1、CHAU DUONG 3 Oct 2012,BEHAVIOURAL FINANCE: WHO IS NAVE?,Overview,Academics versus practitioners Are we biased? Behavioural finance An example: Confirmation bias What can we learn and how to benefit from it?,Academics versus practitioners,“In theory, there is no difference between theory and practice
2、. But, in practice, there is.” In your job, how often do you refer back to the textbook used in your undergraduate programme? How many of you read the Journal of Finance or the Journal of Financial Economics regularly? Are we living in two separate worlds?,Some examples.,Index trackers “Style box” s
3、ub-classification of investment funds Market cap: small versus large Investment style: value versus growth So, are we living in two separate worlds? “the failure to implement research-supported practices has been observed in nearly every field where there is a separation between those who conduct re
4、search and those who are in a position to implement research findings” (Rynes et al., 2007),Are we biased?,Are we biased?,Supposed we are tossing a coin 100 times It happens that we got 100 tails What do you think about the 101 toss?,Why are we biased?,Why are we biased?, it deosnt mttaer in waht or
5、edr the ltteers in a wrod are, the olny iprmoetnt tihng is taht the frist and lsat ltteer be at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe.,Some common heuristic
6、s,Representativeness Availability Adjustment and anchoring Overconfidence,Representativeness,Consider the following description of a random person: “very shy and withdrawn, invariably helpful, but with little interest in people or the social world. A meek and tidy soul, he has a need for order and s
7、tructure and a passion for detail” Is it more likely that s/he a farmer or an academic?,Representativeness,People look for traits that an individual, object, or event may have that correspond with previously formed stereotypes.,Biases caused by representativeness,Insensitivity of sample size Misconc
8、eption of chance Regression to the mean,Availability,Judgments on the basis of how easily we can call to mind what we perceive as relative instances of a given phenomenon The ease of imagining an example, or the vividness and emotional impact of that example becomes more credible than actual statist
9、ical probability of the event occurring.,Biases caused by representativeness,Ease of recall (based on vividness)Example: Which is the more frequent cause of death in the U.S., homicide or stroke? Retrievability (based on memory structures)Example: Are there more words in the English language that be
10、gin with R or have R as the third letter? Presumed associationsExample: Are couples who get married under the age of 25 more likely to have larger families?,Adjustment and anchoring,A psychological heuristic which influences the way people intuitively assess probabilities. People start with an impli
11、citly suggested reference point (the “anchor“) and make adjustments to it to reach their estimate. People respond conservatively to new information, especially if the new information increases the level of uncertainty.,Overconfidence,People are imperfect at gauging their own level of accuracy. Peopl
12、e fail to appreciate the difficulty of questions. They do not decrease their confidence as their knowledge about the subject of a question decreases. People tend to be more overconfident when asked to respond to questions of moderate to extreme difficulty than when responding to simple questions.,Wa
13、nt some more?,http:/ finance,The study of how humans interpret and act on information to make informed investment decisions (Lintner, 1998) Investors not only behave irrationally, but their irrationalities are systematic and predictable, not random (Shiller, 2003),Sorry but we are pros.,Self-attribu
14、tion: success is often attributed to self, failure to external factors Overconfidence in performing difficult task with delayed feedback Too optimistic about own business Confirmatory update,Evidence of confirmation bias,How value and glamour investors process new financial information? Why this iss
15、ue? The widespread value glamour trading and predominance of financial information Interesting existing evidence, but lack of explanations,The design,Piotroskis (2000) F Score,Mohanrams (2005) G Score,profitable,profitable,Findings,Value investors: Under-react to good information Rationally react or
16、 over-react to bad information Glamour investors: Under-react to bad information Rationally react or over-react to good information,The implications,Good Info,optimism,pessimism,The implications,Bad Info,optimism,pessimism,What can we learn and how to benefit from it?,Thank you very much!,Chau Duong c.duonguel.ac.uk,
