The current issue and full text archive of this journal is available at www.emeraldinsight.com/1940-5979.htm RBF 4,2 INTRODUCTION/GUEST EDITORIAL 68 Behavioural finance: the role of psychological factors in financial decisions Gulnur Muradoglu Cass Business School, London, UK, and Nigel Harvey University College London, London, UK Abstract Purpose – The purpose of this paper is to introduce the special issue of Review of Behavioural Finance entitled “Behavioural finance: the role of psychological factors in financial decisions”. Design/methodology/approach – The authors present a brief outline of the origins of behavioural economics; discuss the role that experimental and survey methods play in the study of financial behaviour; summarise the contributions made by the papers in the issue and consider their implications; and assess why research in behavioural finance is important for finance researchers and practitioners. Findings – The primary input to behavioural finance has been from experimental psychology. Methods developed within sociology such as surveys, interviews, participant observation, focus groups have not had the same degree of influence. Typically, these methods are even more expensive than experimental ones and so costs of using them may be one reason for their lack of impact. However, it is also possible that the training of finance academics leads them to prefer methodologies that permit greater control and a clearer causal interpretation. Originality/value – The paper shows that interdisciplinary research is becoming more widespread and it is likely that greater collaboration between finance and sociology will develop in the future. Keywords Decision making, Psychology, Behavioural finance, Research work Paper type Research paper Review of Behavioral Finance Vol. 4 No. 2, 2012 pp. 68-80 r Emerald Group Publishing Limited 1940-5979 DOI 10.1108/19405971211284862 1. Introduction According to Glaser et al. (2004, p. 527): “Behavioural finance as a subdiscipline of behavioral economics is finance incorporating findings from psychology and sociology into its theories. Behavioral finance models are usually developed to explain investor behaviour or market anomalies when rational models provide no sufficient explanations”. Modern economics assumes that people choose between alternatives in a rational manner (von Neumann and Morgenstern, 1944) and that they know the probability distribution of future states of the world (Arrow and DeBreu, 1954). Modern finance assumes that markets are efficient and that agents know the probability distribution of future market risk (Markowitz, 1952; Merton, 1969). Research has been geared towards searching for a better risk factor/pricing model. In parallel with these theoretical developments, psychologists studying decision making were collecting data that suggested that individuals do not always make decisions in an optimal manner that those working in finance and economics assumed (e.g. Edwards, 1954, 1955). After a large corpus of data had accumulated, Bell et al. (1988) argued that it is worth making a conceptual distinction between normative (2004) and Ga These reviews indicate that much behavioural finance uses the corpus of work that demonstrates biases in human judgment and decision making (Kahneman et al. To counter this view. (1999) instigated a programme of research geared to demonstrating that heuristics often produce exceedingly good outcomes. (2002). (2009). p. Good reviews on the development of the field of behavioural finance include those ¨ rling et al. behavioural economics came of age when Kahneman and Tversky (1979) published prospect theory and matured after Kahneman’s receipt of the Nobel Prize for Economics in 2002 demonstrated that economists considered behavioural research as worthy of inclusion in their field of study. Kahneman (2011) argues that it originated in the early 1970s when Richard Thaler. however. this behavioural research had little impact on economics. by De Bondt et al. However. 2005). selecting who will win a tennis match purely on the basis of choosing the player whose name is The role of psychological factors 69 . Daniel et al. demonstrated that one of his professors was highly susceptible to the cognitive bias that is now known as the endowment effect. (2010). Tversky and Kahneman (1974) argued that cognitive biases occur because people use heuristics (mental “rules of thumb”). little sign that the field is contracting. They have demonstrated that. Gigerenzer et al. Behavioural economics did not exist. Arguably. then a graduate student in economics. For many years. 1987) can be seen as a landmark that triggered expansion of the field. However. descriptive models that identified how people actually make decisions under different conditions. There have been other developments too. Thaler (1999) went on to argue that research in the area would soon come to an end because financiers would be so convinced by the behavioural findings that they would adopt reasonable assumptions. 1982) to explain investor behaviour and market anomalies. increasing recognition that we need to move towards a theoretical framework that accounts not just for the circumstances that produce inefficient information processing but also for those that produce efficient information processing (Shefrin. as yet. Although Slovic (1972) drew the attention of those working within finance to the relevance of research on behavioural decision making to their concerns. Glaser et al. 1131) argued that “these heuristics are economical and usually effective”. in out-of-sample tests. They use them because they do not have the cognitive resources to carry out the procedures necessary to make normative decisions. Later. this strategy resulted in many people gaining the impression use of heuristics leads to irrational decisions. Although Tversky and Kahneman (1974. behavioural finance was slower to develop than behavioural economics. simple models that ignore some information or weight different types of information equally can outperform more complex models. and prescriptive models that identified ways of improving decision making when no normative models were available. they pointed out that their use leads to biases under certain circumstances. although those working in finance may be more sympathetic to the notion of basing their theories on realistic assumptions than those working in other areas of economics. For example. The work of De Bondt and Thaler (1985. They argued that economists may have been unwise to assume that normative models are descriptive. There is. They focused on those circumstances because doing so allowed them to cast light on the nature of the heuristics that produce them – in much the same way that vision scientists study visual illusions in their attempts to understand the visual system. such as those based on multiple regression.. there is.models of decision making that identified optimal ways of making decisions. you do not fight complexity with complexity. 2005). the disposition effect (Shefrin and Statman. 1985) refers to the finding that investors are likely to sell shares that have increased in price but tend to keep those that have dropped in price. p. Regulation of modern finance is complex. These examples demonstrate that behavioural finance can provide us with prescriptions as well as descriptions. judgment is often used to make forecasts from time series data. Similar findings have been reported in other fields. 2006. 2011) and beliefs about regime change (Bloomfield and Hayes. It has been demonstrated empirically by a number of researchers (e. the implications of overconfidence for finance (e. For example.g. 1993.. However. That configuration spells trouble. it requires a regulatory response grounded in simplicity. 2002. (2003). Within finance. 2006. few experiments have been conducted as direct tests of the financial effects of overconfidence: they include those carried out on stock market professionals by ¨ nkal (1994) and O ¨ nkal and Biais et al. policing (Snook et al. More recently.RBF 4. . It is an anomaly that is consistent with what would be expected on the basis of prospect theory and with what we know about cognitive biases (e. frequent trading) have been investigated by a number of authors. we shall briefly outline some of issues that those working within finance initially studied non-experimentally but that have more recently been subject to experimental research.g. 1999). Barberis et al. 2012) to be studied systematically.. simpler strategies have been found to be superior to more complex ones for selecting stocks (DeMiguel et al.. Scheibehenne and Broder. Lawrence et al. Researchers within finance have been aware of the potential importance of psychologists’ work on cognitive biases for some time. 2005) and marketing (Wu ¨ bben and and Kurzenha von Wangenheim. Historically. 2006. Harvey and Reimers. Experimental work in finance Experimentation is a mainstream methodology within psychology whereas it has been less common within finance. Reimers and Harvey. 2012. 2007). Gervais and Odean (2001). Odean. not risk. the endowment effect). Frazzini. Daniel et al. 2005. Executive Director for Financial Stability at the Bank of England.2 70 recognised is a strategy that outperforms the rankings produced by the Association of Tennis Professionals (Serwe and Frings. almost certainly too complex. not complexity” (Haldane. 2007).. experiments related to this effect have been comparatively rare: Thaler and Johnson (1990) and Post et al. Speekenbrink et al. He has reported a number of analyses that demonstrate that bank regulators would be better able to predict bank failure by using much simpler models than they do at present. Because complexity generates uncertainty. those working in finance have examined size of errors in real forecasts but such studies did not permit researchers to examine the features of time series that make forecasting difficult. (1998) and Bloomfield et al. Similarly.. Coval and Shumway. such as medicine (Gigerenzer ¨ user. Its effectiveness can depend on forecasters’ beliefs about the presence of regime shifts in those data. 2. perhaps too complex. Muradoglu and O Muradoglu (1994). In finance. including Odean (1998b. has applied Gigerenzer’s approach to bank regulation. Muradoglu (2002). Here. (2008) report two relevant experimental studies. Experiments allow factors that affect both judgmental forecasting (De Bondt. 2001. (2005). 2008). 1998a). 19). Haldane (2012). He argues that the current regulatory regime based on the Basel III Accords should be radically simplified if it is to increase its effectiveness: “Modern finance is complex. As you do not fight fire with fire.g. However. 2012. Furthermore. there is a concern about the validity of studies that have used participants drawn from the general population. What have such studies shown? In one of the first experimental papers to be published in the Journal of Finance. Lo et al. the similarity in the behaviour of finance professionals and lay people is actually an issue that needs to be addressed via empirical studies. conclusions drawn from studies of lay people do need to be modified if they are to be applied to professionals. two of the papers in the current issue are concerned with credit markets: they examine factors that influencing the use of credit by lay people. 1986. 1985). 2012). This issue need not concern us when the finance tasks of interest are ones that are normally carried out by lay people. differences between professionals and lay people occur. Here sampling participants from the general population is clearly the most appropriate approach. Similarly. Conclusions drawn from such studies may need some modification if they are to be applied to investors. such as that reported in third paper in this special issue. for example. Harvey and Reimers. Lo and Harvey. at least in certain financial tasks. The distinction between individual investors who are professional and those who are not is much less clear than it has been in the past. They found that finance professionals were more over confident than novices but that they could reduce this bias if they were given feedback. 1991). Thus. 2011. Within finance. 524) argue that Locke and Mann (2000) take the argument a step further by suggesting that any research that ignores the use of professional traders is likely to be received passively because “ordinary” individuals are unlikely to have any substantial impact on market price since they are too far removed from the price discovery process. It has even been possible to investigate whether in non-human animals (in the context of which it is known as the Concorde fallacy): Dawkins and Carlisle (1976) concluded that animals suffer from the fallacy whereas other researchers have failed to find any evidence that they are susceptible to it (Dawkins and Brockman. 1998) and adults (Arkes and Blumer. Of course. lay people now have increasing access to stock markets via the internet. exhibited more myopic risk aversion than students. Maestripieri and Alleva. The role of psychological factors 71 . Links to an experiment are posted in various forums. Even in stock investment tasks. O 1996) conducted a series of experiments comparing finance professionals and novices in a task requiring probabilistic forecasting of stock prices. So the research shows that. More generally. Haigh and List (2005) reported an experiment using 54 professional futures and options pit traders from the Chicago board of trade and showed that traders ¨ nkal and Muradoglu (1994.. Thus. Thus. Haigh and List (2005. However. The phenomenon has been demonstrated experimentally in both children (Krouse. Burns (1985) argues that finance professionals’ behaviour may differ from non-professionals’ behaviour due to training. 1995. 2012. they need to be modified in a surprising direction: biases have been found to be larger not smaller in professionals.Failure to ignore sunk costs is an issue in finance: for instance. etc. it is likely to have a role in producing the disposition effect. experimenters are increasingly adopting web-based experimentation (e. non-professional participants validly represent a section of the general population that invests in stock markets. at least in some financial tasks. reputation.g. Clearly. Reimers and Harvey. These latter results led Arkes and Ayton (1999) to question whether humans behave less rationally than lower animals. either individual or corporate. p. experience does not always produce expertise. 2012. Similar views have been expressed by Christensen-Szalanski and Beach (1984) and Frederick and Libby (1986). Webley and Plaisier. 1980. 2006). we have two papers that use experimental methods. the authors added graphs of the price information because it is known that visually displaying the data can make trends more salient. Our second paper is written by Sandie McHugh and Rob Ranyard from the University of Bolton. They were presented with price series for nine shares over five. It is even possible to carry out studies on specific populations drawn from various countries by selecting particular forums on which to post the web link to the experiment. Andersson and colleagues were interested in it because of their concern about short termism in financial markets (Stiglitz.000 people from a high street bank’s database of personal account customers. Lawrence et al. Graphs may counteract the myopic tendency to a certain extent by defocusing the attention from the most recent information. Finally. Participants played the role of an investor employed by a company. the authors added a condition intended to reduce participants’ information processing load: in this condition. However. ten or 15 days. The effectiveness of judgment as a means of making forecasts from time series and as a basis for making decisions using those forecasts is a well-researched area (Harvey and Bolger. Participants were asked to make a prediction about the price before making a purchase decision for up to 100 shares. They studied impact of the length of a time series on the predictions of stock prices and investment decisions. Trends in the price series were systematically varied. Martin Hedesstro ¨ m and Anders Biel written by Maria Andersson. studies reported by Lo and Harvey (2011) used this approach to show that availability of credit cards differentially affects purchasing behaviour of compulsive and non-compulsive shoppers in the UK and Taiwan. For example. they investigate the effect of longer evaluation intervals on financial decisions. In this issue. in Experiment 3. They examined the effects of information about the long-term financial consequences of different types of loans on credit repayment decisions.. They argue that bonuses based on the performance over the last year or even over the last quarter are signs of short termism. both prediction and investment performance are improved. They processed 242 replies for the . Their paper is important for its policy implications in the context of the current debate on bonuses. each of five points represented aggregated data over three days. on students from the University of Gothenburg. Tommy Ga from the University of Gothenburg.2 72 This allows participants to be drawn from a much broader demographic than that provided by local students. This time. In Experiment 2. Thus. They define short termism as a preference for actions in the near term that have detrimental consequences in the long term. They conducted two experiments with a random sample of 2. they observed that the predictions based on the longer price series of ten to 15 data points yielded smaller prediction errors but there was no impact on investment decisions. they conducted a laboratory experiment that lasts about 30 minutes. When the number of data points is reduced and averages are presented to reduce local variation. People are in general myopic. The first paper is ¨ rling. thereby lowering the number of data points that had to be processed. 1996. aggregation over time is a useful strategy. Price prediction errors were smaller in this condition than in conditions in which either five or 15 non-aggregated points were presented and risk taking for investments was closer to optimal. No significant effects of the length of the price series were observed either in predictions or in investments.RBF 4. In their first experiment. to distract investors from myopic decisions. In three experiments. 1989). Higher estimates of the likelihood of personal circumstances leading to repayment difficulties and worry about future increases in the cost of living reduced repayment levels. such surveys are carried out in much of the world. They also added questions asking participants to estimate the likelihood that redundancy or illness would lead to repayment difficulties. savings and wealth increases” (p. total cost information. to assess levels of worry this likelihood would produce. 179). Mostly. In these scenarios. with high quality data available from the USA. participants selected a monthly payment level when given either no additional information. Selecting a lower payment plan is associated with worry about a change in personal circumstances causing repayment difficulties. they used a wider variety of credit repayment scenarios. 167). They do not want to realise losses due to price movements.500 and one involving re-mortgage of a property loan of £40. which was conducted just after the 2008 financial crisis. higher levels of education and worry about personal circumstances causing repayment difficulties raised repayment levels. income. At the time. as the third paper in this issue The role of psychological factors 73 . 169) and by research on mental accounting: “Turkish investors do not sell the stocks when the price is falling but they do not hesitate to sell them when the price is rising. Yet others have been supported by work on corporate governance: “[y] investors prefer to buy the stocks of companies that are owned by a well-known group or individual” (p. 3. McHugh and Ranyard again examined the effects of provision of information about the long-term consequences of repayment decisions. Nowadays. were devised. 173). “The typical stockholder is from the upper social class [y] Stock demand increases as education. However.000. Use of surveys in finance Use of surveys in finance does not have a long history. They can internalise losses only in the case of catastrophic situations” (p. the authors showed that provision of additional information produced higher repayment levels. Muradoglu (1989) surveyed about 500 stock investors in Turkey. Maybe lower repayment levels can be used as a means of credit risk management and be associated with taking payment protection insurance. in this experiment. Some of the findings have since been confirmed by the literature on home bias: “[y] those investors who have personal and business relations with the management of the companies invest more in those companies because they feel confident in their action” (p. the UK. However. In their second experiment. The policy implications of the paper are important for retail banks. one with a credit card balance of £1. In contrast. credit cards debts or mortgages. there was much discussion in the country about the possibility of privatisation promoting demand among workers and about the possible effects of privatisation of companies on inhabitants in the neighbourhoods in which they were located. 171). Among the many recommendations was the suggestion that “Further research may [y] be conducted by savings surveys just like the consumer surveys” (p. and Scandinavia and other European countries. it is economists who work in this area. These include household level data on consumption and savings and debt. and to assess their levels of worry arising from the possibility of future rises in the cost of living. Controlling for demographic information. they could speed up the repayment of loans. or both total cost and loan duration information. Two credit repayment scenarios. loan duration information. In one relatively early study.paper that they present here. If they provided information on the cost and duration of debt repayments. they are more likely to finance consumption with credit cards or point-of-sale lending than by using personal bank credit or salary loans. We mentioned Haldane’s (2012) application of them to the problem of bank regulation above. attitude plays a significant role. communicate realistic odds of success to your clients. Finally. emotional and behavioural attitudes towards consumer credits. Second.000 Italian households that was conducted in 2009. The cognitive component which determines the individual’s decision-making framework is crucial. Kahneman and Riepe’s (1998) list of recommendations includes the following: . The survey covered households in both the north and south of Italy and included different household sizes and different income earners in each household. . . 1999). As we have seen. . Importantly. they show that. Age. and assess how risk averse your client is. They report a survey of 2. The questionnaire collected information about psychological characteristics as well as details of cognitive. keep track of instances of your overconfidence. In contrast.. . Further suggestions to financial advisors on how to take findings from behavioural finance into account have recently been outlined by Benartzi (2011). The psychological profile of the borrower is an important factor in consumer credit decisions. Why is work in behavioural finance important for finance? Behavioural finance is used to make recommendations to finance professionals about how to change their behaviour or how to communicate with their clients. Cosma and Pattarin show that cognitive and behavioural components of attitudes towards consumer credit differentiate credit users and non-users. This is contrasted with consumer debt which refers to debts that arise when someone does not fulfil their repayment obligations against their intentions and those of their creditor.2 74 demonstrates. make sure the frame chosen has relevance for the client. financial survey research includes an agenda that can be addressed by those working in behavioural finance. as the attitude of non-users becomes more favourable towards credit. First. . they increasingly prefer point-of-sale lending to credit cards. resist the natural urge to be optimistic. as credit users’ attitude towards credit becomes more positive. simple (fast-and-frugal) heuristics can provide an effective means of making complex decisions (Gigerenzer et al. This paper by Stefano Cosma and Francesco Pattarin focuses on the role of attitudes in the use of consumer credit. The probability of using credit cards also increases as the number of income earners in the household increases and when there are strong expectations that income will rise.RBF 4. among the many determinants of credit use. ask yourself whether you have real reasons to believe that you know more than the market. their definition of consumer credit refers to institutional credit involving a request by a household that the banker considers solvent. Cosma and Pattarin show that the probability of taking on debt increases as the attitude towards debt becomes more favourable. The paper is important in showing that. These results were robust to the needs of the household. They can be useful in . education and gender of credit users and non-users were reasonably well balanced. They distinguish consumer credit users from non-users. 4. Gigerenzer et al. such as in the expectation formation processes underlying selection of the contents of portfolio. It was not until the late nineteenth century that Walras (1874/1954) modelled these economic processes in a rigorous manner and not until the mid-twentieth century that the law that he identified was proved formally. responses to complexity need not themselves be complex: in fact. should act to promote the efficiency of the market and so limit the need for regulation and improve information dissemination (Daniel et al. 1995. use of feedback and a change in the way information is presented can improve forecasting performance (Harvey and Bolger. the processes involved were seen as too complex to allow them to be described formally. for example. The portfolio performance of subjective forecasts was superior to that of standard time series modelling. Even Thaler (2000. 11). 140) has seen this as a problem: “One reason economics did not start this way is that behavioural models are harder than traditional models”. 2012. Methods developed in mathematics. First. p. Thus. (2005) examined the effectiveness of an expectation formation process heuristically based on the subjective forecasts of finance professionals. The problem is in identifying the simple solutions that are appropriate for dealing with complex problems. awareness of findings in behavioural finance may lead to a change in working practices that improve performance: for example. For example. Holte.others areas of finance as well. Neuroeconomics and social neuroscience are still in their infancy. Smith (1776/1976) had to describe those processes in terms of an invisible hand. they are more likely ˚ stebro and Elhedhli. 1999. when he wrote the Wealth of Nations.. O A common objection is that incorporating behavioural data into theories of finance would produce results that would be too complex to be useful in practice. physics and economics are now standard in finance. We have two responses to this objection. There are probably a number of reasons for this. Succeeding in this is still likely to require the development of a more rigorous approach.. 1996. Methods developed in psychology have been imported more slowly. Finance has always borrowed methodologies from other disciplines. Others have argued that knowledge of behavioural finance should enable investors to become aware of how potential biases can affect investment their decisions and thereby to avoid such errors. The invisible hand was a metaphor that he used to communicate his view of an economic reality in which people act in their own self-interest but in which the market has the ability to correct itself without intervention. in turn. because. 1993). Muradoglu et al. during the early development of traditional economic theory. 1996). psychological forces are too complex” (p. as we have seen. Second. 2006. More generally. 2002). Ricciardi and Simon (2000) have argued that behavioural finance enables those who invest in stock and mutual funds to avoid common “mental mistakes and errors” and develop effective investment strategies. Behavioural finance is still in its early days: the path along which it develops may result in it becoming a more rigorous discipline. Thus. he could not describe them formally in the way we do today. However. Bloomfield (2006) has argued: “No behavioural alternative will ever rival the parsimony and power of traditional efficient markets theory. Thus. experiments are difficult and costly to conduct with investors and market professionals because their participation in experiments requires funds that exceed those available under standard finance The role of psychological factors 75 . This. 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