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Behavioral finance: A panel discussion
Journal of Behavioral and Experimental Finance 15 (2017) 52–58
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Journal of Behavioral and Experimental Finance journal homepage: www.elsevier.com/locate/jbef
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Behavioral finance: A panel discussion Greg Filbeck a, *,1 , Victor Ricciardi b,1 , Harold R. Evensky c,2 , Steve Z. Fan d,2 , Hunter M. Holzhauer e,2 , Andrew Spieler f,2 a
Penn State Erie, The Behrend College, United States Goucher College, United States R CFP⃝ Evensky & Katz/Texas Tech University, United States d University of Wisconsin – Whitewater, United States e University of Tennessee – Chattanooga, United States f Hofstra University, United States b c
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Article history: Received 12 February 2017 Received in revised form 10 July 2017 Accepted 26 July 2017 Available online 5 August 2017 JEL classification: G02 G11 G14
a b s t r a c t This panel discussion on behavioral finance took place on November 19, 2016 during the annual meeting of the Southern Finance Association held at Sandestin, Florida. The panel provides an overview of behavioral finance and discusses different types of behavioral biases; how they influence private and institutional wealth management clients and professionals, corporate decision making, and traders; generational and gender differences in asset allocation and estate planning; as well as identifying future areas of research. The content of this panel discussion is partly based on Baker et al. (2017). © 2017 Elsevier B.V. All rights reserved.
Keywords: Behavioral finance Panel discussion Behavioral bias Portfolio management
1. Behavioral finance: A panel discussion Filbeck: Welcome to the panel discussion on behavioral finance. The purpose of this panel discussion is to provide an overview of financial behavior of major stakeholders, financial services, investment products, and financial markets as it examines financial and emotional well-being and processing beliefs, emotions, and behaviors related to money. The basis for the content being shared by our panelists comes from the book Financial Behavior: Players, Services, Products, and Markets edited by H. Kent Baker, Greg Filbeck (me), and Victor Ricciardi and published by Oxford University Press in 2017. The book is a part of the Baker–Filbeck Financial Markets and Investments 11-book series by Oxford University Press. Kent and I published a similarly structured panel discussion based on topics covered by two other books in the same series on risk management (Baker, Filbeck, Holzauer et al., 2015) and private equity (Baker,Filbeck, Ahmed et al., 2015). While each book in the series offers a historical grounding of theoretical and empirical
* Corresponding author.
E-mail address: [email protected] (G. Filbeck). 1 Moderators. 2 Panelists.
http://dx.doi.org/10.1016/j.jbef.2017.07.008 2214-6350/© 2017 Elsevier B.V. All rights reserved.
subject matter including a mix of contributions between academics and practitioners, each title also focuses on the latest trends. We believe these panel discussions focused on the marriage of theory and practice are essential in presenting the majors themes of present study based on what we know today as well as identifying ideas for future research studies based on current trends. Vic and I would like to thank our fellow panelists for their contributions to our Financial Behavior book as well as their willingness to share their knowledge with us today. Bloomfield (2010, p.23), states that traditional finance . . . sees financial settings populated not by the error-prone and emotional Homo sapiens, but by the awesome Homo economicus. The latter makes perfectly rational decisions, applies unlimited processing power to any available information, and holds preferences well-described by standard utility theory. Behavioral finance is a field of finance that proposes psychologybased theories to explain stock market anomalies such as severe rises or falls in stock price. Ricciardi: Much has been published on behavioral finance. Let’s briefly introduce some of the interesting biases and sample research studies, first based on overconfidence. Overconfident investors refer to the fact that as human beings we have a tendency
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to overestimate our own skills and predictions for success. Barber and Odean (2001) examine the trading behavior based on the notion of gender bias for a sample of 35,000 client accounts over a six year investment horizon. The findings suggest that males are more overconfident than females in terms of their investing abilities and males trade more frequently. Males tend to sell their stocks at the wrong time and also reveal higher trading costs than females. Females tend to trade less, utilizing a buy and hold strategy resulting in lower trading costs. Males traded 45 percent more than females while single males trade 67 percent more frequently than single females. Trading costs decreased the net investment returns of men by 2.6 percent per year and only 1.7 percent for women. An extensive amount of research literature in behavioral finance reveals people have a tendency to be overconfident regarding their financial and investment decisions. This overconfident behavior is linked to over trading and too much active investing resulting in lower investment performance. Next, let’s turn to studies on status quo bias. Status quo investors refer to the group of investors that has an inclination to suffer from inertia, procrastination or inattention toward their financial judgments and decisions. The study by Mitchell et al. (2006) examines the trading behavior of employees invested in 401(k) plans. The study utilizes a sample of 1.2 million workers enrolled in 1,500 different retirement plans, with most of the 401(k) plan investors categorized by intense inactivity. The study reveals that most employees in defined contribution retirement plans suffer from status quo bias in which only a small percentage savers execute any trades, and a very small number trade actively. Nearly all retirement investors (approximately 80 percent) execute no trades, and an additional 11 percent makes just a single financial transaction over a two-year period (2003–2004). Investors suffer from inertia and are related to the failure of the pure ‘‘buy and hold’’ strategy. To overcome this bias, retirement savers should rebalance their accounts at least once per year. Next, let’s turn to studies concerning worry and risk perception. The study by MacGregor et al. (1999) focuses on how the financial decision-making process is linked to various aspects of investments/asset classes, specifically expert’s perceptions of returns, risk, and risk/return associations. A survey was mailed to financial advisors in which the 265 participants that responded were asked to provide their assessment of a series of 19 asset classes with 14 specific variables. The main findings revealed with the utilization of multiple regression analysis with perceived risk as the dependent variable that three significant factors (worry, volatility, and knowledge) explained 98 percent r-square of the experts’ risk perception. Finucane and Melissai (2002, p. 238), further comments, ‘‘perceived risk was judged as greater to the extent that the advisor would worry about the investments that the investments had greater variance in market value over time, and how knowledgeable the advisor was about the investment option’’. Finally, based on a study on framing and risk, we can attempt to answer the question of what type of negative emotions and issues did investors experience two years after the financial crisis in 2008? Based on an online survey of 1,697 investors, most investors hold both stocks and bonds in their investment portfolios (Ricciardi, 2011). When posed the question: Which do you worry about more, stocks or bonds, 20 percent indicated that they did not own both stocks and bonds, but 70 percent indicated stocks worry them more, while 10 percent indicates bonds were more worrisome. This survey was taken February 2010 to June 2010 by Nightly Business Report viewers and Kiplinger’s Personal Finance readers as part of the ‘‘Your Mind & Your Money’’ series. FinaMetrica administered the survey and the collection of data. This framing issue demonstrates how financial experts can communicate differently with their clients about the meaning of risk. In this example, the phrase
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worry can be substituted for the technical and objective definition of risk especially when discussing this topic with novice clients. Filbeck: Now it’s time to hear from our panelists. The first question: What are some of the primary examples of cognitive, emotional, and social biases? Spieler: Some examples of cognitive biases include (1) Illusion of control: people tend to believe that they can control or influence outcomes when, in fact they cannot and (2) Conservatism bias: people maintain their prior views or forecasts by inadequately incorporating new information. Some examples of emotional biases include (1) Loss aversion bias: asymmetric utility with respect to equal size losses and gains. Investors tend to prefer avoiding losses as opposed to achieving gains and (2) Overconfidence bias: people demonstrate unwarranted faith in their own intuitive reasoning. Examples of social biases include (1) Herding effect: Investors trade in the same direction or in the same securities, and possibly even trade contrary to the information they have available to them. Herding effects individuals, analysts and portfolio managers and (2) Social trends and paradigm shifts have brought behavioral biases to the forefront including changing attitudes to taking risk (e.g., the desensitization to lotteries and gambling). In addition, the decline of pension funds has forced individuals to take on the responsibility of investing via 401(k)s. Technology and internet trading has made investing (too) accessible and easy for uneducated investors. Fan: A quick Google search reveals that there are 101 cognitive biases, 27 social biases, and 49 memory biases reported by Wikipedia. Among them, 27 biases are regularly mentioned in behavioral finance. Primary examples of widely-recognized behavioral biases in finance include overconfidence, loss aversion, disposition effect, and anchoring effect. Evensky: Here are the comments I often hear that symbolizes overconfidence: ‘‘I can time the market’’. ‘‘I can pick better managers than most’’, and ‘‘The talking heads on TV know something others do not’’. They demonstrate representativeness with thoughts like ‘‘Morningstar gave a fund a 5 Star rating, so it must be good’’. Availability bias is exhibited with statements like ‘‘I like to buy IPOs’’. They make the headlines, but across the board they make lousy investments. (Case vs Base data). Saliency bias holds logic similar to not taking your umbrella out today because it didn’t rain yesterday and is a good way to get soaked. So is buying the hot fund of the last 10 min. Holzhauer: The first bias that comes to my mind is the availability heuristic, which allows a person to make mental shortcuts based on what information is quickly available from their memory, experiences, and imagination. However, given proper reflection, probably the most researched cognitive bias in behavioral finance is overconfidence. Overconfidence bias is created when people believe their personal qualities are better than they really are. A prime example of this is with driving cars. One can quickly poll any room and find that most people believe they are a better driver than the average driver. However, statistically some drivers are simply average and others are below average. In financial research, overconfidence is looked at from a variety of corporate, investment, and even regulatory angles. For example, Hirshleifer(2008) and Hirshleifer and Toeh (2009) both explore overconfidence in policy analysts and explain how overconfidence by policy analysts can lead to adopting too many regulations. Overconfidence is also plays a role in several biases that prevent investors and managers from accurately calculating probabilities such as gambler’s fallacy, hot hand fallacy, illusion of control, and winner’s curse. Some other well-known cognitive biases include representativeness, anchoring and adjusting, framing, and risk aversion.
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The most powerful emotional bias is likely incorporated in the affect heuristic. This heuristic is generally thought of as the specific degree of positive or negative feelings felt immediately when making decisions. Like any heuristic, this shortcut can help a person make quick ‘‘gut’’ decisions, but those decisions can be wrong or at least inefficient given additional information or time for reflection. Some areas that tend to create these rapid feelings can be religious issues, political issues, patriotic issues, and familial issues. Another common emotional bias is the familiarity bias in that many investors only invest in what they know. For example, the average investor tends to only hold a small portion of their portfolio in international investments. From a diversification strategy, this logic does not make sense. However, this behavior makes more sense when considering familiarity bias and that many investors simply do not invest in international companies because they know very little about these companies and may even be more inclined to emotionally trust domestic investments more. One more interesting topic in emotional finance is that individuals can create ‘‘phantastical’’ objects (spelled with a ‘‘ph’’ to represent unconscious fantasies) that result from early emotional development. In finance, these ‘‘phantasies’’ play out when investors become too attached to specific investments. For example, some investors likely viewed ‘‘dot com’’ stocks as phantastical objects in that they were superior magical investments that can do no wrong during the bubble and then became horrible evil investments after the crash. From a social perspective, groupthink is clearly a wellresearched phenomenon in behavioral finance. Groupthink can reduce anxiety for investors in the short-term, but in the longterm it creates herding behavior that can lead to bubbles like the dot com bubble just referenced. Groupthink frequently results in overreaction to new information creating significant market inefficiencies such as post-earnings announcement drift. Filbeck: In sum, our panelists have contrasted cognitive and emotional biases giving us examples of each and have discussed how these biases impact both clients and professionals. Next question: to what extent should behavioral biases be mitigated? Accommodated? Evensky: Generally, behavioral biases should be mitigated. However, some occasions exist when they should be accommodated, particularly when the biases are useful. For example, the decision to ‘‘opt out’’ versus ‘‘opt in’’ for certain pension decisions, the establishment of a preset default balanced portfolio, and whether to increase automatic contributions are areas in which accommodation is necessary. Determining when to move to cash based on a client’s comfort level is important. Holzhauer: I think two issues exist with this question. Can specific biases be limited by creating some controls, offering behavioral nudges, or applying appropriate defaults? Yes. Obvious examples exist of how controls can reduce risk or how nudges like stock options or retirement saving defaults can change behavior. However, does that mean that professionals should find ways to accommodate or mitigate all irrational behavior? No. Not Yet. More research is needed. Some biases are quickly mitigated while others are not. It’s important to understand the role of behavioral finance in relation to traditional finance. Behavioral finance should not be a group of theories that attempts to replace or even compete directly with traditional finance theories like modern portfolio theory and the efficient market hypothesis. Rather behavioral finance should be used to help clear up the picture. Imagine an old television as a metaphor for traditional finance and its screen provides only 95 percent clarity of an image. In some ways, behavioral finance can provide a clearer image by filling in some of the remaining 5 percent due to irrational behavior. In other words, traditional finance still explains the vast
majority of financial principles, but behavioral finance can fill in some missing pieces of the picture. That said, several interesting debates have occurred between Eugene Fama, a traditional finance researcher and Richard Thaler, a behavioral finance researcher. Fama has several issues with behavioral finance and argues against the robustness and reliability of several supposed behavioral anomalies in the market. Thaler argues that traditional finance researchers like to conveniently ignore bubbles and stock market crashes that traditional models do not easily explain. In short, both argue that rational behavior should be included in models. However, Thaler argues that irrational behavior should also be included in the models. Fama disagrees because he does not think irrational behavioral can be accurately measured and applied to those models. In other words, investors can adjust for irrational behavior, but they are just as likely to get it wrong and they are to get it right. Spieler: The general rule is that cognitive errors can be mitigated by educating investors, while the emotional biased cannot mitigated only accommodated. Some biases can be mitigated with preset goals/rules such as rebalancing portfolios on birthday. The two approaches – mitigation and accommodation – can co-exist within the same portfolio. Fan: I believe that education on behavioral finance at college level, especially for the students majoring in finance, is critical to mitigate the negative impacts caused by behavioral biases. It is important for future professionals to be well aware of the impact of behavioral biases on people’s financial decision-making. In the past 30 years, rational risk-return theories, such as the capital asset pricing model (CAPM), have become the foundation of the financial industry largely because the rational theory has been dominant in our teaching. Although recent research has provided strong evidence that investors’ behavioral biases have significant impacts on financial market, coverage of behavioral finance in our curriculum has not been adequate to keep up with the current development. Filbeck: So mitigation is the goal when possible, but certainly raising the awareness of the issue with clients is important regardless. Next, how are behavioral biases manifested in private wealth clients? Evensky: Fear is illustrated by the bailing out of the market during a significant market correction. Confusing certainty with safety holds logic such as bonds are ‘‘safe’’ although they may not provide the long term returns necessary for the investor to maintain his or her standard of living. The confusion between risk and loss occurs when clients are faced with the choice between a fixed income portfolio and a balanced portfolio and avoid the risk of market volatility rather than the loss of maintaining standard of living. They seek status by being able to invest for bragging rights. Mental accounting results from confusion of base versus case data and poor application of basic math. For example, confusion exists on subjects including linked versus average probabilities and the impact of large losses versus subsequent gains required to break even. Holzhauer: I know from my own research on financial risk tolerance that clients can react differently to positive and negative news. Prospect theory does a good job of explaining this effect. One clear issue with clients is that many overreact to bad news. This reality is probably the result of risk aversion, limited attention, and group think. It is the manager’s responsibility to get in front of the situation by calling the clients first and explaining the situation and the game plan moving forward. My research has shown that financial knowledge or literacy plays a role in financial risk tolerance. In other words, simply educating clients can help mitigate anxiety in
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clients and prevent them from liquidating risky investments at the wrong time.
the herding effect. Next, how do psychological factors influence corporate decision-making?
Spieler: Prospect theory is most prevalent here particularly with loss aversion. Private wealth clients often demonstrate loss aversion bias. They feel less pleasure in a gain in the value of the profit than the pain in the decline in the value for an equal amount. Thus, they could tend to hold losers too long and sell winners too quickly. They exhibit Improper understanding of diversification, ‘‘silo’’-ing of investments. They also fail to treat all assets as part of portfolio. Clients often have an overconcentration in company stock or geographically close companies. They exhibit overconfidence in ‘‘good’’ companies regardless of whether the investment is good. They also exhibit a poor understanding of tax impacts and hedging strategies.
Holzhauer: Overconfidence plays a big role in this area of behavioral finance in that advantages and disadvantages exist for overconfident managers. For example, Malmendier and Tate (2015) show overconfident managers tend to spend roughly 8 percent more on investments than other managers. Other research shows that overconfident managers tend to overvalue future returns on projects such as mergers and acquisitions, and tend to underestimate costs and time frames for completing projects. On the positive side, overconfident managers may work harder to try to offset some of these constraints. Evidence exists that entrepreneurs are more overconfident than managers of large corporations (Cooper et al., 1988). Besides overconfidence, another interesting area of research is the agency conflict area of behavioral finance. It plays an important role in corporate finance. Contractual incentives such as compensation, bonuses, and stock options can change employee behavior. That said, other areas exists in which agency conflict plays a role. For example, I am currently researching whether family firms are more likely to engage in mergers or acquisitions compared to nonfamily firms. It is obviously harder to separate ownership and management in family firms yet a few different ways exist in how agency conflict can be applied. Besides agency conflict, managers tend to rely heavily on heuristics. In other words, some managers tend to draw heavily on past experiences instead of following profit maximization techniques. Layoffs impact employee morale less than reductions in compensation suggesting that letting go of some of your workforce may be a better long-term strategy than reducing salaries.
Filbeck: In sum, biases appear across the board affected by attitude and framing. Helping clients understand the broader context of such biases will be helping in shaping and shifting strategy across time. Ricciardi: What types of behavioral issues do institutional investors exhibit? Evensky: The short answer is ‘‘all of the above’’. In other words, institutional investors face the same set of behavioral biases that are faced by private wealth clients. Holzhauer: Familiarity bias is important. Some research suggests that institutional investors are more likely to chase trends in international markets (Brennan et al., 2005). Other evidence shows that because of overconfidence, investors will take credit for success but blame failure on bad luck. Still other research shows that limited attention bias in that many institutional investors may not be mentally tracking transaction costs when they make decisions, which may explain why they may underperform passive benchmarks. Finally, analysts often anchor and adjust to other analysts when making recommendations. This herding mentality makes sense in that there is safety in numbers. In finance, it’s often better for analysts to not be wrong than to be right. In other words, as an analyst, it probably pays to anchor and adjust from a risk-return perspective. Spieler: The same confidence that creates the opportunities to succeed and achieve position as portfolio managers also creates overconfidence and anchoring. As Hunter mentions, herding is also common. Analysts also exhibit confirmation bias, representative bias, and gambler’s fallacy when they conduct research partly from the influence of company management.
Fan: Psychological factors influence almost all aspects of corporate decision-making. In corporate finance, the optimism and overconfidence of financial managers usually result in the belief of undervaluation of their firm. It explains the over-investment from internal financing and the pecking-order theory to some degree. Pecking-order theory refers the phenomena in corporate finance that managers prefer internal financing over external financing. In corporate investment, the over-investment in research and development (R&D) and the sensitivity of investment to cash flow relate to managers’ overconfidence. The ‘‘throw good money after bad’’ phenomenon is believed to be due to the loss aversion effect since managers are reluctant to admit or realize the losses of bad investment. In corporate merger and acquisition, overconfidence leads to the overestimation of value of synergies. The reference point thinking explains why a target’s 52-week high has a strong influence on offer price because it often serves as an anchor (reference point) in price calculation on both the bidder and target side.
Fan: Institutional or professional investors are usually believed to be immune to behavioral biases and exhibit less irrational behaviors. Because institutional investors trade against individual investors in general, institutional investors improve market efficiency. Consistent with this argument, several studies (e.g., Seru et al., 2010) find that mutual funds do not show significant behavioral biases in aggregate. However, at individual fund level, evidence exists that fund managers show a tendency to realize gains more readily than losses due to the disposition effect caused by overconfidence. Professional investors often hold on to losses much longer than gains (e.g., Frazzini, 2006; O’Connell and Teo 2009). Another documented behavioral bias of institutional investors is home bias. Home bias is the tendency for investors to concentrate their portfolio holdings in companies that are located within a close proximity.
Spieler: The most influential psychological factor is that managers are not always risk-averse. Corporate decision makers could exhibit fear toward potential loss but exhibit risk-seeking when a loss exceeds a certain level. This relation is similar to the call option of shareholders on corporate debt as the value of firm assets approach the level of debt. In addition, managers by construction are holders of undiversified portfolios, large equity positions, stock options, and reputational capital. In short, they face sigma (total) risk. Shareholders typically have diversified portfolios and face beta (systematic) risk. This position makes decision makers more risk averse. Conversely, founders/entrepreneurs tend to be overconfident as they often exhibit this inherent personality trait which contributed to their success to date.
Ricciardi: Our panelists have identified a variety of behavioral biases that are common among institutional investors including
Evensky: Overconfidence is the most significant. Another bias that they exhibit is anchoring to earlier estimates. Confirmation bias
Ricciardi: What behavioral biases have an effect on financial planners and analysts?
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– overweighting those facts that support your current belief and underweighting (or ignoring) conflicting evidence – is yet another area of bias. They also are impacted by hindsight bias, believing future market events can be seen as clearly as past events. Both financial planners and analysts are status seeking as they seeking bragging rights based on their investment performance. Holzhauer: In my opinion, the proper use of ‘‘opt in’’ versus ‘‘opt out’’ default strategies is one of the most important behavioral issues for financial planners. Default strategies such as whether to use automatically adjusting asset weights and automatic contribution increases are especially important now that most retirement plans are shifting from defined benefit plans to defined contribution plans. Spieler: Analysts and financial planners could exhibit overconfidence bias if they think they have superior skills to recommend investment opportunities. As Harold indicated, they may also have confirmation bias that viewing new information as confirmation of their original forecast. Filbeck: Next, let’s turn to questions about behavioral biases in decision making. How do psychological biases affect traders? Spieler: Traders could have gambler’s fallacy, a biased thinking that there will be a reversal to the long-term mean more frequently than actually happens. Malcolm Gladwell’s (2005) book ‘‘Blink’’ notes that ex-military makes good traders, quick decision makers and acceptable risk takers. Traders typically have Type A personalities. Fan: Full-time traders are more likely to avoid psychological biases because of superior investment technologies and extensive trading experience. However, full-time traders are usually working in environments with significantly higher stress levels than retail investors. People usually exhibit more psychological biases under stresses. It would be interesting to study whether full-time traders exhibit more or less bias than retail traders on average. Holzhauer: Traders suffer to some degree from limited attention bias, especially given the increase in information available now on the internet. To accommodate this bias, many technical or more active traders likely focus more attention on short-term trends like momentum while many traditional or more passive traders will likely focus more attention on long-term trends and fundamentals. This relation means that all traders use heuristics such as representativeness to take mental shortcuts in informational areas that their knowledge is limited. Some traders are impacted by the disposition effect. The old investment adage is to ‘‘cut your losses and let your profits run’’. However, many investors tend to quickly sell stocks that have appreciated and hold on too long to stocks losing value. In fact, individual investors tend to realize about 50 percent more gains compared to losses during the first 11 months of the year. This effect disappears or reverses for December suggesting that traders are realizing losses for tax purposes at the end of each year. Filbeck: Do generational differences exist in financial behavior? Evensky: This question is not relevant for financial planners as any specific client may not reflect the average generational differences. In fact, drawing conclusions based on age may be counterproductive in the same manner as drawing conclusions based on gender such as assuming the female spouse is more conservative than the male when the opposite may be true. Holzhauer: Overall, evidence exists that financial behavioral differences exists between Baby Boomers versus Millennials. For example, many Baby Boomers will rely on defined benefit pension plans for retirement. However, most Millennials will rely on defined contribution plans such as 401(k) plans. Retirement plans
will be drastically different based on changing life expectancy rates for different generations. That said, the more interesting question may be how does ‘‘age’’ impact financial behavior? First and foremost, investors often become more risk averse as they get older. For example, older investors tend to hold a larger array of stocks and tend to trade less frequently than younger investors. Older investors also tend to exhibit a smaller disposition effect in that they are more willing to sell stocks that are losing value. At some point, an adverse effect of cognitive aging exists. Some evidence suggests peak cognitive abilities are around age 42 with an abrupt drop off after age 70. While I’m not sure I agree with the exact ages or think a perfect normal distribution exists for cognitive abilities based on age, it makes sense that cognitive abilities increase to a peak and then decrease at some point. A tendency exists for some investors to ignore unsettling issues like cognitive decline or even death. Every investor should be willing to accept his own life cycle and structure financial plans to cover issues such as investments, insurance, long-term care, and estate planning. Spieler: Gen-Xers and Gen-Yers are more aligned with the Baby Boomers. Their investment strategies focus on the needs of the family and the continuity of family wealth, and they tend to plan with financial advisors. In contrast, the youngest generation is more pragmatic, proactive in their approach to investing, but sometimes exhibit overconfidence issue in overtrading. The Millennials are more accustomed to seeking their information and have more entrepreneurial spirit, leading to potential overconfidence. However, financial literacy remains remarkably high. Millennials are also more accustomed to raising capital via Kickstarter, crowdfunding, and peer to peer lending which makes them view financing through a very different lens. Fan: I believe that generational differences should not be significant. Because the behavioral biases are human psychological traits, they are not likely to change significantly within several generations. Ricciardi: I would add that the financial crisis of 2007–2008 has influenced generational differences in investing as well especially for those who were new investors at the time the crisis began. Next, let’s focus on estate planning and asset allocation. What behavioral themes exist during the estate planning process? Holzhauer: Trust is important issue in estate planning. Evidence exists that most people trust each other and even strangers. The issue of in-group bias exists when one person automatically trusts someone in a common group or with a professional title such as the Chartered Financial Analysts (CFA) designation. While trust is important, those individuals who seek estate planning expertise must protect themselves from desires to trust others. In other words, as much as individuals may personally like their financial advisors, they need to have someone else look over any major decisions an advisor makes. In other words, diversifying trust may be as important as diversifying other risk aspects when it comes to estate planning. Evensky: While a tax reduction is a primary driver of estate planning, behavioral finance plays a role in the creation of living wills. An effective estate planner needs to work through behavioral biases that can emerge in the process. Spieler: During estate planning, investors often demonstrate mental accounting bias. Estate planning is quite complicated and may resort to simplification or heuristics such as the thought that it is better to gift while alive versus through a bequest. Also, the importance of control may dominate the more efficient transfer of
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wealth. The rules are very different if trusts are involved and if the client is interested in generation-skipping. Ricciardi: So, trust issues, taxes, and breaking down the complexity of the process are all keys to success. How does financial behavior influence asset allocation? Evensky: Asset allocation is primarily driven by risk tolerance subject to risk capacity and risk need. Investors need to be mindful of tendencies to exhibit home bias within a given asset class. Fan: Overconfidence could lead to a riskier-than-it-should-be portfolio. Loss aversion could lead investors to hold on to losses for too long in the portfolio. Holzhauer: I can’t stress enough how important I think default options are for asset allocation. Evidence from Choi et al. (2004) suggests that 80 percent of investors accept default investments and Nessmith et al. (2007) show that 51 percent are still in the default option after two years. In other words, default options could help an investor overcome specific biases such as familiarity bias with regards to international diversification and even combat general inertia that many investors have toward savings in general. Spieler While many individuals in defined contribution plans seek target dates funds as a basis for retirement planning, they need to understand that cross-sectional variation in performance can cause outcomes to be different from expectations. Investors need to be mindful of their tolerance for risk as age-based strategies may leave too much discomfort based on market volatility. Further, as I discussed in a paper of mine, the ‘‘glide paths’’ are not the same across all providers and must be chosen with care and monitored (Miller et al., 2011). Ricciardi: Familiarity bias also plays an important role in asset allocation choices as well with investors gravitating to asset allocation strategies based on previous experiences based on the anchoring effect. Filbeck: Now we turn to future trends in financial behavior. How can investor behavior impact market anomalies? Holzhauer: I think one of the most robust market anomalies is post-earnings-announcement drift, which is the tendency for stock returns to drift for several days, weeks, or even months in the direction of an earnings surprise. This anomaly obviously violates the efficient market hypothesis and is a classic example of herding and market overreaction. Another classic bias is representativeness, which helps explain market anomalies such as the dot com bubble. Not all anomalies are necessarily caused my irrational behavior. One popular anomaly is the January effect, which creates an irrationally high return for stocks in January, especially for smaller cap stocks. Although this anomaly does not always occur, some rational explanations exist for this anomaly including a December selloff due to tax-loss harvesting to offset capital gains. Fan: Market anomalies are a direct challenge to the efficient market hypothesis. Although some anomalies disappear after their discovery, some anomalies are persistent, such as value anomalies, momentum, and, as Hunter mentions, post-earningsannouncement drift. The traditional efficient market hypothesis theory in which investors are rational and security prices incorporate all relevant information often fails to explain the existence of these persistent anomalies. Accumulating evidence suggest that investor behavioral biases play an important role in understanding the anomalies. Overconfidence and self-attribution can explain momentum and long-term reversal because investors overestimate their private information but underestimate public information. Daniel et al. (2001) show overestimation and underestimation result in a positive short-lag autocorrelation (momentum) and
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a negative long-term correlation (long-term reversal). The CEO’s overconfidence in management earning forecasting could lead to accrual anomaly. Limited attention bias, such as neglecting the distinct between accruals and cash flows, also helps explain the accrual anomaly. Due to the cost of arbitrage, behavior biases usually exhibit a higher impact on market anomalies when the limitsto-arbitrage level is high, but a lower impact when the limits-toarbitrage level is low. Consistent with this argument, Wang and Yu (2014) show that the abnormal return in low limits-to-arbitrage stocks is small and is correlated with firm specific risk measures, such as profitability, financial distress probability, and operating leverage. It seems that rational risk-return theory explains the abnormal return. Conversely, the abnormal return in high limitsto-arbitrage stocks is big and is due to mispricing. It suggests that physiological behaviors explain anomalies better for stocks with high level limits-to-arbitrage. Spieler: Some apparent anomalies are a reflection of rational investor behavior. For example, the year-end trading anomalies may just reflect rational behavior to reduce taxes. But some anomalies are a reflection of investor biases. For example, the short-run market anomalies may exhibit herding effects of investors. Filbeck: Our panelists have indicated that investors can definitely contribute to market anomalies, but that corporate professionals may play a role as well. To what extent does financial behavior affect speculation? Spieler: In the extreme, biases can lead to asset bubbles and trend following behavior. The phrase ‘‘This time it is different’’ is often heard, but it is usually not! Paraphrasing a recent quote in CFA Institute Magazine (McCarthy, 2016), ‘‘Investors are serially correlated, not markets’’. Therefore human, emotional beings will always have behavioral issues and always have ‘‘greed’’ as part of their collective DNA. Evensky: Speculation is the outcome from overconfidence, status seeking and availability biases. Fan: The ‘‘talking heads’’ often fuel speculation as the public jumps on board to follow. Holzhauer: Regardless of the underlying reason for anomalies, the mere presence and persistence of anomalies could suggest that investors are irrational and that their biases are correlated. Some anomalies can be fueled by speculation. In contrast, traditionalists could argue that most anomalies persist because they are not profitable enough for arbitragers to try to restore market efficiency. Arbitragers face not only trading and opportunity costs, but also noise-trader risk in that noise trading may make mispricing worse before it gets better making it difficult to time anomalies. In other words, market anomalies may be predictable, but many of these anomalies can be explained by limited arbitrage and noise-trader risk. Ricciardi: Speculation within financial markets influences individual and group behavior in the form of bubbles and crashes. The major behavioral finance themes associated with bubbles are overconfidence, group polarization, groupthink effect, herding, representativeness bias, familiarity issues, grandiosity, excitement, and the overreaction and under-reaction of stock prices. These themes are significant for understanding past financial mistakes because history often has a tendency to repeat itself. In the aftermath of the financial crisis of 2007–2008 or the crash of the stock and real estate markets, many investors suffer from several biases, including the recency bias, anchoring effect, worry, depression, loss averse behavior, status quo bias, and very low levels of trust. In the aftermath of the financial crisis and even today, some investors still exhibit negative long-term effects such as remaining overly
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risk averse resulting in under-investment in risky assets such as stocks and over-investment in safer assets such as cash and bonds. Filbeck: Many investor behaviors contribute to speculation including availability bias and easy access to media advice. Turning to the future, what future trends do you see in financial and investor behavior? Fan: Although behavioral finance has been making a rapid progress recently, it has been criticized for lack of sound theories. I would anticipate that more rigorous theories will be developed and a more systematic research approach will take place in the future. Evensky: I would anticipate the development of more framing strategies such as opt out versus opt in. Holzhauer: I really like Thaler and Sunstein’s (2008) book, ‘‘Nudge’’. Going forward, behavioral finance will increasingly emerge from a regulatory standpoint to help nudge people into behaviors that are more beneficial for the whole society. The manner in which issues are framed for investors will prove to be a very important topic in the future. Spieler: The ease of information is good and bad. Future investors will be much more connected to and may be influenced by many different communities, through social media and other networks. Ricciardi: Final question: what areas represent research opportunities in behavioral finance? Spieler: Three areas of future research include (1) how gender affects different investment style and asset allocation, (2) use of technology, information production and processing and ease of trading, and (3) links of personality data from alternative sources, social media, driving patterns, to financial risk taking. Fan: I believe that the interaction between irrational retail investors and irrational professional investors/corporate managers and how these interactions affect the financial market could be interesting topics in both theoretical and empirical study. Another interesting topic is determining if the development of technology brings more or less behavioral biases to financial market. For example, increasingly automated online trading could increase market efficiency by providing a more effective and efficient way for professional investors to correct the mispricing caused by irrational individual investors. Conversely, as Andrew points out, online trading also makes trading much more accessible to individual retail investors. The increased opportunities for individual investors would likely introduce more behavioral biases. It would be interesting to investigate what is the net effect of online trading on market efficiency. Evensky: Future research will likely focus on discovering a better understanding and measure of risk tolerance. Framing strategies will also be a primary focus on future research. Holzhauer: Countless areas exist for applying behavioral finance. Some of the areas based on my past research include agency conflict theory and overconfidence with mergers and acquisitions; informational asymmetry and familiarity bias with investment selection based on cultural differences or geographical distances; analyzing the financial and social performance of new investments like impact investing funds compared to traditional venture capital funds; comparing the effects of limited attention, affect, and the availability heuristic on investment behavior for groups with competing views in politics and religion; and examining the components of risk aversion and risk tolerance and whether they change overtime. Ricciardi: In conclusion, behavioral finance attempts to explain and improve a person’s knowledge of the cognitive issues and emotional reactions that influence financial judgments and decisions. A
wide collection of biases exist that impact decision-making process of players, including heuristics, framing, anchoring affect, mental accounting, familiarity bias, trust, loss aversion, herding, worry, and regret. These biases are significant and financial experts should use them to better communicate with and advise their clients. Our financial assessments are a situational, multidimensional process that depends on the specific traits of the player involved and the financial product, service or market conditions presented at the time of the decision (Baker et al., 2017). Filbeck: Thanks to each of our panelists for sharing their expertise on the subject of behavioral finance today. References Baker, H. Kent, Filbeck, Greg, Ahmed, Parvez, Holzhauer, Hunter, Preece, Dianna, Small, Kenneth, 2015. Private equality: A panel discussion. J. Appl. Finance 25 (2), 95–107. Baker, H. Kent, Filbeck, Greg, Holzhauer, Hunter, Saadi, Samir, Cristian-Ioan, Tiu, 2015. Risk management: A panel discussion. J. Appl. Finance 25 (1), 46–57. Baker, H. Kent, Filbeck, Greg, Ricciardi, Victor (Eds.), 2017. Financial Behavior Players, Services, Products, and Markets. Oxford University Press, New York. Barber, Brad M., Odean, Terrance, 2001. Boys will be boys: Gender, overconfidence, and common stock investment. Q. J. Econom. 116 (1), 261–292. Bloomfield, Robert, 2010. In: Baker, H. Kent, Nofsinger, John R. (Eds.), Traditional Versus Behavioral Finance. In: Behavioral Finance-Investors, Corporations, and Markets, John Wiley & Sons, Hoboken, NJ, pp. 23–38 Inc. Brennan, Michael. J., Cao, H.Henry, Strong, Norman, Xu, Xinzhong, 2005. The dynamics of international equity market expectations. J. Financ. Econ. 77 (2), 257–288. Choi, James J., David, Laibson, Brigette, C. Madrian, Andrew, Metrick, 2004. In: David, A. Wise. (Ed.), For Better or for Worse: Default Effects and 401(K) Savings Behavior. In: Perspectives on the Economics of Aging, University of Chicago Press, pp. 81–121. Cooper, Arnold D., Carolyn, Y. Woo., Dunkelberg, William C., 1988. Entrepreneurs’ perceived chances for success. J. Bus. Venturing 3 (2), 97–108. Daniel, Kent. D., David, Hirshleifer, Avanidhar, Subrahmanyam, 2001. Overconfidence, arbitrage, and equilibrium asset pricing. J. Financ. 56 (3), 921–965. Finucane, Melissai L., 2002. Mad cows, mad corn, & mad money: Applying what we know about the perceived risk of technologies to the perceived risk of securities. J. Psychol. Financ. Mark. 2 (4), 236–243. Frazzini, Andrea, 2006. The disposition effect and under-reaction to news. 61 (4), 2017–2046. Gladwell, Malcolm, 2005. Blink. Little, Brown, and Company, Boston. Hirshleifer, David, 2008. Psychological bias as a driver of financial regulation. Eur. Financ. Manage. 14 (5), 856–874. Hirshleifer, David, Toeh, Siew Hong, 2009. The psychological attraction approach to accounting and disclosure policy. Contemp. Account. Res. 26 (4), 1067–1090. McCarthy, Ed., 2016. Hybrid zone: Firms are finding success with a diverse array of quant strategies. CFA Inst. Mag. 27 (4), 42–44. MacGregor Donald G., Paul, Slovic, Michael, Berry, Harold R., Evensky, 1999. Perception of financial risk: A survey study of advisors and planners. J. Financ. Plan. 12 (8), 68–86. Malmendier, Ulrike, Tate, Geoffrey, 2015. Behavioral CEOS: The role of managerial overconfidence. J. Econom. Perspect. 29 (4), 37–60. Miller, Jonathan, Rosenburgh, Martin J., Spieler, Andrew C., 2011. Target date funds: Can one just glide into retirement? J. Int. Bus. Law 10 (2), 349–357. Mitchell, Olivia S., Gary, R. Mottola, Stephen, P. Utkus, Takeshi, Yamaguchi, 2006. The Inattentive Participant: Portfolio Trading Behavior in 401(K) Plans. In: Michigan Retirement Research Center Research Paper No. WP 2006-115, Available at SSRN: http://ssrn.com/abstract=1094834. Nessmith, William E., Stephen, P. Utkus, Jean, A. Young, 2007. Measuring the effectiveness of automatic enrollment. In: Vanguard Center for Retirement Research, Vol. 31. O’Connell, Paul G., Teo, Melvyn, 2009. Institutional investors, past performance, and dynamic loss aversion. J. Financ. Quant. Anal. 44 (1), 155–188. Ricciardi, Victor, 2011. The financial judgment and decision-making process of women: The role of negative feelings. In: Third Annual Meeting of the Academy of Behavioral Finance and Economics. Available at http://ssrn.com/abstract= 1936669. Seru, Amit, Tyler, Shumway, Noah, Stoffman, 2010. Learning by trading. Rev. Financ. Stud. 23 (2), 705–739. Thaler, Richard H., Sunstein, Cass R., 2008. Nudge: Improving Decisions About Health, Wealth, and Happiness. Yale University Press, New Haven and London. Wang, Huijun, Jianfeng, Yu, 2014. An Empirical Assessment of Models of the Value Premium. Working Paper, SSRN. Available at https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=1866397.
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Journal of Behavioral and Experimental Finance journal homepage: www.elsevier.com/locate/jbef
Full length article
Behavioral finance: A panel discussion Greg Filbeck a, *,1 , Victor Ricciardi b,1 , Harold R. Evensky c,2 , Steve Z. Fan d,2 , Hunter M. Holzhauer e,2 , Andrew Spieler f,2 a
Penn State Erie, The Behrend College, United States Goucher College, United States R CFP⃝ Evensky & Katz/Texas Tech University, United States d University of Wisconsin – Whitewater, United States e University of Tennessee – Chattanooga, United States f Hofstra University, United States b c
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Article history: Received 12 February 2017 Received in revised form 10 July 2017 Accepted 26 July 2017 Available online 5 August 2017 JEL classification: G02 G11 G14
a b s t r a c t This panel discussion on behavioral finance took place on November 19, 2016 during the annual meeting of the Southern Finance Association held at Sandestin, Florida. The panel provides an overview of behavioral finance and discusses different types of behavioral biases; how they influence private and institutional wealth management clients and professionals, corporate decision making, and traders; generational and gender differences in asset allocation and estate planning; as well as identifying future areas of research. The content of this panel discussion is partly based on Baker et al. (2017). © 2017 Elsevier B.V. All rights reserved.
Keywords: Behavioral finance Panel discussion Behavioral bias Portfolio management
1. Behavioral finance: A panel discussion Filbeck: Welcome to the panel discussion on behavioral finance. The purpose of this panel discussion is to provide an overview of financial behavior of major stakeholders, financial services, investment products, and financial markets as it examines financial and emotional well-being and processing beliefs, emotions, and behaviors related to money. The basis for the content being shared by our panelists comes from the book Financial Behavior: Players, Services, Products, and Markets edited by H. Kent Baker, Greg Filbeck (me), and Victor Ricciardi and published by Oxford University Press in 2017. The book is a part of the Baker–Filbeck Financial Markets and Investments 11-book series by Oxford University Press. Kent and I published a similarly structured panel discussion based on topics covered by two other books in the same series on risk management (Baker, Filbeck, Holzauer et al., 2015) and private equity (Baker,Filbeck, Ahmed et al., 2015). While each book in the series offers a historical grounding of theoretical and empirical
* Corresponding author.
E-mail address: [email protected] (G. Filbeck). 1 Moderators. 2 Panelists.
http://dx.doi.org/10.1016/j.jbef.2017.07.008 2214-6350/© 2017 Elsevier B.V. All rights reserved.
subject matter including a mix of contributions between academics and practitioners, each title also focuses on the latest trends. We believe these panel discussions focused on the marriage of theory and practice are essential in presenting the majors themes of present study based on what we know today as well as identifying ideas for future research studies based on current trends. Vic and I would like to thank our fellow panelists for their contributions to our Financial Behavior book as well as their willingness to share their knowledge with us today. Bloomfield (2010, p.23), states that traditional finance . . . sees financial settings populated not by the error-prone and emotional Homo sapiens, but by the awesome Homo economicus. The latter makes perfectly rational decisions, applies unlimited processing power to any available information, and holds preferences well-described by standard utility theory. Behavioral finance is a field of finance that proposes psychologybased theories to explain stock market anomalies such as severe rises or falls in stock price. Ricciardi: Much has been published on behavioral finance. Let’s briefly introduce some of the interesting biases and sample research studies, first based on overconfidence. Overconfident investors refer to the fact that as human beings we have a tendency
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to overestimate our own skills and predictions for success. Barber and Odean (2001) examine the trading behavior based on the notion of gender bias for a sample of 35,000 client accounts over a six year investment horizon. The findings suggest that males are more overconfident than females in terms of their investing abilities and males trade more frequently. Males tend to sell their stocks at the wrong time and also reveal higher trading costs than females. Females tend to trade less, utilizing a buy and hold strategy resulting in lower trading costs. Males traded 45 percent more than females while single males trade 67 percent more frequently than single females. Trading costs decreased the net investment returns of men by 2.6 percent per year and only 1.7 percent for women. An extensive amount of research literature in behavioral finance reveals people have a tendency to be overconfident regarding their financial and investment decisions. This overconfident behavior is linked to over trading and too much active investing resulting in lower investment performance. Next, let’s turn to studies on status quo bias. Status quo investors refer to the group of investors that has an inclination to suffer from inertia, procrastination or inattention toward their financial judgments and decisions. The study by Mitchell et al. (2006) examines the trading behavior of employees invested in 401(k) plans. The study utilizes a sample of 1.2 million workers enrolled in 1,500 different retirement plans, with most of the 401(k) plan investors categorized by intense inactivity. The study reveals that most employees in defined contribution retirement plans suffer from status quo bias in which only a small percentage savers execute any trades, and a very small number trade actively. Nearly all retirement investors (approximately 80 percent) execute no trades, and an additional 11 percent makes just a single financial transaction over a two-year period (2003–2004). Investors suffer from inertia and are related to the failure of the pure ‘‘buy and hold’’ strategy. To overcome this bias, retirement savers should rebalance their accounts at least once per year. Next, let’s turn to studies concerning worry and risk perception. The study by MacGregor et al. (1999) focuses on how the financial decision-making process is linked to various aspects of investments/asset classes, specifically expert’s perceptions of returns, risk, and risk/return associations. A survey was mailed to financial advisors in which the 265 participants that responded were asked to provide their assessment of a series of 19 asset classes with 14 specific variables. The main findings revealed with the utilization of multiple regression analysis with perceived risk as the dependent variable that three significant factors (worry, volatility, and knowledge) explained 98 percent r-square of the experts’ risk perception. Finucane and Melissai (2002, p. 238), further comments, ‘‘perceived risk was judged as greater to the extent that the advisor would worry about the investments that the investments had greater variance in market value over time, and how knowledgeable the advisor was about the investment option’’. Finally, based on a study on framing and risk, we can attempt to answer the question of what type of negative emotions and issues did investors experience two years after the financial crisis in 2008? Based on an online survey of 1,697 investors, most investors hold both stocks and bonds in their investment portfolios (Ricciardi, 2011). When posed the question: Which do you worry about more, stocks or bonds, 20 percent indicated that they did not own both stocks and bonds, but 70 percent indicated stocks worry them more, while 10 percent indicates bonds were more worrisome. This survey was taken February 2010 to June 2010 by Nightly Business Report viewers and Kiplinger’s Personal Finance readers as part of the ‘‘Your Mind & Your Money’’ series. FinaMetrica administered the survey and the collection of data. This framing issue demonstrates how financial experts can communicate differently with their clients about the meaning of risk. In this example, the phrase
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worry can be substituted for the technical and objective definition of risk especially when discussing this topic with novice clients. Filbeck: Now it’s time to hear from our panelists. The first question: What are some of the primary examples of cognitive, emotional, and social biases? Spieler: Some examples of cognitive biases include (1) Illusion of control: people tend to believe that they can control or influence outcomes when, in fact they cannot and (2) Conservatism bias: people maintain their prior views or forecasts by inadequately incorporating new information. Some examples of emotional biases include (1) Loss aversion bias: asymmetric utility with respect to equal size losses and gains. Investors tend to prefer avoiding losses as opposed to achieving gains and (2) Overconfidence bias: people demonstrate unwarranted faith in their own intuitive reasoning. Examples of social biases include (1) Herding effect: Investors trade in the same direction or in the same securities, and possibly even trade contrary to the information they have available to them. Herding effects individuals, analysts and portfolio managers and (2) Social trends and paradigm shifts have brought behavioral biases to the forefront including changing attitudes to taking risk (e.g., the desensitization to lotteries and gambling). In addition, the decline of pension funds has forced individuals to take on the responsibility of investing via 401(k)s. Technology and internet trading has made investing (too) accessible and easy for uneducated investors. Fan: A quick Google search reveals that there are 101 cognitive biases, 27 social biases, and 49 memory biases reported by Wikipedia. Among them, 27 biases are regularly mentioned in behavioral finance. Primary examples of widely-recognized behavioral biases in finance include overconfidence, loss aversion, disposition effect, and anchoring effect. Evensky: Here are the comments I often hear that symbolizes overconfidence: ‘‘I can time the market’’. ‘‘I can pick better managers than most’’, and ‘‘The talking heads on TV know something others do not’’. They demonstrate representativeness with thoughts like ‘‘Morningstar gave a fund a 5 Star rating, so it must be good’’. Availability bias is exhibited with statements like ‘‘I like to buy IPOs’’. They make the headlines, but across the board they make lousy investments. (Case vs Base data). Saliency bias holds logic similar to not taking your umbrella out today because it didn’t rain yesterday and is a good way to get soaked. So is buying the hot fund of the last 10 min. Holzhauer: The first bias that comes to my mind is the availability heuristic, which allows a person to make mental shortcuts based on what information is quickly available from their memory, experiences, and imagination. However, given proper reflection, probably the most researched cognitive bias in behavioral finance is overconfidence. Overconfidence bias is created when people believe their personal qualities are better than they really are. A prime example of this is with driving cars. One can quickly poll any room and find that most people believe they are a better driver than the average driver. However, statistically some drivers are simply average and others are below average. In financial research, overconfidence is looked at from a variety of corporate, investment, and even regulatory angles. For example, Hirshleifer(2008) and Hirshleifer and Toeh (2009) both explore overconfidence in policy analysts and explain how overconfidence by policy analysts can lead to adopting too many regulations. Overconfidence is also plays a role in several biases that prevent investors and managers from accurately calculating probabilities such as gambler’s fallacy, hot hand fallacy, illusion of control, and winner’s curse. Some other well-known cognitive biases include representativeness, anchoring and adjusting, framing, and risk aversion.
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The most powerful emotional bias is likely incorporated in the affect heuristic. This heuristic is generally thought of as the specific degree of positive or negative feelings felt immediately when making decisions. Like any heuristic, this shortcut can help a person make quick ‘‘gut’’ decisions, but those decisions can be wrong or at least inefficient given additional information or time for reflection. Some areas that tend to create these rapid feelings can be religious issues, political issues, patriotic issues, and familial issues. Another common emotional bias is the familiarity bias in that many investors only invest in what they know. For example, the average investor tends to only hold a small portion of their portfolio in international investments. From a diversification strategy, this logic does not make sense. However, this behavior makes more sense when considering familiarity bias and that many investors simply do not invest in international companies because they know very little about these companies and may even be more inclined to emotionally trust domestic investments more. One more interesting topic in emotional finance is that individuals can create ‘‘phantastical’’ objects (spelled with a ‘‘ph’’ to represent unconscious fantasies) that result from early emotional development. In finance, these ‘‘phantasies’’ play out when investors become too attached to specific investments. For example, some investors likely viewed ‘‘dot com’’ stocks as phantastical objects in that they were superior magical investments that can do no wrong during the bubble and then became horrible evil investments after the crash. From a social perspective, groupthink is clearly a wellresearched phenomenon in behavioral finance. Groupthink can reduce anxiety for investors in the short-term, but in the longterm it creates herding behavior that can lead to bubbles like the dot com bubble just referenced. Groupthink frequently results in overreaction to new information creating significant market inefficiencies such as post-earnings announcement drift. Filbeck: In sum, our panelists have contrasted cognitive and emotional biases giving us examples of each and have discussed how these biases impact both clients and professionals. Next question: to what extent should behavioral biases be mitigated? Accommodated? Evensky: Generally, behavioral biases should be mitigated. However, some occasions exist when they should be accommodated, particularly when the biases are useful. For example, the decision to ‘‘opt out’’ versus ‘‘opt in’’ for certain pension decisions, the establishment of a preset default balanced portfolio, and whether to increase automatic contributions are areas in which accommodation is necessary. Determining when to move to cash based on a client’s comfort level is important. Holzhauer: I think two issues exist with this question. Can specific biases be limited by creating some controls, offering behavioral nudges, or applying appropriate defaults? Yes. Obvious examples exist of how controls can reduce risk or how nudges like stock options or retirement saving defaults can change behavior. However, does that mean that professionals should find ways to accommodate or mitigate all irrational behavior? No. Not Yet. More research is needed. Some biases are quickly mitigated while others are not. It’s important to understand the role of behavioral finance in relation to traditional finance. Behavioral finance should not be a group of theories that attempts to replace or even compete directly with traditional finance theories like modern portfolio theory and the efficient market hypothesis. Rather behavioral finance should be used to help clear up the picture. Imagine an old television as a metaphor for traditional finance and its screen provides only 95 percent clarity of an image. In some ways, behavioral finance can provide a clearer image by filling in some of the remaining 5 percent due to irrational behavior. In other words, traditional finance still explains the vast
majority of financial principles, but behavioral finance can fill in some missing pieces of the picture. That said, several interesting debates have occurred between Eugene Fama, a traditional finance researcher and Richard Thaler, a behavioral finance researcher. Fama has several issues with behavioral finance and argues against the robustness and reliability of several supposed behavioral anomalies in the market. Thaler argues that traditional finance researchers like to conveniently ignore bubbles and stock market crashes that traditional models do not easily explain. In short, both argue that rational behavior should be included in models. However, Thaler argues that irrational behavior should also be included in the models. Fama disagrees because he does not think irrational behavioral can be accurately measured and applied to those models. In other words, investors can adjust for irrational behavior, but they are just as likely to get it wrong and they are to get it right. Spieler: The general rule is that cognitive errors can be mitigated by educating investors, while the emotional biased cannot mitigated only accommodated. Some biases can be mitigated with preset goals/rules such as rebalancing portfolios on birthday. The two approaches – mitigation and accommodation – can co-exist within the same portfolio. Fan: I believe that education on behavioral finance at college level, especially for the students majoring in finance, is critical to mitigate the negative impacts caused by behavioral biases. It is important for future professionals to be well aware of the impact of behavioral biases on people’s financial decision-making. In the past 30 years, rational risk-return theories, such as the capital asset pricing model (CAPM), have become the foundation of the financial industry largely because the rational theory has been dominant in our teaching. Although recent research has provided strong evidence that investors’ behavioral biases have significant impacts on financial market, coverage of behavioral finance in our curriculum has not been adequate to keep up with the current development. Filbeck: So mitigation is the goal when possible, but certainly raising the awareness of the issue with clients is important regardless. Next, how are behavioral biases manifested in private wealth clients? Evensky: Fear is illustrated by the bailing out of the market during a significant market correction. Confusing certainty with safety holds logic such as bonds are ‘‘safe’’ although they may not provide the long term returns necessary for the investor to maintain his or her standard of living. The confusion between risk and loss occurs when clients are faced with the choice between a fixed income portfolio and a balanced portfolio and avoid the risk of market volatility rather than the loss of maintaining standard of living. They seek status by being able to invest for bragging rights. Mental accounting results from confusion of base versus case data and poor application of basic math. For example, confusion exists on subjects including linked versus average probabilities and the impact of large losses versus subsequent gains required to break even. Holzhauer: I know from my own research on financial risk tolerance that clients can react differently to positive and negative news. Prospect theory does a good job of explaining this effect. One clear issue with clients is that many overreact to bad news. This reality is probably the result of risk aversion, limited attention, and group think. It is the manager’s responsibility to get in front of the situation by calling the clients first and explaining the situation and the game plan moving forward. My research has shown that financial knowledge or literacy plays a role in financial risk tolerance. In other words, simply educating clients can help mitigate anxiety in
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clients and prevent them from liquidating risky investments at the wrong time.
the herding effect. Next, how do psychological factors influence corporate decision-making?
Spieler: Prospect theory is most prevalent here particularly with loss aversion. Private wealth clients often demonstrate loss aversion bias. They feel less pleasure in a gain in the value of the profit than the pain in the decline in the value for an equal amount. Thus, they could tend to hold losers too long and sell winners too quickly. They exhibit Improper understanding of diversification, ‘‘silo’’-ing of investments. They also fail to treat all assets as part of portfolio. Clients often have an overconcentration in company stock or geographically close companies. They exhibit overconfidence in ‘‘good’’ companies regardless of whether the investment is good. They also exhibit a poor understanding of tax impacts and hedging strategies.
Holzhauer: Overconfidence plays a big role in this area of behavioral finance in that advantages and disadvantages exist for overconfident managers. For example, Malmendier and Tate (2015) show overconfident managers tend to spend roughly 8 percent more on investments than other managers. Other research shows that overconfident managers tend to overvalue future returns on projects such as mergers and acquisitions, and tend to underestimate costs and time frames for completing projects. On the positive side, overconfident managers may work harder to try to offset some of these constraints. Evidence exists that entrepreneurs are more overconfident than managers of large corporations (Cooper et al., 1988). Besides overconfidence, another interesting area of research is the agency conflict area of behavioral finance. It plays an important role in corporate finance. Contractual incentives such as compensation, bonuses, and stock options can change employee behavior. That said, other areas exists in which agency conflict plays a role. For example, I am currently researching whether family firms are more likely to engage in mergers or acquisitions compared to nonfamily firms. It is obviously harder to separate ownership and management in family firms yet a few different ways exist in how agency conflict can be applied. Besides agency conflict, managers tend to rely heavily on heuristics. In other words, some managers tend to draw heavily on past experiences instead of following profit maximization techniques. Layoffs impact employee morale less than reductions in compensation suggesting that letting go of some of your workforce may be a better long-term strategy than reducing salaries.
Filbeck: In sum, biases appear across the board affected by attitude and framing. Helping clients understand the broader context of such biases will be helping in shaping and shifting strategy across time. Ricciardi: What types of behavioral issues do institutional investors exhibit? Evensky: The short answer is ‘‘all of the above’’. In other words, institutional investors face the same set of behavioral biases that are faced by private wealth clients. Holzhauer: Familiarity bias is important. Some research suggests that institutional investors are more likely to chase trends in international markets (Brennan et al., 2005). Other evidence shows that because of overconfidence, investors will take credit for success but blame failure on bad luck. Still other research shows that limited attention bias in that many institutional investors may not be mentally tracking transaction costs when they make decisions, which may explain why they may underperform passive benchmarks. Finally, analysts often anchor and adjust to other analysts when making recommendations. This herding mentality makes sense in that there is safety in numbers. In finance, it’s often better for analysts to not be wrong than to be right. In other words, as an analyst, it probably pays to anchor and adjust from a risk-return perspective. Spieler: The same confidence that creates the opportunities to succeed and achieve position as portfolio managers also creates overconfidence and anchoring. As Hunter mentions, herding is also common. Analysts also exhibit confirmation bias, representative bias, and gambler’s fallacy when they conduct research partly from the influence of company management.
Fan: Psychological factors influence almost all aspects of corporate decision-making. In corporate finance, the optimism and overconfidence of financial managers usually result in the belief of undervaluation of their firm. It explains the over-investment from internal financing and the pecking-order theory to some degree. Pecking-order theory refers the phenomena in corporate finance that managers prefer internal financing over external financing. In corporate investment, the over-investment in research and development (R&D) and the sensitivity of investment to cash flow relate to managers’ overconfidence. The ‘‘throw good money after bad’’ phenomenon is believed to be due to the loss aversion effect since managers are reluctant to admit or realize the losses of bad investment. In corporate merger and acquisition, overconfidence leads to the overestimation of value of synergies. The reference point thinking explains why a target’s 52-week high has a strong influence on offer price because it often serves as an anchor (reference point) in price calculation on both the bidder and target side.
Fan: Institutional or professional investors are usually believed to be immune to behavioral biases and exhibit less irrational behaviors. Because institutional investors trade against individual investors in general, institutional investors improve market efficiency. Consistent with this argument, several studies (e.g., Seru et al., 2010) find that mutual funds do not show significant behavioral biases in aggregate. However, at individual fund level, evidence exists that fund managers show a tendency to realize gains more readily than losses due to the disposition effect caused by overconfidence. Professional investors often hold on to losses much longer than gains (e.g., Frazzini, 2006; O’Connell and Teo 2009). Another documented behavioral bias of institutional investors is home bias. Home bias is the tendency for investors to concentrate their portfolio holdings in companies that are located within a close proximity.
Spieler: The most influential psychological factor is that managers are not always risk-averse. Corporate decision makers could exhibit fear toward potential loss but exhibit risk-seeking when a loss exceeds a certain level. This relation is similar to the call option of shareholders on corporate debt as the value of firm assets approach the level of debt. In addition, managers by construction are holders of undiversified portfolios, large equity positions, stock options, and reputational capital. In short, they face sigma (total) risk. Shareholders typically have diversified portfolios and face beta (systematic) risk. This position makes decision makers more risk averse. Conversely, founders/entrepreneurs tend to be overconfident as they often exhibit this inherent personality trait which contributed to their success to date.
Ricciardi: Our panelists have identified a variety of behavioral biases that are common among institutional investors including
Evensky: Overconfidence is the most significant. Another bias that they exhibit is anchoring to earlier estimates. Confirmation bias
Ricciardi: What behavioral biases have an effect on financial planners and analysts?
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– overweighting those facts that support your current belief and underweighting (or ignoring) conflicting evidence – is yet another area of bias. They also are impacted by hindsight bias, believing future market events can be seen as clearly as past events. Both financial planners and analysts are status seeking as they seeking bragging rights based on their investment performance. Holzhauer: In my opinion, the proper use of ‘‘opt in’’ versus ‘‘opt out’’ default strategies is one of the most important behavioral issues for financial planners. Default strategies such as whether to use automatically adjusting asset weights and automatic contribution increases are especially important now that most retirement plans are shifting from defined benefit plans to defined contribution plans. Spieler: Analysts and financial planners could exhibit overconfidence bias if they think they have superior skills to recommend investment opportunities. As Harold indicated, they may also have confirmation bias that viewing new information as confirmation of their original forecast. Filbeck: Next, let’s turn to questions about behavioral biases in decision making. How do psychological biases affect traders? Spieler: Traders could have gambler’s fallacy, a biased thinking that there will be a reversal to the long-term mean more frequently than actually happens. Malcolm Gladwell’s (2005) book ‘‘Blink’’ notes that ex-military makes good traders, quick decision makers and acceptable risk takers. Traders typically have Type A personalities. Fan: Full-time traders are more likely to avoid psychological biases because of superior investment technologies and extensive trading experience. However, full-time traders are usually working in environments with significantly higher stress levels than retail investors. People usually exhibit more psychological biases under stresses. It would be interesting to study whether full-time traders exhibit more or less bias than retail traders on average. Holzhauer: Traders suffer to some degree from limited attention bias, especially given the increase in information available now on the internet. To accommodate this bias, many technical or more active traders likely focus more attention on short-term trends like momentum while many traditional or more passive traders will likely focus more attention on long-term trends and fundamentals. This relation means that all traders use heuristics such as representativeness to take mental shortcuts in informational areas that their knowledge is limited. Some traders are impacted by the disposition effect. The old investment adage is to ‘‘cut your losses and let your profits run’’. However, many investors tend to quickly sell stocks that have appreciated and hold on too long to stocks losing value. In fact, individual investors tend to realize about 50 percent more gains compared to losses during the first 11 months of the year. This effect disappears or reverses for December suggesting that traders are realizing losses for tax purposes at the end of each year. Filbeck: Do generational differences exist in financial behavior? Evensky: This question is not relevant for financial planners as any specific client may not reflect the average generational differences. In fact, drawing conclusions based on age may be counterproductive in the same manner as drawing conclusions based on gender such as assuming the female spouse is more conservative than the male when the opposite may be true. Holzhauer: Overall, evidence exists that financial behavioral differences exists between Baby Boomers versus Millennials. For example, many Baby Boomers will rely on defined benefit pension plans for retirement. However, most Millennials will rely on defined contribution plans such as 401(k) plans. Retirement plans
will be drastically different based on changing life expectancy rates for different generations. That said, the more interesting question may be how does ‘‘age’’ impact financial behavior? First and foremost, investors often become more risk averse as they get older. For example, older investors tend to hold a larger array of stocks and tend to trade less frequently than younger investors. Older investors also tend to exhibit a smaller disposition effect in that they are more willing to sell stocks that are losing value. At some point, an adverse effect of cognitive aging exists. Some evidence suggests peak cognitive abilities are around age 42 with an abrupt drop off after age 70. While I’m not sure I agree with the exact ages or think a perfect normal distribution exists for cognitive abilities based on age, it makes sense that cognitive abilities increase to a peak and then decrease at some point. A tendency exists for some investors to ignore unsettling issues like cognitive decline or even death. Every investor should be willing to accept his own life cycle and structure financial plans to cover issues such as investments, insurance, long-term care, and estate planning. Spieler: Gen-Xers and Gen-Yers are more aligned with the Baby Boomers. Their investment strategies focus on the needs of the family and the continuity of family wealth, and they tend to plan with financial advisors. In contrast, the youngest generation is more pragmatic, proactive in their approach to investing, but sometimes exhibit overconfidence issue in overtrading. The Millennials are more accustomed to seeking their information and have more entrepreneurial spirit, leading to potential overconfidence. However, financial literacy remains remarkably high. Millennials are also more accustomed to raising capital via Kickstarter, crowdfunding, and peer to peer lending which makes them view financing through a very different lens. Fan: I believe that generational differences should not be significant. Because the behavioral biases are human psychological traits, they are not likely to change significantly within several generations. Ricciardi: I would add that the financial crisis of 2007–2008 has influenced generational differences in investing as well especially for those who were new investors at the time the crisis began. Next, let’s focus on estate planning and asset allocation. What behavioral themes exist during the estate planning process? Holzhauer: Trust is important issue in estate planning. Evidence exists that most people trust each other and even strangers. The issue of in-group bias exists when one person automatically trusts someone in a common group or with a professional title such as the Chartered Financial Analysts (CFA) designation. While trust is important, those individuals who seek estate planning expertise must protect themselves from desires to trust others. In other words, as much as individuals may personally like their financial advisors, they need to have someone else look over any major decisions an advisor makes. In other words, diversifying trust may be as important as diversifying other risk aspects when it comes to estate planning. Evensky: While a tax reduction is a primary driver of estate planning, behavioral finance plays a role in the creation of living wills. An effective estate planner needs to work through behavioral biases that can emerge in the process. Spieler: During estate planning, investors often demonstrate mental accounting bias. Estate planning is quite complicated and may resort to simplification or heuristics such as the thought that it is better to gift while alive versus through a bequest. Also, the importance of control may dominate the more efficient transfer of
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wealth. The rules are very different if trusts are involved and if the client is interested in generation-skipping. Ricciardi: So, trust issues, taxes, and breaking down the complexity of the process are all keys to success. How does financial behavior influence asset allocation? Evensky: Asset allocation is primarily driven by risk tolerance subject to risk capacity and risk need. Investors need to be mindful of tendencies to exhibit home bias within a given asset class. Fan: Overconfidence could lead to a riskier-than-it-should-be portfolio. Loss aversion could lead investors to hold on to losses for too long in the portfolio. Holzhauer: I can’t stress enough how important I think default options are for asset allocation. Evidence from Choi et al. (2004) suggests that 80 percent of investors accept default investments and Nessmith et al. (2007) show that 51 percent are still in the default option after two years. In other words, default options could help an investor overcome specific biases such as familiarity bias with regards to international diversification and even combat general inertia that many investors have toward savings in general. Spieler While many individuals in defined contribution plans seek target dates funds as a basis for retirement planning, they need to understand that cross-sectional variation in performance can cause outcomes to be different from expectations. Investors need to be mindful of their tolerance for risk as age-based strategies may leave too much discomfort based on market volatility. Further, as I discussed in a paper of mine, the ‘‘glide paths’’ are not the same across all providers and must be chosen with care and monitored (Miller et al., 2011). Ricciardi: Familiarity bias also plays an important role in asset allocation choices as well with investors gravitating to asset allocation strategies based on previous experiences based on the anchoring effect. Filbeck: Now we turn to future trends in financial behavior. How can investor behavior impact market anomalies? Holzhauer: I think one of the most robust market anomalies is post-earnings-announcement drift, which is the tendency for stock returns to drift for several days, weeks, or even months in the direction of an earnings surprise. This anomaly obviously violates the efficient market hypothesis and is a classic example of herding and market overreaction. Another classic bias is representativeness, which helps explain market anomalies such as the dot com bubble. Not all anomalies are necessarily caused my irrational behavior. One popular anomaly is the January effect, which creates an irrationally high return for stocks in January, especially for smaller cap stocks. Although this anomaly does not always occur, some rational explanations exist for this anomaly including a December selloff due to tax-loss harvesting to offset capital gains. Fan: Market anomalies are a direct challenge to the efficient market hypothesis. Although some anomalies disappear after their discovery, some anomalies are persistent, such as value anomalies, momentum, and, as Hunter mentions, post-earningsannouncement drift. The traditional efficient market hypothesis theory in which investors are rational and security prices incorporate all relevant information often fails to explain the existence of these persistent anomalies. Accumulating evidence suggest that investor behavioral biases play an important role in understanding the anomalies. Overconfidence and self-attribution can explain momentum and long-term reversal because investors overestimate their private information but underestimate public information. Daniel et al. (2001) show overestimation and underestimation result in a positive short-lag autocorrelation (momentum) and
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a negative long-term correlation (long-term reversal). The CEO’s overconfidence in management earning forecasting could lead to accrual anomaly. Limited attention bias, such as neglecting the distinct between accruals and cash flows, also helps explain the accrual anomaly. Due to the cost of arbitrage, behavior biases usually exhibit a higher impact on market anomalies when the limitsto-arbitrage level is high, but a lower impact when the limits-toarbitrage level is low. Consistent with this argument, Wang and Yu (2014) show that the abnormal return in low limits-to-arbitrage stocks is small and is correlated with firm specific risk measures, such as profitability, financial distress probability, and operating leverage. It seems that rational risk-return theory explains the abnormal return. Conversely, the abnormal return in high limitsto-arbitrage stocks is big and is due to mispricing. It suggests that physiological behaviors explain anomalies better for stocks with high level limits-to-arbitrage. Spieler: Some apparent anomalies are a reflection of rational investor behavior. For example, the year-end trading anomalies may just reflect rational behavior to reduce taxes. But some anomalies are a reflection of investor biases. For example, the short-run market anomalies may exhibit herding effects of investors. Filbeck: Our panelists have indicated that investors can definitely contribute to market anomalies, but that corporate professionals may play a role as well. To what extent does financial behavior affect speculation? Spieler: In the extreme, biases can lead to asset bubbles and trend following behavior. The phrase ‘‘This time it is different’’ is often heard, but it is usually not! Paraphrasing a recent quote in CFA Institute Magazine (McCarthy, 2016), ‘‘Investors are serially correlated, not markets’’. Therefore human, emotional beings will always have behavioral issues and always have ‘‘greed’’ as part of their collective DNA. Evensky: Speculation is the outcome from overconfidence, status seeking and availability biases. Fan: The ‘‘talking heads’’ often fuel speculation as the public jumps on board to follow. Holzhauer: Regardless of the underlying reason for anomalies, the mere presence and persistence of anomalies could suggest that investors are irrational and that their biases are correlated. Some anomalies can be fueled by speculation. In contrast, traditionalists could argue that most anomalies persist because they are not profitable enough for arbitragers to try to restore market efficiency. Arbitragers face not only trading and opportunity costs, but also noise-trader risk in that noise trading may make mispricing worse before it gets better making it difficult to time anomalies. In other words, market anomalies may be predictable, but many of these anomalies can be explained by limited arbitrage and noise-trader risk. Ricciardi: Speculation within financial markets influences individual and group behavior in the form of bubbles and crashes. The major behavioral finance themes associated with bubbles are overconfidence, group polarization, groupthink effect, herding, representativeness bias, familiarity issues, grandiosity, excitement, and the overreaction and under-reaction of stock prices. These themes are significant for understanding past financial mistakes because history often has a tendency to repeat itself. In the aftermath of the financial crisis of 2007–2008 or the crash of the stock and real estate markets, many investors suffer from several biases, including the recency bias, anchoring effect, worry, depression, loss averse behavior, status quo bias, and very low levels of trust. In the aftermath of the financial crisis and even today, some investors still exhibit negative long-term effects such as remaining overly
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risk averse resulting in under-investment in risky assets such as stocks and over-investment in safer assets such as cash and bonds. Filbeck: Many investor behaviors contribute to speculation including availability bias and easy access to media advice. Turning to the future, what future trends do you see in financial and investor behavior? Fan: Although behavioral finance has been making a rapid progress recently, it has been criticized for lack of sound theories. I would anticipate that more rigorous theories will be developed and a more systematic research approach will take place in the future. Evensky: I would anticipate the development of more framing strategies such as opt out versus opt in. Holzhauer: I really like Thaler and Sunstein’s (2008) book, ‘‘Nudge’’. Going forward, behavioral finance will increasingly emerge from a regulatory standpoint to help nudge people into behaviors that are more beneficial for the whole society. The manner in which issues are framed for investors will prove to be a very important topic in the future. Spieler: The ease of information is good and bad. Future investors will be much more connected to and may be influenced by many different communities, through social media and other networks. Ricciardi: Final question: what areas represent research opportunities in behavioral finance? Spieler: Three areas of future research include (1) how gender affects different investment style and asset allocation, (2) use of technology, information production and processing and ease of trading, and (3) links of personality data from alternative sources, social media, driving patterns, to financial risk taking. Fan: I believe that the interaction between irrational retail investors and irrational professional investors/corporate managers and how these interactions affect the financial market could be interesting topics in both theoretical and empirical study. Another interesting topic is determining if the development of technology brings more or less behavioral biases to financial market. For example, increasingly automated online trading could increase market efficiency by providing a more effective and efficient way for professional investors to correct the mispricing caused by irrational individual investors. Conversely, as Andrew points out, online trading also makes trading much more accessible to individual retail investors. The increased opportunities for individual investors would likely introduce more behavioral biases. It would be interesting to investigate what is the net effect of online trading on market efficiency. Evensky: Future research will likely focus on discovering a better understanding and measure of risk tolerance. Framing strategies will also be a primary focus on future research. Holzhauer: Countless areas exist for applying behavioral finance. Some of the areas based on my past research include agency conflict theory and overconfidence with mergers and acquisitions; informational asymmetry and familiarity bias with investment selection based on cultural differences or geographical distances; analyzing the financial and social performance of new investments like impact investing funds compared to traditional venture capital funds; comparing the effects of limited attention, affect, and the availability heuristic on investment behavior for groups with competing views in politics and religion; and examining the components of risk aversion and risk tolerance and whether they change overtime. Ricciardi: In conclusion, behavioral finance attempts to explain and improve a person’s knowledge of the cognitive issues and emotional reactions that influence financial judgments and decisions. A
wide collection of biases exist that impact decision-making process of players, including heuristics, framing, anchoring affect, mental accounting, familiarity bias, trust, loss aversion, herding, worry, and regret. These biases are significant and financial experts should use them to better communicate with and advise their clients. Our financial assessments are a situational, multidimensional process that depends on the specific traits of the player involved and the financial product, service or market conditions presented at the time of the decision (Baker et al., 2017). Filbeck: Thanks to each of our panelists for sharing their expertise on the subject of behavioral finance today. References Baker, H. Kent, Filbeck, Greg, Ahmed, Parvez, Holzhauer, Hunter, Preece, Dianna, Small, Kenneth, 2015. Private equality: A panel discussion. J. Appl. Finance 25 (2), 95–107. Baker, H. Kent, Filbeck, Greg, Holzhauer, Hunter, Saadi, Samir, Cristian-Ioan, Tiu, 2015. Risk management: A panel discussion. J. Appl. Finance 25 (1), 46–57. Baker, H. Kent, Filbeck, Greg, Ricciardi, Victor (Eds.), 2017. Financial Behavior Players, Services, Products, and Markets. Oxford University Press, New York. Barber, Brad M., Odean, Terrance, 2001. Boys will be boys: Gender, overconfidence, and common stock investment. Q. J. Econom. 116 (1), 261–292. Bloomfield, Robert, 2010. In: Baker, H. Kent, Nofsinger, John R. (Eds.), Traditional Versus Behavioral Finance. In: Behavioral Finance-Investors, Corporations, and Markets, John Wiley & Sons, Hoboken, NJ, pp. 23–38 Inc. Brennan, Michael. J., Cao, H.Henry, Strong, Norman, Xu, Xinzhong, 2005. The dynamics of international equity market expectations. J. Financ. Econ. 77 (2), 257–288. Choi, James J., David, Laibson, Brigette, C. Madrian, Andrew, Metrick, 2004. In: David, A. Wise. (Ed.), For Better or for Worse: Default Effects and 401(K) Savings Behavior. In: Perspectives on the Economics of Aging, University of Chicago Press, pp. 81–121. Cooper, Arnold D., Carolyn, Y. Woo., Dunkelberg, William C., 1988. Entrepreneurs’ perceived chances for success. J. Bus. Venturing 3 (2), 97–108. Daniel, Kent. D., David, Hirshleifer, Avanidhar, Subrahmanyam, 2001. Overconfidence, arbitrage, and equilibrium asset pricing. J. Financ. 56 (3), 921–965. Finucane, Melissai L., 2002. Mad cows, mad corn, & mad money: Applying what we know about the perceived risk of technologies to the perceived risk of securities. J. Psychol. Financ. Mark. 2 (4), 236–243. Frazzini, Andrea, 2006. The disposition effect and under-reaction to news. 61 (4), 2017–2046. Gladwell, Malcolm, 2005. Blink. Little, Brown, and Company, Boston. Hirshleifer, David, 2008. Psychological bias as a driver of financial regulation. Eur. Financ. Manage. 14 (5), 856–874. Hirshleifer, David, Toeh, Siew Hong, 2009. The psychological attraction approach to accounting and disclosure policy. Contemp. Account. Res. 26 (4), 1067–1090. McCarthy, Ed., 2016. Hybrid zone: Firms are finding success with a diverse array of quant strategies. CFA Inst. Mag. 27 (4), 42–44. MacGregor Donald G., Paul, Slovic, Michael, Berry, Harold R., Evensky, 1999. Perception of financial risk: A survey study of advisors and planners. J. Financ. Plan. 12 (8), 68–86. Malmendier, Ulrike, Tate, Geoffrey, 2015. Behavioral CEOS: The role of managerial overconfidence. J. Econom. Perspect. 29 (4), 37–60. Miller, Jonathan, Rosenburgh, Martin J., Spieler, Andrew C., 2011. Target date funds: Can one just glide into retirement? J. Int. Bus. Law 10 (2), 349–357. Mitchell, Olivia S., Gary, R. Mottola, Stephen, P. Utkus, Takeshi, Yamaguchi, 2006. The Inattentive Participant: Portfolio Trading Behavior in 401(K) Plans. In: Michigan Retirement Research Center Research Paper No. WP 2006-115, Available at SSRN: http://ssrn.com/abstract=1094834. Nessmith, William E., Stephen, P. Utkus, Jean, A. Young, 2007. Measuring the effectiveness of automatic enrollment. In: Vanguard Center for Retirement Research, Vol. 31. O’Connell, Paul G., Teo, Melvyn, 2009. Institutional investors, past performance, and dynamic loss aversion. J. Financ. Quant. Anal. 44 (1), 155–188. Ricciardi, Victor, 2011. The financial judgment and decision-making process of women: The role of negative feelings. In: Third Annual Meeting of the Academy of Behavioral Finance and Economics. Available at http://ssrn.com/abstract= 1936669. Seru, Amit, Tyler, Shumway, Noah, Stoffman, 2010. Learning by trading. Rev. Financ. Stud. 23 (2), 705–739. Thaler, Richard H., Sunstein, Cass R., 2008. Nudge: Improving Decisions About Health, Wealth, and Happiness. Yale University Press, New Haven and London. Wang, Huijun, Jianfeng, Yu, 2014. An Empirical Assessment of Models of the Value Premium. Working Paper, SSRN. Available at https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=1866397.