Behavioral Finance 1-1. Chapter 5 Heuristics and Biases

Transcription

1 Behavioral Finance 1-1 Chapter 5 Heuristics and Biases 1

2 Introduction 1-2 This chapter focuses on how people make decisions with limited time and information in a world of uncertainty. Perception and memory are imprecise filters of information & the way in which information is presented, that is, the frame, influences how it is received. 2

3 Introduction (cont d) 1-3 People have developed shortcuts or heuristics to come up w/ reasonable decisions. B/c too much information is difficult to deal with Representativeness heuristics The most important heuristics that designed to estimate probability 3

4 Introduction (cont d) 1-4 Anchoring tendency to change one s view more slowly than is appropriate. 4

5 Perception and processing constraints 1-5 Perceptions Influenced by expectations People see what they want to see. Cognitive dissonance a situation involving conflicting attitudes, beliefs or behaviors.. Or when people simultaneously hold two thoughts, which are psychologically inconsistent 5

6 Perception and processing constraints E.g. Voters in a Canadian election were surveyed either before or after leaving the ballot box Respondents were more likely to believe that their candidate was the best choice and would be victorious if surveyed after voting rather than before unconscious coalescence of actions and views Festinger's (1957) We have an inner drive to hold all our attitudes and beliefs in harmony and avoid disharmony (or dissonance)

7 Memory 1-7 Memory: NOT a simple matter of information retrieval: Reconstructive Variable in intensity: with emotion playing a role events are remembered more vividly when they arouse emotions Self-serving distortion: hindsight bias When people look back, they do not have perfect memory; they tend to fill in the gaps w/ what they prefer to believe. prevent from learning from the past 7

8 Hindsight Bias 1-8 I knew it all along! tend to perceive that the event was predictableeven if it wasn t Actual outcomes are more readily grasped by people s minds than the infinite array of outcomes that could have but didn t materialize Therefore, people tend to overestimate the accuracy of their own predictions 8

9 Framing effects 1-9 Perception and memory are influenced by context, or the frame E.g. How tall is that sports announcer? Looks short when interviewing a basketball player, but tall when interviewing a jockey (contrast effect) Primacy effect(what comes first has greater impact) vs. recency effect (what comes last has greater impact) Halo effects: Someone who likes one outstanding attribute of an individual likes everything about the individual 9

10 Framing effects 1-10 A B Contrast effect: Which line is longer? 10

11 Heuristics 1-11 Heuristics or rules-of-thumb: decision-making shortcuts. A heuristics is a decision rule that utilizes a subset of the information set Necessary because the world, being a complicated place, must be simplified in order to allow decisions to be made. Heuristics often make sense but falter when used outside of their natural domain. 11

12 Type 1 & 2 heuristics 1-12 Type 1: Autonomic, non-cognitive, and economize on effort. Used when very quick choice called for Or when it s no big deal I choose a hamburger over a hot dog b/c I usually prefer them. Type 2: Cognitive & requiring effort. Used when you have more time to ponder No, I will choose the hot dog today b/c it is prepared a bit differently and I like to try new things. Type 2 can overrule Type 1. 12

13 Self-preservation heuristics 1-13 Hear a noise with an unknown source? Move away till you know more Food tasting off? Stop eating it These make good sense. Other heuristics, which are more cognitive, are related to comfort with the familiar. People are more likely to accept a gamble if they feel more competent 13

14 Example: Ambiguity aversion 1-14 Drawing a red (or black) ball from an urn known to have 50 black & 50 red balls vs. drawing one from the urn containing 100 balls of black and red balls in unknown proportions People prefer risk to uncertainty. Risk exists when we precisely know the probability dist n, while uncertainty exists when we don t know it. Lesson: people are more comfortable with risk vs. uncertainty (ambiguity). 14

15 Example: Diversification heuristic 1-15 People like to try a little bit of everything when choices are not mutually exclusive. Observe people at a buffet Nobody wants to miss out on something good People hate losing options, even if they are bad ones. People love diversification, even when it is pointless and costly. 15

16 Example: Diversification heuristic factors to drive diversification 1) Many people have a hardwired preference for variety and novelty. 2) Future preferences embody some uncertainty. 3) It makes your choice simpler, thus saving time and reducing decision conflict. 16

17 Diversification experiment I 1-17 Experimental finding options that threaten to disappear cause decision makers to invest more effort and money in keeping these options open, even when the options themselves seem to be of little interest Shin (MIT) & Ariely (MIT), 2004, Keeping doors open: The effect of unavailability on incentives to keep options viable. Management Science, 50,

18 Diversification experiment I 1-18 First, pick a door. 18 Shin, J. (MIT) & Ariely, D. (MIT), 2004, Keeping doors open: The effect of unavailability on incentives to keep options viable. Management Science, 50,

19 Diversification experiment I 1-19 Then click on the payoff box for some unknown amount (avg. 3 per click). $ 19

20 Diversification experiment I 1-20 Then click on the payoff box for some unknown amount (avg. 3 per click). 50 clicks total. Earn as much money as possible $ 20

21 Diversification experiment I 1-21 Can continue to click on the payoff button. Or can click to switch doors. But, switching uses up one of your 50 clicks $ 21

22 Diversification experiment I 1-22 All doors have the same average value (3 ). What is the best strategy? $ 22

23 If all doors have the same average value (3 ), the best strategy is a) Never switch doors because switching uses a click b) Use ⅓ of clicks on red door, ⅓ on blue, ⅓ on green c) Use ½ of clicks on one door and ½ on another door d) Switch doors on every other click e) Switch doors randomly 1-23 $ 23

24 Diversification experiment I 1-25 Participants explicitly told: These doors all have the same average payoff. Did they switch doors during the game? $ 25

25 Diversification experiment I 1-26 Participants explicitly told: These doors all have the same average payoff. The average number of switches: about $ 26

26 Diversification experiment I 1-27 New twist: Each time a door is clicked, the others shrink 1/15 th. At the 15 th time without being clicked they disappear $ 27

27 Diversification experiment I 1-28 All doors still have same average payout. Does the best strategy change? $ 28

28 If all doors have the same average value, but unclicked doors eventually disappear, the best strategy is 1-29 a) Never switch doors because switching uses a click b) Use ⅓ of clicks on red door, ⅓ on blue, ⅓ on green c) Use ½ of clicks on one door and ½ on another door d) Switch doors on every other click e) Switch doors randomly $ 29

29 Diversification experiment I 1-30 Participants explicitly told: These doors all have the same average payoff. Did they switch doors during the game with disappearing doors? $ 30

30 Diversification experiment I 1-33 Similar results if switching costs a click and 3. if you could make the door come back. if the disappearing doors have a lower payoff $ 33

31 Can diversity bias (the irrational desire to avoid losing options) apply to dating? 1-34 Prof. Dan Ariely s comments 34

32 Diversification experiment II 1-35 Diversification, if done to reduce risk in one s wealth portfolio, can be a great idea Good financial planning requires each individual to use his/her wealth to buy a sensible mix of different assets, such as stocks, bonds, real estate, etc. But naïve diversification that is done simply because one is overwhelmed by a complex choice can cause serious problems. One extreme is 1/n heuristic 35

33 Example: Status quo bias or endowment effect What you currently have seems better than what you do not have. Stick w/ what you have unless there are strong reasons for doing otherwise. It could either be viewed as an implication of prospect theory or as a heuristic w/ potential for bias Experimental subjects valued something that they possessed (after it was given to them) more than they would have if they had to consciously go out and buy the item

34 Example: Information overload 1-37 Experiment involving tasting jams and jellies in a supermarket. Treatment 1: Small selection. Treatment 2: Large selection. Which attracted more interest? Treatment 2. Which lead to more buying? Treatment 1. 37