the lottery mindset: investors, gambling and the stock market ||

10.1057/9781137381736preview - The Lottery Mindset: Investors, Gambling and the Stock Market, Wai Mun Fong

Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0001

The Lottery Mindset: Investors, Gambling and the Stock Market


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0001

Other Titles by the Author

Wai Mun Fong and Benedict Koh, Personal Financial Planning (Prentice Hall), 4th ed, 2011Wai Mun Fong and Benedict Koh, Personal Investments (Prentice Hall), 4th ed, 2011


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0001


Wai Mun FongAssociate Professor, National University of Singapore, Singapore


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

© Wai Mun Fong 2014

All rights reserved. No reproduction, copy or transmission of thispublication may be made without written permission.

No portion of this publication may be reproduced, copied or transmittedsave with written permission or in accordance with the provisions of theCopyright, Designs and Patents Act 1988, or under the terms of any licencepermitting limited copying issued by the Copyright Licensing Agency,Saff ron House, 6–10 Kirby Street, London EC1N 8TS.

Any person who does any unauthorized act in relation to this publicationmay be liable to criminal prosecution and civil claims for damages.

Th e author has asserted his right to be identifi ed as the author of this workin accordance with the Copyright, Designs and Patents Act 1988.

First published in 2014 byPALGRAVE MACMILLAN

Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited,registered in England, company number 785998, of Houndmills, Basingstoke,Hampshire RG21 6XS.

Palgrave Macmillan in the US is a division of St Martin’s Press LLC,175 Fift h Avenue, New York, NY 10010.

Palgrave Macmillan is the global academic imprint of the above companiesand has companies and representatives throughout the world.

Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries.

ISBN: 978–1–137–38174–3 EPUBISBN: 978–1–137–38173–6 PDFISBN: 978–1–137–38172–9 Hardback

A catalogue record for this book is available from the British Library.

A catalog record for this book is available from the Library of Congress.

www.palgrave.com/pivot

doi: 10.1057/9781137381736


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

http://www.palgrave.com/pivot

DOI: 10.1057/9781137381736.0001 v

Contents

List of Figures viii

List of Tables x

Preface xii

About the Author xiv

1 A Survey of Behavioral Finance 11.1 The behavioral finance paradigm 21.2 Investor preferences 5

1.2.1 Mental accounting 51.2.2 Preference for concentrated

portfolios 61.2.3 Preference for the familiar 71.2.4 Preference for lottery-type stocks 81.2.5 Preference for active trading 9

1.3 Heuristics 101.3.1 The availability heuristic 101.3.2 The anchoring heuristic 111.3.3 The representativeness heuristic 12

Categorical predictions 12The “law of small numbers” 14

1.4 Beliefs 151.5 Emotions 18

1.5.1 Gains and losses: Prospect Theory 181.5.2 Rejoicing and regret 211.5.3 Optimism 211.5.4 The social psychology of emotions 23

1.6 Conclusion 24


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

vi Contents

DOI: 10.1057/9781137381736.0001

2 Overtrading 252.1 Introduction 262.2 Turnover on equity markets 262.3 The profitability of individual investor trades 28

2.3.1 US studies 282.3.2 Non-US studies 32

2.4 Learning from trading 342.5 Do smart investors outsmart the market? 362.6 Why do individual investors trade so much? 37

2.6.1 Risk preferences 382.6.2 Sensation-seeking 392.6.3 Stocks as lotteries 402.6.4 Beliefs and sentiment 422.6.5 Heuristics 44

2.7 Conclusion 45

3 Trend-Chasing 463.1 Introduction 473.2 The “hot-hand” fallacy and the gambler’s fallacy 483.3 Trend-chasing in stock markets 51

3.3.1 Experimental evidence 513.3.2 Survey evidence 52

3.4 Trend-chasing: mutual fund investors 543.5 Behavioral biases of mutual fund investors 603.6 Trend-chasing behavior in the aggregate stock market 663.7 Conclusion 72Appendix: Dollar-weighted returns and institutional

ownership 72

4 Growth Stocks 774.1 Introduction 784.2 The value premium revisited 78

4.2.1 The US value premium 794.2.2 The international value premium 81

4.3 Lottery stock preference, arbitrage risk, and the value premium 85

4.4 The Persistence of lottery-stock preferences 874.5 Earnings extrapolation and the value premium 924.6 Conclusion 94


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

viiContents

DOI: 10.1057/9781137381736.0001

Appendix 4.1: Lottery factors 95Appendix 4.2: Earnings growth persistence: is it there? 97

5 The Beta Anomaly 1015.1 Introduction 1025.2 The beta anomaly around the world 103

5.2.1 US evidence 1035.2.2 International evidence 105

5.3 The beta anomaly: long-run consequences 1085.4 Omitted risks 110

5.4.1 Financial distress 1105.4.2 Liquidity risk 113

5.5 Explaining the beta anomaly 1145.6 Conclusion 117Appendix 5.1: Distress and liquidity measures 118Appendix 5.2: Institutional ownership and the

beta anomaly 120

6 The IVOL Puzzle 1226.1 Introduction 1236.2 The IVOL anomaly revisited 1236.3 Who invest in high-IVOL stocks? 1286.4 Does idiosyncratic skewness drive the IVOL effect? 1316.5 IVOL and beta 1336.6 Conclusion 137

7 The MAX Effect 1387.1 Introduction 1397.2 Sizing up the MAX anomaly 1407.3 Investor sentiment and the MAX effect 1437.4 Institutional ownership and the MAX effect 1487.5 Sentiment or fundamentals? 1507.6 Explaining the MAX effect: salience and lottery

stock preference 1537.7 Conclusion 155

8 Conclusion 156

Bibliography 159

Index 178


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0002viii

List of Figures

1.1 Portfolio pyramid 5 1.2 Prospect theory value function 20 2.1 NYSE average holding period: 1960–2012 27 2.2 Average holding period in Asian stock markets:

2003–2012 28 2.3 Net risk-adjusted returns by turnover quintiles 30 2.4 FF3 factor loadings by turnover quintiles 31 2.5 Alphas of individual investors’ buy-and-sell

trades in Taiwan 33 2.6 Net daily CAPM alphas of day traders: 1992–2006 35 2.7 Percentage of day trading volume among

unprofitable day traders: 1995–2006 36 2.8 FF4 alphas of individual investors by smartness

quintiles 37 2.9 FF4 alphas of portfolios sorted by buyer-initiated

trades and IVOL: small trades 412.10 FF4 alphas of portfolios sorted by buyer-initiated

trades and IVOL: large trades 41 3.1 Probability of attributing sequences to basketball

or coin toss 50 3.2 Stylized plot of cumulative average returns:

long-short portfolios formed on three-Month FLOW 55

3.3 Average excess returns of quintile portfolios formed on past FLOW 56

3.4 Average excess returns of quintile portfolios formed on past three-year FLOW and book- to-market (BM) ratio 59


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

ixList of Figures

DOI: 10.1057/9781137381736.0002

3.5 Average return of long-short FLOW strategy: new issues 60 3.6 Regression estimates of trend-chasing behavior: past 12-month

returns and behavioral bias proxies 63 3.7 Regression estimates of trend-chasing behavior: past 24-month

returns and behavioral bias proxies 64 3.8 Impact of a one standard deviation increase in a behavioral

bias proxy on annualized return and alpha 65 3.9 Annual scaled distribution of IO quintile 1: 1980–2011 693.10 Annual scaled distribution of IO quintile 5: 1980–2011 69 4.1 Value in December 2012 of $1 invested in July 1981 84 4.2 t-statistics of lottery factor regression coefficients 90 4.3 Subperiod alphas of size-sorted value and growth portfolios 91 4.4 Average run rates for operating income: various categories

of firms and time horizon 99 5.1 Average returns of portfolios sorted by firm size and beta 104 5.2 The beta anomaly in international markets: 1980–2012 106 5.3 Cumulative returns of beta-sorted portfolios: 1972–2012 108 5.4 Cumulative returns of beta-sorted portfolios: 1995–2012 109 5.5 Fama-McBeth regression estimates: coefficients on distress

variables 112 6.1 Fraction of IVOL effect due to overpricing of high-IVOL stocks 127 7.1 Firm characteristics of MAX portfolios 142 7.2 Average returns and alphas of MAX portfolios 143 7.3 Post-formation FF4 alphas of MAX portfolios: 1965–2007 145 7.4 Baker-Wurlger sentiment index and closed-end fund

discount: 1965–2010 147 7.5 Alphas of MAX portfolios conditional on investor

sentiment states 147 7.6 Formation period average returns of high and low-MAX

deciles by institutional ownership 149 7.7 The MAX effect in institutional ownership quintiles following

high and low investor sentiment states 151


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0003x

List of Tables

3.1 Factor analysis of behavioral characteristics of individual investors 62

3.2 Annual scaled distribution by institutional ownership quintiles 68

3.3 Predictive regressions: annual returns on lagged scaled distributions 70

3.4 Buy-and-hold returns, dollar-weighted returns and correlations between scaled distribution (SDIST) and past month returns, R(-1) across IO quintiles 71

3.5 Firm characteristics by institutional ownership quintiles 75

4.1 The US value premium: 1926–2012 804.2 The international value premium: 1981–2012 824.3 Returns of value and growth portfolios by

firm size 864.4 Excess returns and alphas of size-sorted value and

growth stocks by sub-periods 885.1 Returns and alphas of beta quintiles: 1972–2012 1055.2 Contribution of high-beta stocks mispricing

to the beta anomaly 1075.3 Returns on beta-sorted portfolios controlling

for firm distress 1115.4 Returns on beta-sorted portfolios controlling for

illiquidity 1135.5 Firm characteristics of beta-sorted portfolios 1165.6 Alphas of portfolios sorted by institutional

ownership and beta 1216.1 Returns and alphas of IVOL-sorted portfolios 125


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

xiList of Tables

DOI: 10.1057/9781137381736.0003

6.2 Returns and alphas of IVOL-sorted portfolios: longer holding periods 126

6.3 Characteristics of IVOL-sorted portfolios 1296.4 IVOL effect by institutional ownership 1306.5 IVOL effect controlling for idiosyncratic skewness 1326.6 Cross-sectional regressions with IVOL and ISKEW factors 1356.7 Time series regressions: returns of high-minus-low beta

portfolio on IVOL factor 1367.1 Descriptive statistics of MAX portfolios 1457.2 The MAX effect by institutional ownership quintiles 1507.3 FF4 alphas of MAX portfolios: sentiment and economic states 1527.4 Predictive regressions: returns of the long-short MAX

portfolio on lagged sentiment macroeconomic variables 153


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0004xii

Preface

Individual investors have a striking ability to lose money in myriad ways. This book catalogues these money-losing methods, summarizes the research evidence on how badly individual investors perform, provides new research evidence, and examines the motivations that lead indi-viduals to invest in ways which are detrimental to their wealth.

More than ever, individual investors need help to plan their finances, and grow their wealth. People today are living longer than their predecessors. Pension systems are shifting away from defined benefits plans to defined contribution plans where individuals make the call on what to invest, when to buy and when to sell. Financial markets are growing in complexity, increasing the risk that investors may be led to investment products and strategies they poorly understand. Meanwhile, the crisis-ridden decade of the 2000s is a stark reminder of how the primal forces of greed and fear can wreak havoc on household finances.

Where do individual investors stand in the midst of these dramas? Not on very solid grounds, unfortunately. Behavioral finance research shows that individuals systematically make poor investment decisions by under diversifying, overtrading, chasing past performance, and gambling in securities with lottery-like payoffs. At the same time, thanks to advances in psychology and neuro-science, behavioral scientists now have a much better understanding of the mental shortcuts used by individuals to make investment decisions.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

xiiiPreface

DOI: 10.1057/9781137381736.0004

This book examines common mental shortcuts that influence the investment decisions of individual investors. Drawing on existing and new research, it summarizes the behavioral motivations and detrimental impact of investment strategies that are popular with individual inves-tors. My hope is that readers of this book will become more cognizant of their own behavioral biases, avoid serious investment missteps, and learn to become more successful investors.

Reforming one’s behavior is never easy because many of our decisions are made subconsciously by what Nobel laureate Daniel Kahenman calls System I. System I is the source of intuitive thinking. System I is quick, automatic, and effortless but as Kahneman puts it, it is also “the origin of much that we do wrong.” Yet there is hope because each of us is also endowed with System II. Slow, deliberate, and effortful, System II is the very essence of rational thinking. Reading this book is a System II activity. Hopefully, doing so will put us on the road to making better investment decisions.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0005xiv

About the Author

Wai Mun Fong is associate professor of Finance in the National University of Singapore (NUS). Having graduated with a PhD in 1992 from the Manchester Business School, he spent several years in institutional portfolio manage-ment before joining NUS, where has taught Corporate Finance, Research Methods and currently teaches a course in Personal Finance and Private Wealth Management. Wai Mun has written as two textbooks, Personal Investing and Personal Financial Planning (Prentice-Hall) and also published widely in leading journals in areas such as applied econometrics, empirical asset pricing, investments and behavioral finance. He has extensive experience in advising many organizations in Singapore including ANZ Bank, CapitaLand, Citibank, DBS Bank, Ernst and Young, and United Overseas Bank.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

DOI: 10.1057/9781137381736.0006 1

1A Survey of Behavioral Finance

Abstract: This chapter presents the core ideas of behavioral finance. We provide a glossary of terms used in the field which will be referred to extensively in later chapters. We also provide a brief survey of the literature on important behavioral drivers of investment choice: investor preferences, beliefs, heuristics, and emotions. Lastly, drawing on the research findings of neuroeconomics, the neural basis of rewards, beliefs, heuristics, and emotions that affect investor behavior will be discussed.

Keywords: beliefs; emotions; heuristics; preferences; utility maximization

Fong, Wai Mun. The Lottery Mindset: Investors, Gambling and the Stock Market. Basingstoke: Palgrave Macmillan, 2014. doi: 10.1057/9781137381736.0006.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

2 The Lottery Mindset

DOI: 10.1057/9781137381736.0006

1.1 The behavioral finance paradigm

Much of academic research in finance is built on the idea that inves-tors are rational. Investors in these models maximize utility using all relevant information to construct “optimal” portfolios to balance risk and returns. These rational investors hold well-diversified portfolios to eliminate idiosyncratic risks that are not rewarded in efficient markets. They eschew active trading and follow buy-and-hold strategies that economize on trading costs.

Psychology research shows that real investors do not behave this way. Behavioral finance, which borrows heavily from psychology, has produced considerable evidence that most individual investors under-diversify (Barber and Odean, 2000; Goetzmann and Kumar, 2008), exhibit a “home bias” in their portfolios (French, 2008; Solnick and Zuo, 2012), trade excessively (Odean, 1999; Barber and Odean, 2000), and show a strong preference for speculative (“lottery-type”) securities such as those with high idiosyncratic volatility and high idiosyncratic skewness (Kumar, 2009; Mitton and Vorkink, 2007). There is also evidence that individual investors chase returns both directly and via mutual funds (Ippolito, 1992; Chevalier and Ellison, 1997; Bange, 2000; Frazzini and Lamont, 2008; Barber, Zhu and Odean, 2009a, b; Fong, 2014). Importantly, the average individual investor does all of these to his detriment.

In light of the growing body of evidence that investors are not completely rational, finance is evolving a new paradigm featuring inves-tors who often act under the influence of behavioral biases, who trade on noise as if it were information, and who are sometimes driven by emotions and sentiment.

Behavioral finance is a big part of this new paradigm. The first behavioral finance paper published in a top-ranking journal appeared only in 1972 (Slovic, 1972). Since then, behavioral finance research has gradually gained momentum. Two decades later, the profession was confident enough to present an edited volume of collected papers with the title, Advances in Behavioral Finance. The editor was Richard Thaler, a pioneer in behavioral finance research. About the same time, two psychologists, Daniel Kahneman and Amos Tversky, made seminal contributions to the study of individual behavioral biases which inspired a large volume of research in both theoretical and behavioral finance.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

3A Survey of Behavioral Finance

DOI: 10.1057/9781137381736.0006

Kahneman and Tversky (1979) gave the world, Prospect Theory and its offshoot, Cumulative Prospect Theory (Tversky and Kahneman, 1992) as alternative models of how people actually make decisions as opposed to how they are supposed to act. In a series of path-breaking papers, they provide convincing evidence that the carriers of utility are gains and losses rather than final wealth, and that people’s judgment is heavily influenced by how a problem is framed (whether as gains or losses), their point of reference, and a host of other mental heuristics such as the availability heuristic, the representativeness heuristic, and anchoring (see Kahneman, 2011). These heuristics are mental short-cuts that produce quick solutions to the problems people face. While heuristics can lead to accurate decisions when the environment is predictable and the decision-maker has true expertise (think doctors and engineers), they can also lead to errors of judgment outside these domains. Moreover, due to deep-seated cognitive biases, these errors of judgment may become systematic: people may repeat these mistakes over and over again.

This is not a textbook on behavioral finance nor does it provide an in-depth survey of behavioral finance research. For readers who wish to get acquainted with the seminal ideas of Kahneman and Tversky, I recom-mend Kahneman’s (2003) insightful essay, “Maps of bounded rationality.” Kahneman’s recent book, Thinking Fast and Slow (2011) gives an authoritative and engaging account of the self-delusions that people fall prey to. There are also many excellent surveys of behavioral economics and finance. Early surveys include Thaler (1993), Rabin (1998), and Daniel, Hirschleifer, and Teoh (2002). Subrahmanyam (2008), Debondt et al. (2008), and Barber and Odean (2013) are more recent reviews of the literature.

This book is primarily about how individual investors reduce their wealth through suboptimal investment strategies. As we will show in the subsequent chapters, behavioral biases play a big role in explaining why individual investors persistently engage in money-losing strategies.

In general, people’s investment decisions are shaped by four factors: preferences, beliefs, mental heuristics, and emotions. An investors’ pref-erence for one type of investment over others is driven by his goals and risk tolerance. While the traditional view is that all investors are risk-averse, in reality, people can be both risk-averse and risk-seeking. As Friedman and Savage (1948) pointed out long ago, people may purchase both insurance and lotteries. Shefrin and Statman (2000) developed behavioral portfolio theory to account for this behavior.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

4 The Lottery Mindset

DOI: 10.1057/9781137381736.0006

Investors’ investment choices also depend on their beliefs about financial markets and about their investment skills. A robust finding from psychology is that people are overconfident about their abilities to perform a variety of tasks such as driving, forecasting election outcomes and picking stocks (see, e.g., Alpert and Raiffa, 1982; Lichenstein, Fischhoff and Phillips, 1982; Odean, 1999). In experiments, overcon-fidence is manifested by subjects expressing overly narrow confidence intervals. Overconfidence is a powerful explanation of why investors prefer undiversified portfolios despite their patchy record of earning positive alphas from stock picking.

Investors’ beliefs are influenced by what others think. When most investors become overly optimistic or pessimistic about the market, sentiment-driven trading results. Keynes (1936) points out the possibil-ity that significant numbers of sentiment-driven traders in the market can cause asset prices to deviate from their fundamental values. Shiller (2008) argues that investor sentiment, mediated by social contagion or herd behavior, accounts for some of the most spectacular episodes of stock market booms and crashes.

As noted, mental heuristics are rules of thumb that people use to find adequate but often imperfect solutions to complex problems. We use heuristics because it is mentally taxing to work out the ideal solution especially under the pressure of time. According to Kahneman (2011), the human brain operates at two levels in making judgments: System I and System II. System I provides quick and automatic solutions to a problem, while System II is slow, deliberate, and thoughtful. Heuristics are invoked when System I is in action. The many cognitive biases that influence individual investors indicate that people often rely on heuris-tics to make investment decisions, perhaps to a greater extent than they realize.

Finally, our investment decisions are also influenced by emotions, particularly, pleasure from gains, pain from losses, pride, and regret. While scientists still do not have a complete theory of how emotions govern risk-taking activities, evidence from brain imaging studies clearly show that brain areas that govern emotional states significantly influence people’s attitude toward risk and rewards.

The rest of this chapter summarizes research findings from psychol-ogy, neuroscience, and behavioral finance concerning the key factors that drive investors’ preferences, beliefs, use of heuristics, and sensitivity to emotions.


Co

pyr

igh

t m

ater

ial f

rom

ww

w.p

alg

rave

con

nec

t.co

m -

lice

nse

d t

o G

eorg

ian

Co

urt

Un

iver

sity

- P

alg

rave

Co

nn

ect

- 20

14-1

2-06

This is a preview which allows selected pages of this ebook to be viewed without a current

Palgrave Connect subscription. If you would like access the full ebook for your institution please

contact your librarian or use our Library Recommendation Form

(www.palgraveconnect.com/pc/connect/info/recommend.html), or you can use the 'Purchase

Copy' button to buy a print copy of the title.

If you believe you should have subscriber access to the full ebook please check you are accessing

Palgrave Connect from within your institution's network or you may need to login via our Institution

/ Athens Login page (www.palgraveconnect.com/pc/nams/svc/institutelogin?target=/index.html).


Wai Mun Fong

ISBN: 9781137381736

DOI: 10.1057/9781137381736preview

Palgrave Macmillan

Please respect intellectual property rights

This material is copyright and its use is restricted by our standard site license terms and conditions

(see palgraveconnect.com/pc/connect/info/terms_conditions.html). If you plan to copy, distribute or

share in any format including, for the avoidance of doubt, posting on websites, you need the

express prior permission of Palgrave Macmillan. To request permission please contact

[email protected].

the lottery mindset: investors, gambling and the stock market ||

Documents