Behavior in a Simplified Stock Market: the Status Quo Bias, the Disposition Effect and the Ostrich Effect
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Belief in Mean Reversion and the Disposition Effect
Belief in Mean Reversion and the Disposition Effect: An Experimental Test By Peiran Jiao* Claremont Graduate University Current Version: October 28, 2013 Abstract The disposition effect refers to the investors’ tendency to disproportionately sell more gaining assets than losing ones. This paper experimentally evaluates two of its important competing behavioral mechanisms: belief in mean reversion and prospect theory. In the experiment, fully 61% of the participants significantly exhibited the disposition effect. I use the participants' elicited risk preferences, and beliefs about price movements to explain their selling decisions, and find that belief in mean reversion alone explains 17% of the between-subject variation in the disposition effect. The prospect theory parameters and demographic variables turn out to be insignificant after controlling for beliefs. Additionally, the results from a goodness-of-fit test on the predicting performance of the two models also favor the belief mechanism. JEL classification: C91, D03, G02 Keywords: the disposition effect, belief in mean reversion, prospect theory, experimental test ________________________ * Department of Economics and Center for Neuroeconomics Studies, Claremont Graduate University, 150 East 10th Street, Claremont, CA 91711-6165 (e-mail: [email protected]). The author thanks Paul Zak, Joshua Tasoff, Sean Flynn, and participants at the 2013 Bay Area Behavioral and Experimental Economics Workshop, the Western Economics Association International 2013 annual conference, and the Economic Science Association 2013 North-American conference for helpful comments on the manuscript. 1 I. Introduction Despite the common adage to “let your profits run and cut your losses,” which has been embedded in various forms of investor education, individual investors in the financial markets often do the opposite. -
Infographic I.10
The Digital Health Revolution: Leaving No One Behind The global AI in healthcare market is growing fast, with an expected increase from $4.9 billion in 2020 to $45.2 billion by 2026. There are new solutions introduced every day that address all areas: from clinical care and diagnosis, to remote patient monitoring to EHR support, and beyond. But, AI is still relatively new to the industry, and it can be difficult to determine which solutions can actually make a difference in care delivery and business operations. 59 Jan 2021 % of Americans believe returning Jan-June 2019 to pre-coronavirus life poses a risk to health and well being. 11 41 % % ...expect it will take at least 6 The pandemic has greatly increased the 65 months before things get number of US adults reporting depression % back to normal (updated April and/or anxiety.5 2021).4 Up to of consumers now interested in telehealth going forward. $250B 76 57% of providers view telehealth more of current US healthcare spend % favorably than they did before COVID-19.7 could potentially be virtualized.6 The dramatic increase in of Medicare primary care visits the conducted through 90% $3.5T telehealth has shown longevity, with rates in annual U.S. health expenditures are for people with chronic and mental health conditions. since April 2020 0.1 43.5 leveling off % % Most of these can be prevented by simple around 30%.8 lifestyle changes and regular health screenings9 Feb. 2020 Apr. 2020 OCCAM’S RAZOR • CONJUNCTION FALLACY • DELMORE EFFECT • LAW OF TRIVIALITY • COGNITIVE FLUENCY • BELIEF BIAS • INFORMATION BIAS Digital health ecosystems are transforming• AMBIGUITY BIAS • STATUS medicineQUO BIAS • SOCIAL COMPARISONfrom BIASa rea• DECOYctive EFFECT • REACTANCEdiscipline, • REVERSE PSYCHOLOGY • SYSTEM JUSTIFICATION • BACKFIRE EFFECT • ENDOWMENT EFFECT • PROCESSING DIFFICULTY EFFECT • PSEUDOCERTAINTY EFFECT • DISPOSITION becoming precise, preventive,EFFECT • ZERO-RISK personalized, BIAS • UNIT BIAS • IKEA EFFECT and • LOSS AVERSION participatory. -
John Collins, President, Forensic Foundations Group
On Bias in Forensic Science National Commission on Forensic Science – May 12, 2014 56-year-old Vatsala Thakkar was a doctor in India but took a job as a convenience store cashier to help pay family expenses. She was stabbed to death outside her store trying to thwart a theft in November 2008. Bloody Footwear Impression Bloody Tire Impression What was the threat? 1. We failed to ask ourselves if this was a footwear impression. 2. The appearance of the impression combined with the investigator’s interpretation created prejudice. The accuracy of our analysis became threatened by our prejudice. Types of Cognitive Bias Available at: http://en.wikipedia.org/wiki/List_of_cognitive_biases | Accessed on April 14, 2014 Anchoring or focalism Hindsight bias Pseudocertainty effect Illusory superiority Levels-of-processing effect Attentional bias Hostile media effect Reactance Ingroup bias List-length effect Availability heuristic Hot-hand fallacy Reactive devaluation Just-world phenomenon Misinformation effect Availability cascade Hyperbolic discounting Recency illusion Moral luck Modality effect Backfire effect Identifiable victim effect Restraint bias Naive cynicism Mood-congruent memory bias Bandwagon effect Illusion of control Rhyme as reason effect Naïve realism Next-in-line effect Base rate fallacy or base rate neglect Illusion of validity Risk compensation / Peltzman effect Outgroup homogeneity bias Part-list cueing effect Belief bias Illusory correlation Selective perception Projection bias Peak-end rule Bias blind spot Impact bias Semmelweis -
Decision Making Under Sunk Cost Gregory Kenneth Laing University of Wollongong
University of Wollongong Research Online University of Wollongong Thesis Collection University of Wollongong Thesis Collections 2002 Decision making under sunk cost Gregory Kenneth Laing University of Wollongong Recommended Citation Laing, Gregory Kenneth, Decision making under sunk cost, Doctor of Philosophy thesis, School of Accounting and Finance, University of Wollongong, 2002. http://ro.uow.edu.au/theses/1909 Research Online is the open access institutional repository for the University of Wollongong. For further information contact Manager Repository Services: [email protected]. DECISION MAKING UNDER SUNK COST A Thesis submitted in fulfilment of the requirements for the award of the degree DOCTOR OF PHILOSOPHY from UNIVERSITY OF WOLLONGONG by GREGORY KENNETH LAING, BBus(Acc), MCom(Hons), Grad Cert Ed(Higher Ed) VOLUME 1 OF 2 SCHOOL OF ACCOUNTING & FINANCE 2002 CERTIFICATION I, Gregory Kenneth Laing, declare that this thesis, submitted in fulfilment of the requirements for the award of Doctor of Philosophy, in the School of Accounting and Finance, University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution. Gregory Kenneth Laing 19Atmh October 2002 u ABSTRACT DECISION MAKING UNDER SUNK COST Gregory Kenneth Laing This dissertation investigates whether trained professionals can be adversely influenced by sunk cost information when making financial decisions. The rational decision making model posits that sunk costs are irrelevant to choices between alternative courses of action. However, a review of the literature reveals that, contrary to the assumptions of normative theory, people do not always act in a rational manner when making financial decisions. -
1 a Work Project Presented As Part of the Requirements For
A Work Project presented as part of the requirements for the Award of a Master Degree in Economics from the NOVA – School of Business and Economics. “The disposition effect in stocks versus bitcoin” Miguel Alves Castro Nº 3116 A Project carried out on the Master in Economics Program, under the supervision of: Alexander Coutts 11th September 2019 1 “The disposition effect in stocks versus bitcoin” Abstract Cryptocurrencies have become a hot topic in finance: its price swings have gathered attention from investors therefore they have become an appealing asset to hold alongside other financial instruments. Despite this, do cryptocurrencies reflect the same investment behavior as seen in other assets? This paper aims to study irrational behavior with a focus on the disposition effect in stocks and Bitcoin. Is there a disposition effect in cryptocurrencies and, if so, how different are the effects between the two assets? The findings suggest there is disposition effect in Bitcoin, but it is stronger for stocks. Keywords: Disposition effect; Bitcoin; Investor behavior; Prospect theory 2 1. Introduction On the 17th of June 2019, Bitcoin hit $9,000 and it appears to have, arguably, gathered new interest from investors with the news of Facebook’s new cryptocurrency and the interest of more companies accepting cryptocurrencies as method of payment. In the beginning of this year, Bitcoin was priced at around $3,700 therefore representing an increase of 143% in 6 months but the volatility of this asset was best shown in 2017 where it had an increase of 1400% ($1000 to $14000 on a year basis).This helps to show how volatile Bitcoin is but also the prospect of returns on investment in such a small time frame might propel new investments in this class of assets from experienced investors and not so experienced ones. -
The Effects of Expertise on the Hindsight Bias
The Effects of Expertise on the Hindsight Bias A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Melissa A.Z. Marks Knoll, B.A., M.A. Graduate Program in Psychology * * * * * The Ohio State University 2009 Dissertation Committee: Dr. Hal R. Arkes, Advisor Dr. Thomas E. Nygren Dr. Michael C. Edwards ABSTRACT I present data from three experiments in which I explored the effects of expertise on the hindsight bias. In Experiment 1 participants read an essay about baseball or about owning a dog and then answered a 20-question true/false quiz about the baseball essay to the best of their ability (do-your-best group), as if they had not read the essay (discount group), or to the best of their ability even though they read about owning a dog (dogs group). Participants also completed a quiz about baseball rules (measure of expertise). Results demonstrated that as participants’ baseball expertise increased, their inability to act as if they had never read the essay also increased; expertise exacerbated hindsight bias. In Experiment 2, varsity baseball players and baseball non-experts answered a 20- question quiz about baseball current events. Foresight participants answered the questions, while hindsight participants were given the questions and the answers and had to give the probability that they would have known the answers had the answers not been provided. The baseball players displayed no hindsight bias, while non-experts demonstrated the bias. To test of the effects of subjective expertise on hindsight bias, participants in Experiment 3 ranked five topics in order of expertise and gave feeling-of- knowing (FOK) ratings for 100 questions from these topics. -
AN EXPERIMENTAL ANALYSIS Benjamin Kelly A
SUNK COST ACCOUNTING AND ENTRAPMENT IN CORPORATE ACQUISITIONS AND FINANCIAL MARKETS : AN EXPERIMENTAL ANALYSIS Benjamin Kelly A Thesis Submitted for the Degree of PhD at the University of St. Andrews 2008 Full metadata for this item is available in the St Andrews Digital Research Repository at: https://research-repository.st-andrews.ac.uk/ Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/427 This item is protected by original copyright This item is licensed under a Creative Commons License Sunk Cost Accounting and Entrapment in Corporate Acquisitions and Financial Markets: An Experimental Analysis Benjamin Kelly University of St Andrews, School of Economics and Finance For the Degree of Doctor of Philosophy Date of Submission: 12th December 2006 I, Benjamin Kelly hereby certify that this thesis, which is approximately 72,000 words in length, has been written by me, that it is the record of work carried out by me and that it has not been submitted in any previous application for a higher degree. date 10/12/07 signature of candidate ……… I was admitted as a research student in October 2003 and as a candidate for the degree of Doctor of Philosophy in October 2003 the higher study for which this is a record was carried out in the University of St Andrews between 2003 and 2006 date 10/12/07 signature of candidate ……… I hereby certify that the candidate has fulfilled the conditions of the Resolution and Regulations appropriate for the degree of Doctor of Philosophy in the University of St Andrews and that the candidate is qualified to submit this thesis in application for that degree. -
Who Knew Too Much
The Man(ager) Who Knew Too Much Snehal Banerjee, Jesse Davis and Naveen Gondhi∗ July 14, 2020 Abstract Better-informed individuals are often unable to ignore their private information when forecasting others' beliefs. We study how this bias, known as \the curse of knowledge," affects communication and investment within a firm. A principal utilizes an informed manager's recommendations when investing. The curse of knowledge leads the manager to over-estimate his ability to convey information, which hampers com- munication and decreases firm value. However, this same misperception increases the manager's information acquisition and can increase value when endogenous informa- tion is indispensable (e.g., R&D). Finally, we characterize settings where the principal delegates the investment decision only if the manager is cursed. JEL Classification: D8, D9, G3, G4 Keywords: curse of knowledge, cheap talk, disclosure, delegation, belief formation. ∗Banerjee ([email protected]) is at the University of California - San Diego; Davis (Jesse Davis@kenan- flagler.unc.edu) is at the University of North Carolina - Chapel Hill; and Gondhi ([email protected]) is at INSEAD. We thank Judson Caskey, Archishman Chakraborty, Keri Hu, Navin Kartik, Nadya Malenko, Yuval Rottenstreich and seminar participants at UCSD for valuable feedback. All errors are our own. Corresponding author: Snehal Banerjee ([email protected]), Rady School of Management, University of California - San Diego, Gilman Drive #0553, La Jolla, CA, 92093. \The single biggest problem in communication is the illusion that it has taken place." | George Bernard Shaw 1 Introduction Firms routinely make decisions under uncertainty. While managers and employees \on the ground" are likely to be better informed about product demand, operational constraints, and new technologies, \top level" managers are usually responsible for the actual decision of which projects to pursue and how much capital should be invested. -
Framing and Investment Decision Making
IOSR Journal of Business and Management (IOSR-JBM) e-ISSN: 2278-487X, p-ISSN: 2319-7668. Volume 20, Issue 9. Ver. VII (September. 2018), PP 45-49 www.iosrjournals.org Framing And Investment Decision Making Anastasios D. Konstantinidis1, Konstantinos Spinthiropoulos1 , George Kokkonis1 Technological Education Institute of Western Macedonia,Greece, Corresponding Author: AnastasiosD.Konstantinidis Abstract: Framing is a cognitive heuristic, which suggests that people react differently to the choices they are asked to make depending on how these choices are presented. In the context of the stock market,framing is defined as the effect of different investment frames on investment decisions. The present paperis an attempt to make a comprehensive discussionof framing, both of routine everydaydecisions and also ofdecisions made in the specialized context of investment choices. In addition, it discusses methods to preventframing so that choices and decisions derive from rational processes. Keywords: Behavioral Finance, Framing, Psychology, biases, investment ------------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 20-09-2018 Date of acceptance: 08-10-2018 ------------------------------------------------------------------------------------------------------------------------------------------- I. Introduction In terms of thestandardfinance theory, individuals, particularly investors, always actrationallyin their effort to maximize expected utility -
Innate Biases
Academic Entrepreneurship for Medical and Health Scientists Volume 1 Issue 1 People Article 8 10-7-2019 Innate Biases Elana Meer Perelman School of Medicine, University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/ace Part of the Entrepreneurial and Small Business Operations Commons Recommended Citation Meer, Elana (2019) "Innate Biases," Academic Entrepreneurship for Medical and Health Scientists: Vol. 1 : Iss. 1 , Article 8. Available at: https://repository.upenn.edu/ace/vol1/iss1/8 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/ace/vol1/iss1/8 For more information, please contact [email protected]. The Academic Entrepreneurship for Medical and Health Scientists book project is free to all – we don’t ask for money but we truly value your feedback. Below are two links -- one to a brief feedback survey and the other to a place where you can sign up to join our community of innovators and problem solvers. You can visit them and give tell us what you think now OR after you've had the chance to read this chapter -- either one works for us! Please complete our brief feedback survey https://redcap.chop.edu/surveys/?s=HDXK3CE48L Join our growing community of Academic Entrepreneurs! https://bit.ly/3bnWTuD Innate Biases Summary • Entrepreneurs face a host of innate biases that inhibit their ability to make optimal and objective decisions under conditions of uncertainty. • Biases include overconfidence bias, illusion of control bias, anchoring and adjustment bias, confirmation bias, curse of knowledge bias, and optimism bias. • Through awareness, collaboration and inquiry, open discussion, and the deliberate challenging of consensus, entrepreneurs can mitigate these innate biases. -
Advancing Transformation with Behavioral Science a Toolkit for Post-Secondary Institutions (And Beyond)
Advancing Transformation with Behavioral Science A Toolkit for Post-Secondary Institutions (and Beyond) Authors: Piyush Tantia Cassie Taylor Rachel Taylor Uyhun Ung August 2020 About ideas42 We’re a non-profit looking for deep insights into human behavior—into why people do what they do— and using that knowledge in ways that help improve lives, build better systems, and drive social change. Working globally, we reinvent the practices of institutions, and create better products and policies that can be scaled for maximum impact. We also teach others, ultimately striving to generate lasting social impact and create a future where the universal application of behavioral science powers a world with optimal health, equitable wealth, and environments and systems that are sustainable and just for all. For more than a decade, we’ve been at the forefront of applying behavioral science in the real world. And as we’ve developed our expertise, we’ve helped to define an entire field. Our efforts have so far extended to 40 countries as we’ve partnered with governments, foundations, NGOs, private enterprises, and a wide array of public institutions—in short, anyone who wants to make a positive difference in people’s lives. ideas42’s post-secondary education team uses insights from behavioral science to help more people— particularly those from historically under-represented groups—efficiently complete college degrees that improve their economic well-being. Since 2013, ideas42 has run more than three dozen behavioral interventions that promote college access, retention, and graduation. Visit ideas42.org and follow @ideas42 on Twitter to learn more about our work. -
The Curse of Knowledge in Reasoning About False Beliefs Susan A.J
PSYCHOLOGICAL SCIENCE Research Report The Curse of Knowledge in Reasoning About False Beliefs Susan A.J. Birch1 and Paul Bloom2 1University of British Columbia, Vancouver, British Columbia, Canada, and 2Yale University ABSTRACT—Assessing what other people know and believe The source of children’s difficulty is a matter of considerable is critical for accurately understanding human action. debate. Some researchers interpret children’s difficulties on Young children find it difficult to reason about false beliefs these tasks as reflecting a conceptual deficit: Perhaps young (i.e., beliefs that conflict with reality). The source of this children lack a concept of belief or a concept of mental repre- difficulty is a matter of considerable debate. Here we show sentation more generally (e.g., Gopnik, 1993; Perner, Leekam, that if sensitive-enough measures are used, adults show & Wimmer, 1987; Wellman, 1990; Wellman et al., 2001). An deficits in a false-belief task similar to one used with young alternative view is that young children’s problems are due to children. In particular, we show a curse-of-knowledge bias more general cognitive factors such as memory and processing in false-belief reasoning. That is, adults’ own knowledge of limitations, and thus not necessarily indicative of a conceptual an event’s outcome can compromise their ability to reason limitation (e.g., Fodor, 1992; German & Leslie, 2000; Leslie, about another person’s beliefs about that event. We also 1987; Onishi & Baillargeon, 2005; Roth & Leslie, 1998; Zait- found that adults’ perception of the plausibility of an event chik, 1990; for a discussion, see Bloom & German, 2000).