Updated

Behavioral Finance L1

Prior evidence showing that high testosterone CEOs deliver better firm performance (Wong et al., 2011). Poorly informed and unsophisticated investors might lead financial market to be inefficient. Behavioural finance studies investor decision processes which in turn shed light on anomalies which depart from neoclassical finance theory (DeBondt et al., 2008). Implications and Applications of behavioural finance in many corporate events such as M&A, splits, portfolio choices (Subrahmanyam, 2007). Cause of under reaction are anchoring, loss aversion, overconfidence. Cause of overreaction is Representativeness, Availability, Herding. In traditional finance, people are rational utility maximizer, able to make unbiased forecast, perfect information processor, omniscient. In behavioural finance, people are imperfect decision maker, prone to cognitive error, poor intuitive statistician, concerned with emotion and feeling, prone to satisfies their decision rather than optimise. Traditional finance, market assume to be efficient even not all investor rational because cancel out and process of arbitrage. In behavioural finance, there is cognitive limitations. Prof Karolyi show the growing research paper for behavioural finance since 2002. Hot research in behavioural finance are: sentiment in finance such as Baker and Wurgler (2006) setup sentiment index out of proxy such as share turnover, numbers of IPOs, First day return of IPOs, Dividend Premium, cross section cited about more 1000 people.  High media pessimism predicts downward pressure on market prices followed by a reversion to fundamentals (Tetlock, 2007). High testoreron will increase firm risk, maintain high leverage ratio, more acquisitive, high risk adjusted compensation (Wong et. Al 2011).

1. DeBondt et al. (2008) Behavioral Finance, Quo Vadis
2. Subrahmanyam, (2007) Behavioral Finance, Review and Synthesis
3. Wong et al. (2011) Testosteron and CEO Performance
4. Huberman and Regev, (2001) “Contagious Speculation and a Cure for Cancer
5. Bolster et al (2009) market madness
6. Engelberg (2009) Aver 3%abnormal overnight returns following recommendations
7. Han and Hosung (2012) Gangnam Style and Father Company
8. Kim (2014) Youtube viewer and investor enthusiasm
9. Simon (1978) Bounded Rationality and Simplified model for complicated real life
10. Tetlock (2007) The role of media in finance
11. Tetlock et al (2008) Quantifying language to measure firms fundamental +- words
12. Chen and Keith (2013) Language on economic behaviour

Overconfidence L2

There are three distinct ways to define overconfidence: 1) Overestimation, 2) Overprecision, 3) Overplacement (Moore and Healy, 2008). For example, analyst recommendation, investor beat market, takeover failure hubris, corporate collapse. There are illusion of knowledge and control. The bias includes over optimism bias and self-serving attribution bias e.g. ‘lucky fool’ syndrome among market traders, attributing randomness to skill. Overconfidence also relates to confirmation bias means we see what we want to see. We can draw a concentration and motivation curve to explain the diffidence, optimal confidence and overconfidence. And negative linearity for anxiety graph. What is overconfidence positive side, impact and how to deal with? It is difficult due to hard wired, should know where is on spectrum and humility exercise. Measures of overconfidence in finance such as excessive trading activity reduce returns (Barber and Odean, 2001, Odean, 1999, Barber and Odean, 2000), late exercise of managerial options (Malmendier and Tate, 2005)and active share (Choi and Lou, 2010). The link between the overconfidence and trading relate to disposition effect when investors tend to sell securities that rising in recent week, hold if declining. Men take more risk and trade more than women(Barber and Odean, 2001). To calculate using Proportion of Gains Realized divided by Proportion of Losses Realized. Disposition effect has negative impact on portfolio returns, and it explain stock momentum (Grinblatt and Han, 2005)and under reaction to news (Frazzini, 2006). To debiase it, we need strong sell discipline, take gain and stop loss limits and frequency of looking at the screen. There is also overconfidence among fund managers, turnover impacts negatively on fund performance (Carhart, 1997). Tracking error vs Active share was proposed to measure overconfidence (Cremers and Petajisto, 2009, Petajisto, 2013). The critics for Active share such as difficult to measure, can be misleading, sensitive to benchmark definition, prone to data mining. To sum up, the proxy for overconfidence is fund manager private info through noisy and delayed feedback, place to much weight and overestimate private info, Domain specific risk taking or DOSPERT psychometric test 2.

1. Moore, and Healy, (2008)
2. Barber and Odean, (2000) Monthly Turnover and Annual Performance of Individual
3. Barber and Odean, (2001) Man vs Woman
4. Odean (1999) Investor Trade Excessively
5. Carhart (1997) Overconfidence amoung Fund Manager
6. Odean (1998) Proportion of Realized Gain or Loss
7. Frazzini (2006) Underreaction
8. Grinblatt and Han (2005) Stock Momentum
9. Cremer and Petajisto (2009) Active Share

Loss Aversion and Prospect Theory L3

Loss aversion in psychoanalysis like pain of losing not just due to the financial loss but also the associated emotions of guilt, regret and shame. I often unconscious mental defences against loss such as denial, blame and projection, rationalisation and hope. Generally faced with gain, people prefer less risk but in lottery it runs differently. Expected utility theory vs prospect theory. Prospect theory suggest that investors think in terms of gains or losses relative to some reference point such as the status quo or what the investors expects based on other people’s experience. See the prospect theory value function that loss graph is steeper than gain due to loss aversion (Barberis, 2013). Then, disposition effect (Frazzini, 2006)explain that investors generally tend to sell their winner to soon but hold on to their losers too long, it is the result of prospect theory and loss aversion. This loss become sunk cost which irrelevant for current decision making but in fact it influence, this is called sunk cost fallacy. Endowment effect refers to the fact that people require more to sell because they have feeling as owner rather than they are willing to pay for goods. The endowment effect is inconsistent with standard economic theory because willingness to pay and willingness to accept is different which underlies consumer theory or indifference curves. Then, discussing about the survival frame and mortality frame that is similar kind by giving two different questions that substantially providing similar choices. Traditional finance assume framing bias can see through different ways, or framing is transparent. Behavioural finance sees framing differently as frame dependent that perceptions are highly influenced by framing. Framing practice is opaque, actual behaviour and change in form could change in substances. Presentation in different format can alter people’s decisions such as The Shepard tables illusion. The mitigation of framing bias use familiarity and use thinking than intuition. Framing can be linked to prediction such as presenting return 20% vs presenting increase price from 5000 to 6000. It will be seen by investor differently to predict future, return forecast will continue and price forecast will be reversed. Nudge improving decisions about health, wealth and happiness (Sunstein and Thaler, 2008). Central idea design choice environment that make it easier for people to choose, give freedom of choices, libertarian paternalism, the implications many to financial regulations and products. Behavioural intervention, opt in opt out (changes to the default of policy, lead people to opt out rather opt in), status quo bias (investor tend to hold investment they currently have, the bias longer if experience lost, another explanation of disposition effect). Hindsight bias tell us that we are unable to go back in time once the result of event is known or inevitable. Debiasing hindsight because it is very pervasive and damaging, keeping formal record of predictions and investment diary. Choices of architectures called nudges. Easy, attractive, social, timely. Can successful fund manager be identified in advance, but did we know of warrant buffet ability of foresight. Effective Consent Rates. Opt In and Opt Out, Hindsight Bias. Choice of Architecture

1. Frazzini, (2006) The Disposition Effect and Under-reaction to News
2. Barberis, (2013) Thirty Years Prospect Theory
3. Kahneman and Tversky (1979) Prospect Theory
4. Sunstein and Thaler (2008) Nudge Improve Decisions about Health, Wealth and Happines
5. Behaviour Change report, House of Lords

Mental Accounting, Behavioural Investing and Financial Crises L4

Mental accounting is the process by which people code, categorize and evaluate economic outcomes. The example is cheaper calculator and laptop in different store, ticket cost and loss, credit washing machine matching cost to benefit. People mentally frame assets as belonging to either current income, current wealth or future income (Kumar and Lim, 2008). The accounts are largely non-fungible. Separate mental account between open or close to manage physiological pain. The feeling of discomfort due to conflicting cognitions called cognitive dissonance. Alpha is the amount by which the market is beaten, after adjusting for risk. Common sources of alpha are value, small cap and momentum. There are 10 financial bubbles. Common feature of crisis: asset market collapse, decline in employment and output. There also inflation crisis experiences, German sample. Sovereign debt crisis, banking crisis contagious due lending boom, panic, random deposit withdrawals and natural outgrow of business cycle economic downturn, solvency problem such as in Sweden and Japan. Who is to blame with bank crisis: regulator, government or who. Algorithmic Trading early 90s, Automated trading late 90s, High frequency trading 2000s (Lewis, 2018), market anomalies, value anomalies, different faces of value investors, passive screeners and activist value investors, post earnings announcement drift. Market anomaly is an empirical result involving asset returns that is inconsistent with market efficiency and the maintained asset pricing model, resulted in abnormal return. Value investor is one who invest in low price to book or low price to earnings stocks. Behavioural explanation for value anomaly: overreaction, extrapolation, overreaction, extrapolation, representativeness, shying away. Different faces of value investors include passive screeners: investor who screen for stocks that have characteristic of undervalued stock such as low P/E and P/B ratios and activist value investors: invest in poorly firms and change to the way company run. The tendency of drift happens due to unexpected very good or bad information and it contradict market efficiency. Behavioural explanation is that maybe investors and analyst anchored on recent earnings which means underreact to new information. Under reaction in short term followed by overreaction in long term. Self-control,mental accounting,and framing are incorporated in a behavioral enrichment of the life-cycle theory of saving called the Behavioral Life-Cycle (BLC) hypothesis (Shefrin and Thaler, 1988). Once investor know diversification from Markowitz, they don’t follow. They build layered pyramid with each layered representing goals (Shefrin and Statman, 1984). Discussing with Tom Howard, he is successful chief executive pick right stock by anonymising the stocks and masking the initial purchase price to avoid behavioural bias. Alpha is by which the market is beaten. Three categories outperform the long run: value, small cap, momentum. MSCI World Equity Annualised Returns.  Framing mode is important determinant of investor’s stock investment decision. Reinhart and Rogoff (2009) analyse major financial crises in 66 countries over a period of 800 years: asset market collapse, profound declines in output and employment, the real value of government debt tend to explode.

1. Kumar and Lim, (2008), “How do Decision Frames Influence
2. Shefrin and Statman (2000), “Behavioural Portfolio Theory”
3. Shefrin and Thaler (1988) “The behavioral life-cycle hypothesis”.
4. Reinhart and Rogoff (2009) analyse major financial crises in 66 countries.

Heuristic and Neuro Finance L5

Heuristic is mental shortcut to simplify complex judgments or decision. It leads to decision errors due to less than rational decisions. For example: Availability, Ambiguity Aversion, Diversification, Representativeness. Real example shark attack vs deer hit. Heuristic make people overestimate. Heuristic caused by the easiness to remember something then we assume. The frequency of media exposure influences the formation of heuristic. The fact that each analyst also have their own experience that form their own heuristic (Malmendier et al., 2011). Heuristic create different forms of bias such as a familiarity bias, home country bias (Bekaert and Wang, 2009), attention bias “noise trading” (Barber and Odean, 2008). Attention grabbing stocks include abnormal trading volume, extreme one day return, new stories. Retail investor are attention driven while institutional are not. Let’s see Ellsberg Paradox. There is ambiguity aversion that lead to prefer risk of uncertainty. The risk is probability distribution known while uncertainty unknown. Known unknown vs unknown unknown. This ambiguity aversion closely related to diversification heuristic. Conjunction fallacy is the combination of two events is more likely than one on its own. Remember winning lottery and being happy ven diagram. This is special form of representativeness heuristic: stereotypes, similarity, Other factor influence judgment. Representativeness example is dotcom and fund style name changes, company name changes (Cooper et al., 2001). Dotcom produce 74% abnormal returns of 10 days surrounding the announcement day, positive reaction. A more recent example is blockchain. Heuristic could lead to stock recommendation bias based on company attractiveness and blindly trusting fund managers also affinity fraud. Biases related to representativeness include insensitivity to sample size, and ignoring base rate frequencies (base rate fallacy, base rate neglect). Gambler fallacy[1], Anchoring and Adjustment, Anchoring in Auction and Finance. Move to heuristic and human brain or neuro finance using brain imaging fMRI, human brain tested using Cognitive Reflection test. Cognitive burden (Shiv and Fedorikhin, 1999), having subject to remember and giving choice to eat. Time discounting results from combined influence of two neural systems: emotional system is impatient and analytic frontal system is patient. Emotional brain responds little to delayed rewards and create taste for instant gratification.

1. Barber and Odean (2008) the Effect of Attention and News on the Buying
2. Cooper et al (2001) study firm name changes during the dotcom era
3. Shiv and Fedorikhin (1999) cognitive burden
4. Malmendiar, Tate, Yan (2011) overconfidence and Early Life Experience
5. Bekaert and Wang (2009) ranking countries by home bias
6. Frederick (2005) CRT

Herding L6

Public opinion only exists when there are no ideas (Wilde, 1894). Herding exist due to social pressure of conformity, sociable human nature, common rationale, less regret. Herding explained with FSS model (Forbes, 2009)where asset trade v (value of asset) = a + b (two distinct attributes to value). There are three types of traders such as informed speculators, uninformed traders and a competing set of market makers. Thus, the informed speculator will choose a or b is up to them. They then execute the trading based on the information a or b at day 1. Market market close half of the trading at day 1 with price 1. Then completed trading close at day 2 with price 2. The value with probability alpha will be revealed at day 3 or if not with probability 1-a in day 4. After all, the implication of FSS model are the negative spill overs if alpha is 1 and positive spill overs if alpha is 0. In negative spill over, the trader doesn’t want others to follow his strategy in order for him to make profit. In positive spill over, the trader wants others to follow him in order to be profited from the follower. Negative spill over is in the long trading horizon, wait until all fully revealed, encourages the collection and use wide variety of information. Positive spill over is in the short-term trading horizon, focus on information others will later be easily able to pick up on, collecting truly fundamental information may be less important than eye catching information. Think of Chartism[2]. Institutions consistently pile into a fairly narrow set of stocks driving their price and returns to holding them up (Nofsinger and Sias, 1999). Some confounding effect of momentum, but even allow for that, institutional shareholders enter and reap profits in narrow segments of equity markets up (Nofsinger and Sias, 1999). They find the importance of herding in comparison between individual and institutional investor because herding drive to or away from the fundamental values. Herding to past winner and away from past looser. Herding is more than simply agreement (Welch, 2000). We can never really know the dispersion of behaviour if they did not herd. Welch (2000) obtained the data from over 50,000 analyst recommendations at US brokerage houses over 1989 – 1994. He observed how distribution of recommendation changes with prevailing consensus. Only when the analyst revision on recommendation gravitate other recommendation, he consider it as herd. He finds that the recommendation revision herd. Strength of herding toward the consensus is not affected by whether the consensus recommendation is a good predictor of future stock price performance. Herding has a root in social influence and human phycology. It occurs in financial market, even amongst professional. To avoid it is by doing the homework before following the trend. By applying daily returns of 35,328 stocks traded on 69 countries over 10 years, using CSSD method the absence of herding behaviour is due to diverse opinions and analysts’ reports published by leading investment banks or the media (Chen, 2013). Using CSAD better capture the interdependence between asset returns and the market return, investors are more inclined to herd in the developed markets during market losses. Using State Space method, First, herding behaviour is still identified in both up and down markets for some countries. Second, investors tend to herd in response to bad news (down market) instead of good news (up market).

1. Nofsinger and Sias (1999) “Herding and Feedback Trading by Institutional and Individual Investors”
2. Chen, (2013) “Do Investors Herd in Global Stock Markets?”
3. Forbes Ch 11 (2009), FSS Model

Social Interaction and Emotion in Finance L7

Investor become interested in stock market because other mentioned it (Shiller and Pound, 1989). Information about investing influenced by neighbourhood. When neighbour increase their investment in industry by 10%, the household will improve the ownership by 2% (Ivkovi et al., 2007). Word of mouth is influential. Interaction make people are more interesting to invest (Hong et al., 2004). Survey of 7,500 households in Health and Retirement study of households finds that social households are more likely to invest in the stock market, this is called peer effects. The informal opinions, norms of the social group influence your investment decision. Study on pension plan participation is influenced by the work location (Duflo and Saez, 2002). Therefore, the speed of communication is also important, it is like disease that infectious and contagion. The evidence from the year after M&A completion, target investors double their trading activity, neighbours within 3 miles radius follow the trends (Huang et.al., 2016). His research using VAR to account for speed of communication, regress trading activity by household i. Google Search volume index can be used to measure investor attention to the media (Da et al., 2011). The language and words also matter because some words create vivid imagery. Vivid words influence the performance forecast of the company (Hales et al., 2011). Then we move to emotions in finance that includes feeling, misattribution bias, sentiment, excitement and entertainment. Investor mood can be influenced by misattribution of sunshine. The sunny days outperformed the miserable weather days (Hirshleifer and Shumway, 2003).Sentiment, investing for fun, local sports, moonstruck.

1. Hong et al., (2004) Social Interaction and Stock-Market Participation
2. Baker and Wurgler (2006) Investor Sentiment and the Cross-section of Stock Returns

Behavioural Biases, Perception about Risk and Return, Capital Structure and Budgeting L8

Traditional model includes CAPM, Fama and French, and Carhart. But manager appear rely on representativeness, affect when forming judgment about risk and return. Affect heuristic, return is positive and risk negative, those negatively correlated, in fact not. Fortune survey show the representativeness that quality management relate to good stock. Executive think that low betas, large market cap, low book to market to earn higher return and less risky. Perception about market premium explained with hot hand fallacy, gambler fallacy, extrapolating bias. Bull market high return, bear market low return. Overweight recent event will face extrapolation bias hot hand fallacy for individual investor and executives. For the professional investor will prone to predict reversal or gambler fallacy Tversky and Thaler (1990). In general, investor behaviour is less than fully rational think of smart manager who use market timing Baker and Wurgler, (2002)and catering approach to manage earnings, fewer constraint and superior information. In fact, managerial behaviour is less than fully rational due to managerial bias. Hot hand fallacy, perception about market premium, extrapolation bias, market timing and catering approach, affect heuristic, overconfidence, reluctant to terminate losing project. Capital structure include behavioural APV. Market timing, debt puzzle, project hurdle rate, cash poor, cash limited. Three key variables, financing constraints, degree of perceived mispricing, impact of the firms repurchase. Proxies for CEO overconfidence: options exercise-based measure or media coverage analysis (Malmendier and Tate, 2005). CEOs should exercise the vested option if it is 67% in the money, given a risk aversion of 3 in a constant relative risk-aversion utility specification Hall and Murphy (2002). It can also from trading behaviour through net purchase ratio Billet and Qian (2008), net buyer (Malmendier and Tate, 2005), photograph, press release Chaterjee and Hambrick, (2007). Financial flexibility and the project hurdle rate between cash poor and cash limited firms compare to cash rich firms (Shefrin, 2017). Investment of overconfidence manager will be sensitive to the cash flow (Malmendier and Tate, 2005). Choosing capital structure in practice between equity due to market timing overvaluation or undervaluation due to overconfidence Hall and Murphy (2002)or gambler fallacy and the debt puzzle conservatism due to loss aversion. In Capital budgeting, Affect heuristic play role during the uncertainty of capital budgeting, preference reversal. Overconfidence usually underestimate project risk and perceived control. Management reluctant to terminate losing negative project because disposition effect, aversion to sure loss, not close mental account. Manager put more money into failure due to confirmation bias, visibility salient and regret. 97% Company use cost of capital, only 73 % can decide whether to continue or abandon project.

1. Tversky and Thaler, (1990), “Anomalies: Preference Reversals”
2. Baker and Wurgler, (2002), “Market Timing and Capital Structure”
3. Malmendier and Tate, (2005) Investment and Cash Flow
4. Shefrin ch2,3,4,6, Capital Structure, Budgeting
5. Hall and Murphy (2002) CEO Overconfidence

Behavioural biases, dividend policy and M&A L9

Basic premise of MM is investor are immune to framing effects. The imperfections due to tax, signalling theory, agency problem and transaction cost. Mental accounting and hedonic editing feature framing effects that lead individual investors to find dividends especially attractive. Older view dividends as a replacement for wage and salary (Shefrin and Statman, 1984). Mental accounting is mentally separating info into manageable pieces, by maintaining separate accounts. Investor over age 65 concentrate their stock holdings in firms that pay high dividends, reason for individual prefer dividend are mental accounting, hedonic editing, tax effect (Graham and Kumar, 2006). For younger investor, hedonic editing applied means people prefer to experience gains separately than together e.g. gain+gain (segregated), loss+loss, large gain+small loss (cancellation effect), small gain+large loss (silver lining effect, segregated)(Thaler, 1985). Who make acquisitions (Malmendier and Tate, 2005). Managers developed heuristic to set dividend policy that cater to investor’ psychological needs. The survey evidence shows manager establish long run target payout ratios, concern for dividend increase rescind (Lintner, 1956). The market reacts positively to dividend, asymmetry. Managers appear catering to investors preference for dividends, it has price affects. During the bear market, investors who engage in hedonic editing might favour stable divs, then how about during bull market (investors’ perception of risk and return change). Moving to M&A, it relates to CEO overconfidence indicated by press coverage and option excising behaviour-based measures (Longholder, Holder 67)  (Malmendier and Tate, 2005, Malmendier and Tate, 2008). The finding is strong relation between OC and probs undertaking mergers (Malmendier and Tate, 2008). Tendency compounded when firm is generating positive cash flow but mitigated when board size less than 12.  In M&A, winner’s curse and hubris are frequently happen. Optimistic Executives in M&As usually have likelihood of conducting a deal, overpayment, more negative market reaction, cash payment, overconfident happen for ample internal sources. Rational manager calculates value of combined firm as market value company A plus market value company B plus synergy and minus cash paid. Overestimate will perceive dilution cost and pay as much as possible in cash, will perceive the firm to be overvalued with reversed pecking order. OC acquirer, OC target: premium is common and could be very large. Asymmetric info says that target firm only accept in which the acquiring firms overpays.

1. Shefrin and Statman, (1984) Explaining Investor Preferences for Cash Dividends
2. Malmendier and Tate, (2008), “Who Makes Acquisitions?
3. Campbell et al (2011), “CEO Optimism and Forced Turnover
4. Hirshleifer, Low and Teoh, (2012), “Are Overconfident CEOs Better Innovators?
5. Shefrin ch7,10, Dividends and M&A

Financial Crisis L10

Property price increase and then dramatically fall, subprime mortgages, securitisation. The participants are mortgage lenders, real estate appraisers, financial institutions. Physiological of borrowers is that people have difficulty processing complex contracts, often underestimate future costs, and optimistic about their future. Predatory lending targets are people who are most susceptible to these manipulated frames. Cross subsidy from the less wealthy to the wealthier. Underwater households and social norms. Biases of other participants such as insurance firms, credit rating agency and regulator. General biases during the crisis are greed, underestimation of risk, herding, fear and panic phase.

1. Demyanyk and Hemert (2011) “Understanding the Subprime Mortgage Crisis.
2. Stango and Jonathan (2009) “Exponential Growth Bias and Household Finance”

References

Barber, B. and Odean, T. (2001) ‘Boys will be boys: gender, overconfidence, and common stock investment’, Quarterly journal of economics,cxvi(1), pp. 261-292.

Barber, B. M. and Odean, T. (2000) ‘Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors’, Journal of Finance,55(2), pp. 773-806.

Barber, B. M. and Odean, T. (2008) ‘All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors’, The Review of Financial Studies,21(2), pp. 785-818.

Barberis, N. C. (2013) ‘Thirty Years of Prospect Theory in Economics: A Review and Assessment’, Journal of Economic Perspectives,27(1), pp. 173-196.

Bekaert, G. and Wang, X. S. (2009) ‘Home bias revisited’.

Carhart, M. M. (1997) ‘On Persistence in Mutual Fund Performance’, Journal of Finance,52(1), pp. 57-82.

Chen, T. (2013) ‘Do Investors Herd in Global Stock Markets?’, Journal of Behavioral Finance,14(3), pp. 230-239.

Choi, D. and Lou, D. (2010) ‘A test of the self-serving attribution bias: evidence from mutual funds’.

Cooper, M. J., Dimitrov, O. and Rau, P. R. (2001) ‘A Rose.com by Any Other Name’, Journal of Finance,56(6), pp. 2371-2388.

Cremers, K. M. and Petajisto, A. (2009) ‘How active is your fund manager? A new measure that predicts performance’, The Review of Financial Studies,22(9), pp. 3329-3365.

Da, Z., Engelberg, J. and Gao, P. (2011) ‘In Search of Attention’, Journal of Finance,66(5), pp. 1461-1499.

Duflo, E. and Saez, E. (2002) ‘Participation and investment decisions in a retirement plan: the influence of colleagues’ choices’, Journal of Public Economics,85(1), pp. 121-148.

Forbes, W. (2009) Behavioural finance.Chichester: Chichester : Wiley.

Frazzini, A. (2006) ‘The Disposition Effect and Underreaction to News’, Journal of Finance,61(4), pp. 2017-2046.

Graham, J. R. and Kumar, A. (2006) ‘Do Dividend Clienteles Exist? Evidence on Dividend Preferences of Retail Investors’, Journal of Finance,61(3), pp. 1305-1336.

Grinblatt, M. and Han, B. (2005) ‘Prospect theory, mental accounting, and momentum’, Journal of Financial Economics,78(2), pp. 311-339.

Hales, J., Kuang, X. and Venkataraman, S. (2011) ‘Who Believes the Hype? An Experimental Examination of How Language Affects Investor Judgments.(Report)’, Journal of Accounting Research,49(1), pp. 223.

Hirshleifer, D. and Shumway, T. (2003) ‘Good Day Sunshine: Stock Returns and the Weather’, Journal of Finance,58(3), pp. 1009-1032.

Hong, H., Kubik, J. D. and Stein, J. C. (2004) ‘Social Interaction and Stock‐Market Participation’, Journal of Finance,59(1), pp. 137-163.

Ivkovi, amp, x, Zoran and Weisbenner, S. (2007) ‘Information Diffusion Effects in Individual Investors' Common Stock Purchases: Covet Thy Neighbors' Investment Choices’, The Review of Financial Studies,20(4), pp. 1327-1357.

Kumar, A. and Lim, S. S. ‘How Do Decision Frames Influence the Stock Investment Choices of Individual Investors?’, 54(6), pp. 1052-1064.

Lintner, J. (1956) ‘Distribution of Incomes of Corporations Among Dividends, Retained Earnings, and Taxes’, The American Economic Review,46(2), pp. 97-113.

Malmendier, U. and Tate, G. (2005) ‘CEO Overconfidence and Corporate Investment’, Journal of Finance,60(6), pp. 2661-2700.

Malmendier, U. and Tate, G. (2008) ‘Who makes acquisitions? CEO overconfidence and the market’s reaction’, Journal of Financial Economics,89(1), pp. 20-43.

Malmendier, U., Tate, G. and Yan, J. (2011) ‘Overconfidence and Early‐Life Experiences: The Effect of Managerial Traits on Corporate Financial Policies’, Journal of Finance,66(5), pp. 1687-1733.

Moore, D. A. and Healy, P. J. (2008) ‘The Trouble with Overconfidence’, Psychological Review,115(2), pp. 502-517.

Odean, T. (1999) ‘Do Investors Trade Too Much?’, American Economic Review,89(5), pp. 1279-1298.

Petajisto, A. (2013) ‘Active share and mutual fund performance’, Financial Analysts Journal,69(4), pp. 73-93.

Shefrin, H. (2017) Behavioral Corporate Finance.McGraw-Hill Education.

Shefrin, H. and Thaler, R. (1988) ‘The Behavioral Life-Cycle Hypothesis’, Economic Inquiry,26(4), pp. 609.

Shefrin, H. M. and Statman, M. (1984) ‘Explaining investor preference for cash dividends’, Journal of Financial Economics,13(2), pp. 253-282.

Shiller, R. J. and Pound, J. (1989) ‘Survey evidence on diffusion of interest and information among investors’, Journal of Economic Behavior and Organization,12(1), pp. 47-66.

Thaler, R. (1985) ‘Mental accounting and consumer choice’, Marketing science,4(3), pp. 199-214.

 

[1]an individual erroneously believes that a certain random event is less likely or more likely, given a previous event or a series of events. This line of thinking is incorrect because past events do not change the probability that certain events will occur in the future.

 

[2]A chartist is an individual who uses charts or graphs of a security’s historical prices or levels to forecast its future trends. A chartist essentially looks for well-known patterns such as head-and-shoulders or support and resistance levels in securities so as to trade them more profitably. Chartists ply their trade in all markets where financial instruments are traded – equities, currencies, commodities and bonds. A chartist is also known as a technical analyst.