B) = P(B|A)

P(B) ∗ P(A) Where the conditional probablities [P(A|B), P(B|A) use the new probabilities given the new information)

The CAPM Model2

𝑟𝑒 = 𝑟𝑓 + 𝛽(𝑟𝑚− 𝑟𝑓)

Where:

re = The required return on equity

rf = Risk-free rate

rm = The market return

β = The stock market beta (rm-rf) = The Equity risk Premium (ERP) Thus in perfectly efficient markets it is the job of an investment manager to ID portfolios on the efficient frontier that meets the risk/reward profile of an investor

In reality, even traditional finance acknowledges that markets are unlikely to be perfectly

efficient Specifically, the assumption that all the relevant information is available and

incorporated into market prices instantly has been challenged As a result there are three

modifications to completely efficient markets that have been proposed

Tweaks of the Efficient Market Hypothesis

There are three challenges to the ‘Efficient Market Hypothesis (EMH): weak, semi-strong, and

strong Each relaxes the assumption of perfect information to a different degree Distinctions between them are often tested

Modifications to the Efficient Market Hypothesis (EMH)

Definition Prices reflect all past

price and volume data

Prices reflect all past price and volume data AND all public information

Prices reflect all past price and volume data and all public AND nonpublic information

Implications

Charts/technical trading will not lead to excess returns

Charts/technical trading AND fundamental analysis will not lead to excess returns

No excess returns possible

Significance Fundamental Analysis

can lead to alpha

Insider info can lead to

alpha No alpha possible

Challenges to these theories include fundamental anomalies (value investing, small-cap) which challenges semi-strong/strong) and technical anomalies (calendar, moving average/momentum) which challenge the weak form

2 An excellent recap of the CAPM model can be found here

Types of Market Anomalies

This is an odd stand-alone section which the curriculum adds to the end of the behavioral

finance section It shouldn’t be too important, but it exists to remind us that when investors act according to certain biases then the entire markets will behave irrationally too The best and most famous explanation of this ever is undoubtedly Benjamin Graham’s description of Mr Market.

Anomaly 1: Value vs Growth & Small-cap vs Large-cap

Value stocks have outperformed growth stocks over a period of 20 years Similarly, small cap stocks have outperformed large cap stocks over that time period The curriculum also includes a discussion about why these anomalies may not actually be anomalies—just reflections of

different type of risk

Anomaly 2: Bubbles & Crashes

Bubbles and Crashes are both symptoms of investor herding behavior which can be caused by availability bias or fear of regret (trend-chasing)

Bubbles happen during periods of irrationally high asset prices and exuberance in the markets They are usually caused by overconfidence, self-attribution, and confirmation biases Crashes are defined as a fall in market prices of > 30% They are often caused by herding behavior as a result

of the availability bias or fear of regret (trend-chasing) Don’t worry all of these terms are

explained below

Utility Theory

The concept of rational economic man and investing along a CAPM frontier should be very familiar from previous levels What hasn’t been covered before is that those concepts are

actually built on the economic theory of utility

Rational economic man is rational precisely because he makes utility-maximizing choices

When you combine rational man with a few basic assumptions about the way he or she thinks

about maximizing their own self-interests you get something called Utility Utility is just an

economic term describing how you measure your best possible outcome Its official definition is

“the level of relative satisfaction received from the consumption of a good or service.” Utility theory depends on four assumptions (which “won’t” be directly tested):3

 Completeness: Individuals know their preferences and can choose between them

 Transitivity: If A > B and B > C then, A > C

 Independence: Rankings are additive So assuming from above that B> C, the

following must be true: A + B > A +C

 Continuity: Utility curves are continuous If C> B > A then there is a combo of C

& A = B

To make the concept of Utility clearer let’s give a simple example

3 Obviously I can’t guarantee that you won’t be tested on something like this, but it’s really in the weeds

Say you have a simple tradeoff to make between working and making money on the one hand

OR hanging out but having less money on the other Obviously you need some money or

hanging out isn’t much fun But if all you do is work, your money isn’t worth much either

because you have no time to use it

The more of either leisure or work you have, the less valuable having a little bit more of that

becomes Thus utility assumes diminishing marginal returns As a consequence you maximize

your utility by choosing some combination of work and leisure that “works” for you according to

your preferences and your constraints.4

A Standard Utility Curve (IC) Plotted Against an Efficient Frontier

This works exactly the same in thinking about risk and reward tradeoffs in investing The more

wealth you have the more the expected return of an investment must increase to offset risk

That’s because each dollar you earn has less and less utility (The double-inflection utility

function)

Graphically, the fact that returns must increase at an increasing rate is represented by the shape

on the IC curve from the left of point A The less leisure time you have, the more someone is

going to have to pay you to give it up

From an investor’s perspective think of it this way Since you’re already rich you care more

about keeping what you have versus getting more Each additional dollar is subject to

diminishing returns You are risk averse because you accept less risk per additional dollar

you earn

Behavioral finance relaxes this assumption so that people can be neutral or even

risk-seeking5 depending on their level of wealth This leads to different types of behaviors in the

pursuit of wealth/investment returns

The key takeaway from this entire section is summed up in the graphs below If you know what

the graphs below are telling you and why, you know enough about this section

4 Graph from http://en.wikipedia.org/wiki/Labour_economics

5 We all have a casino-loving gambling friend after all

 All points on IC reflect same utility

 Diminishing returns and a diminishing marginal rate of substitution give the Indifference Curve (IC) its convex shape

 The straight line represents an efficient frontier and point A is the maximum obtainable utility given resource constraints

 The Concave shape of the risk-averse investor's utility function indicates diminishing

marginal utility Thus as the overall wealth increases, utility begins to increase at a

decreasing rate

 The risk-neutral investor acts as if unaware of risk (considers only returns)

 The utility function for the risk-seeking individual is convex, indicating increasing

marginal utility Thus each additional unit of wealth provides more and more utility”

Challenging EMH

So far we’ve introduced traditional finance and explained some of its key implications for how both individuals and markets behave In this section we’re going to take a more specific look at some of the alternative theories to efficient markets presented in the behavioral finance reading This coverage will be picked up again in Reading 7 on behavioral finance and asset allocation

Bounded Rationality

Bounded rationality is a key concept in understanding behavioral finance Essentially, bounded rationality states that it is impossible for every individual to have perfect information about every possible outcome for every single decision The result is that people practice satisfice

Satisfice means getting to an acceptable outcome, even if that outcome isn’t optimal or return maximizing The idea of bounded rationality + satisfice is a key behavioral finance concept because it recognizes that people:

(1) Gather some but not all available info (2) Use heuristics (rules-of-thumb) to analyze that info (3) Have intellectual/computational limits

The result is Satisfice (satisfy + suffice)

Prospect Theory

This is the first modification to traditional finance presented in the curriculum Prospect theory relaxes the assumption of utility maximization and substitutes it with loss aversion (or risk

aversion) Loss aversion is an important concept in understanding how investors actually behave

At its most basic it means that investors care more about a loss of a dollar than they do the gain

of a dollar (see more at Loss Aversion)

More generally, prospect theory assumes investors aren’t thinking about total returns, instead they are analyzing risk relative to possible gains and losses Under prospect theory investors care more about relative changes to wealth than about absolute changes

Prospect Theory

What the above graph shows is that there may be levels of return at which an investor is a risk seeker (in the convex area of losses) and levels where an investor is risk neutral or risk averse (the concave positive gain area).6 In other words, if investors fear losses they may actually take

on greater risk in an attempt to reverse them

The key testable takeaway here is that loss aversion can lead to investors selling winning stocks too early (to lock in gains) and/or holding on or even doubling down on losers

Decision making in Prospect Theory

The curriculum also discusses the framework for how investors make decisions in prospect theory

This is pretty detailed but unlikely to be directly tested Don’t burn too much time memorizing the steps

Decision making under prospect theory is a two-step process where we figure out our choices

(editing), and then evaluate those choices (evaluation phase)

The editing phase consists of an investor figuring out/clarifying the choices they can make The six steps in the editing phase are: Codification, Combination, Segregation, Cancellation, Simplification, and Dominance

6 People tend to be risk averse when there is moderate or high probability of gains or low probability of losses and people are risk seeking when there is low probability of gains or high probability of losses