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Brand valuation a key tool for business Over the years, there has been a dramatic shift in the source of value creation from tangible to intangible assets that don't show up on the balance sheets. Load More. Several aspects of the experimental design are worth highlighting. First, the only difference between the two conditions is the removal of the purchase price information.
We think of this condition as a control treatment because this previous study found that the average subject exhibited a sizable disposition effect, and because it resembles many real-world settings where purchase price information is prominently displayed on financial statements and trading software. We now describe our method for calculating the disposition effect at the individual subject level, which follows a similar methodology to that of Odean Every time a subject is offered the opportunity to sell a stock, we classify his decision into one of four mutually exclusive categories: realized gains, realized losses, paper gains or paper losses.
A decision is classified as a realized gain if the market price of the stock is above the purchase price, and the subject decides to sell the stock. A decision is classified as a realized loss if the market price of the stock is below the purchase price, and the subject decides to sell the stock. A decision is classified as a paper gain if the market price of the stock is above the purchase price, and the subject decides not to sell the stock.
A decision is classified as a paper loss if the market price of the stock is below the purchase price, and the subject decides not to sell the stock. For each subject, we count the number of realized gains, realized losses, paper gains, and paper losses over the course of both experimental sessions. In this section we present a simple model of selling decisions, and use it to derive hypotheses about the effect of making the purchase price less salient.
Consider the problem of an individual who is deciding whether or not to sell stock i in trial t. The model assumes that individuals make selling decisions using a random utility model based on the following utility statistic:.
The REV i,t term is given by the difference between the current price for stock i, and the expected price immediately after the next price change for the stock. As we now show, REV i,t is the key variable for an investor who trades to maximize expected final wealth. Let p i,t be the price of stock i in trial t , after the price update, if any. Now consider the case of a stock that received a price update.
Given the Markovian structure of the price process, we can write q i,t as follows:. Furthermore, recall that subjects are told that there is an equal chance that each stock begins in the good or bad state. Using this equation, we can then compute the relative expected value of selling the stock, which we denote by REV. Thus, we have that REV is given by:. This is quite intuitive. Given the symmetry in the distribution of potential gains and losses, selling the asset increases expected income only when a price decrease is more likely than a price increase, which only happens when the asset is more likely to be in the bad state than in the good state 9.
The CG term is computed as follows. Let c i,t denote the last purchase price for stock i in trial t , and let p i,t denote the price at which it currently trades. The capital gain variable is given by. The motivation for including the REV term in the model is that it captures a motive based purely on maximizing expected wealth. The motivation for including the CG term in the model is that several important explanations of the disposition effect predict that selling decisions are heavily influenced by this variable.
As described in the introduction, these include models based on realization utility, prospect theory, and an irrational belief in the mean-reversion of stock prices. Consider how each of them relates to the CG statistic. First, consider an individual who is driven solely by a realization utility motive. By assumption, the utility generated from selling a stock for such an individual is proportional to the realized capital gain at the time of selling.
Previous studies have shown that this simple model can explain the disposition effect, as long as individuals also discount the future at a sufficiently high rate 10 ; i. In this case of heavy discounting, we have that the relative value of selling the asset is approximately given by CG i,t. In other words, the decision of a pure realization utility trader that has linear utility, and who discounts the future at a high rate, is approximately driven by the capital gains term Second, consider an individual who trades based on prospect theory preferences Odean ; Weber and Camerer Furthermore, utility is concave in the gain domain and convex in the loss domain, inducing the S-shaped value function proposed by Kahneman and Tversky Much of the early literature examining the disposition effect through a prospect theory explanation uses a static setting, and for simplicity, we do the same here The individual now finds himself in the gain domain, where he is risk averse because of the concave utility.
This risk aversion will on average induce the individual to sell the stock because he no longer finds holding the stock attractive because of the increase in risk aversion. Owing to the risk-seeking behavior that occurs in this domain, the individual finds it attractive to hold the stock since he has an increased appetite for risk. This suggests that, in sufficiently simple and static trading settings, the behavior of traders with prospect theory preferences is approximately driven by the capital gain.
We emphasize however, that recent studies have raised doubts about the generalizability of this result, particularly in complex dynamic settings Barberis and Xiong ; Kaustia ; Hens and Vlcek Finally, consider a model based on an irrational belief in the mean reversion of stock prices, which has also been argued to provide an explanation for the disposition effect Odean ; Weber and Camerer In the simplest version of the model, individuals have linear utility and seek to maximize the expected value of total trading payoffs.
However, unlike a Bayesian investor, and contrary to the true nature of the price process, they believe that prices exhibit mean reversion. First, there is the motive to maximize expected wealth from the experiment, which is captured by the REV variable. Second, there is the motive to trade based on the CG variable, which can be the result of realization utility preferences, simple prospect theoretic preferences, or an irrational belief in the mean reversion of stock prices. However, our experimental design does not provide a clean test of which of the three mechanisms discussed here provides a better explanation for the disposition effect.
This is an important question, but is beyond the scope of this paper. Using the procedure described in section 3. Therefore, this type of investor will tend to sell more capital losses than capital gains, which leads to a negative value of PGR-PLR. Based on the findings of our previous work Frydman et al. The central goal of the study is to investigate whether the disposition effect is modulated by the saliency with which the purchase price information is displayed.
Although individuals can compute this information on their own, we hypothesized that making this information less salient, by removing it from the price update and trading screens, would decrease the magnitude of the disposition effect. The second part of Hypothesis 2 is based on the fact that all of the simple models of the disposition effect described above predict that behavior is highly responsive to the CG variable.
One natural question is whether decreasing the saliency of the purchase price information also increases the impact of the REV variable on selling decisions. Although we test for this possibility below, we emphasize that it is hard to pin down an a priori hypothesis because it is not known if the effects of information saliency are direct in which case only the CG mechanism should be affected by the treatment or relative in which case the impact of both CG and REV should be affected.
To test the predictions about the motives generating this behavior, we estimate the following logistic regression, separately for every subject, and only on trials in which the subject has an opportunity to sell a stock:.
As shown there, the majority of individuals had positive estimated coefficients for both variables, which provides support for the hybrid model proposed here. We then compute the average estimated coefficient across subjects, which has been shown to provide a good approximation to a mixed effects model with random coefficients Friston et al.
Together, this provides evidence consistent with Hypothesis 1. In the control condition the population of subjects is sensitive to two motives when making selling decisions: the maximization of expected wealth and the realization of capital gains. The sensitivity of the decision to capital gains is important because it is consistent with the presence of a sizable disposition effect. First, as expected, the average disposition effect decreases from 6.
Second, Figure 3 depicts the percentage of decisions that are optimal, in the sense of being consistent with the maximization of expected wealth, by condition and decision type realized gains, realized losses, paper gains, and paper losses. It shows that paper losses are, on average, suboptimal, and that reducing the saliency of the purchase price has a significant effect on the number of paper losses: they decrease from Realized gains and realized losses are optimal when the REV is positive, whereas paper gains and paper losses are optimal when the REV is negative.
The chart shows that the LOW-SALIENCY treatment primarily affects behavior through the paper loss and paper gain channels; that is, the disposition effect is attenuated because of a reduction in paper losses and an increase in paper gains. As in the control condition, most subjects have positive estimates for both variables. Fourth, as shown in Figure 4 , we compare the distribution of estimated coefficients across the groups of subjects associated with each condition using unpaired two-tailed t-tests.
We estimate the logistic model in 9 , separately for each individual. For each condition we then compute the average coefficient across subjects , for both the REV and the CG regressors,. Fifth, as shown in Figure 4A , one limitation of the previous test is that there is significant heterogeneity across subjects in the extent to which they responded to the REV variable in both conditions. To address this concern, we construct a post hoc measure of the relative effect of the CG and the REV variables.
In particular, we compare the selling decisions of subjects in two experimental conditions. First, there is a HIGH-SALIENCY condition in which the purchase price of a stock is prominently displayed, and which is meant to resemble the information that is displayed on many financial statements and software trading platforms.
To the best of our knowledge, this is the first demonstration that it is possible to debias the disposition effect by reducing the saliency of information related to the computation of capital gains. The result is also interesting because it suggests that there are limitations to this type of intervention, since individuals exhibit a measure of PGR-PLR that is significantly above the optimal level even when the purchase price information is not explicitly displayed.
Importantly, the results show that the relative weights given to these two motives are not fixed, and instead are modulated by contextual variables, such as what information is made salient at the time of decision.
This result is interesting because it suggests that the saliency with which information is displayed during portfolio decisions has the potential to change preferences, and therefore impact investor behavior Libby et al. This motivates future analyses of investor behavior in which information saliency is incorporated explicitly.
Although we find that reducing the saliency of the purchase price has a sizable effect on the disposition effect, our experimental setup does not allow us to identify the specific channel through which the change in behavior occurs. However, as we emphasized above, this is not critical to our results, since they are consistent with any model of the disposition effect in which the capital gain variable is highly correlated with the utility of selling a risky asset.
These alternative models include theories of the disposition effect based on a belief in the mean reversion of prices and static models based on prospect theoretic preferences Odean ; Weber and Camerer Distinguishing among the competing theories of the disposition effect is an important and open question, not least because it will contribute to our understanding of how to best mitigate its costly effects for investors. Extrapolating from the lab, our results also provide a potential concrete recipe for debiasing the disposition effect in the field.
In particular, since investors who are prone to the disposition effect will trade to realize capital gains, and hold stocks with capital losses, regulators can potentially debias this effect by stipulating that brokerage houses decrease the saliency of information related to capital gains. We acknowledge that this intervention is not without complications for taxable accounts, since the purchase price carries useful information that allows the investor to compute the aftertax proceeds from realizing a capital gain.
However, our proposed policy intervention is well-suited for tax-free accounts, such as a Roth IRA, where the purchase price should be irrelevant. More broadly, our results suggest that regulators can potentially use saliency and attention as a powerful tool to influence investor and consumer behavior, by requiring subtle changes to the layout of financial statements Bertrand and Morse ; Choi et al. Specifically, in order to increase compliance with paying capital gains tax, this legislation mandates that investors must decide, at the time of trading, which cost basis method they will use when reporting capital gains for tax purposes.
Previously, investors decided this method after the trading decision, and so this legislation effectively increases the saliency of the cost basis during the decision phase. Our experimental results suggest that this may have a systematic and detrimental effect on the trading performance of some individual investors.
Future research should take advantage of the fact that this new legislation introduces a useful opportunity to test the effect of information saliency on trading behavior. In particular, a testable implication of our results is that the new cost basis legislation should induce investors to pay more attention to capital gains, and this should lead to a higher average disposition effect among individual investors starting in January However, both data from the field and from experiments have cast doubt on each of these explanations Odean ; Weber and Camerer ; Frydman et al.
For example, this feature allows us to test if an increase in the price of stock A at time t impacts buying or selling decisions for stocks B and C in the second part of the trial. We do not find evidence for such cross-stock effects, and thus they are not discussed further. The actual value of selling takes into account the expected cumulative price change of the stock until it is optimal to sell it, whereas our definition only takes into account the expected one-period price change.
However, our definition of REV i,t , is highly correlated with the actual value of selling, which can be computed by simulation. If subjects do not discount the future heavily, but instead have concave realization utility over gains, this would also generate a disposition effect. However, under our assumption that the trader is essentially myopic, the value of holding is zero.
It may seem surprising that a subject would discount future utility at a high rate in the context of a minute experiment. However, the literature on hyperbolic discounting suggests that discounting can be steep even over short intervals, perhaps because people distinguish sharply between rewards available right now and rewards available at all future times. Furthermore, what may be important in our experiment is not so much calendar time, as transaction time.
A subject who can trade stock B now may view the opportunity to trade it in the future as a very distant event - one that is potentially dozens of screens away — and hence one that he discounts heavily. In particular, recent theoretical models of trading in a dynamic setting show that it is often difficult to generate a disposition effect with prospect theory preferences Barberis and Xiong ; Kaustia ; Hens and Vlcek J Econ Behav Organ. Author manuscript; available in PMC Mar Cary Frydman 1 and Antonio Rangel 2.
Author information Copyright and License information Disclaimer. Corresponding author. Cary Frydman: ude. Copyright notice. See other articles in PMC that cite the published article. Abstract The disposition effect refers to the empirical fact that investors have a higher propensity to sell risky assets with capital gains compared to risky assets with capital losses, and it has been associated with low trading performance.
Keywords: debiasing, disposition effect, attention, behavioral finance, realization utility, decision mistakes. Introduction A considerable effort in behavioral economics has been devoted to documenting systematic biases exhibited by investors and understanding the impact that these biases have on trading performance Shleifer ; Barberis and Thaler ; Campbell Related Literature Our study is related to several literatures in behavioral finance, which we discuss here. Experimental Design 3.
Open in a separate window. Figure 1. Measuring the Disposition Effect We now describe our method for calculating the disposition effect at the individual subject level, which follows a similar methodology to that of Odean Theory and Hypotheses In this section we present a simple model of selling decisions, and use it to derive hypotheses about the effect of making the purchase price less salient.
Results 5. Figure 2. Figure 3. Figure 4. Comparison of group estimates across conditions We estimate the logistic model in 9 , separately for each individual. References Barberis Nicholas, Thaler Richard. Handbook of the economics of finance. Elsevier; A survey of behavioral finance. What drives the disposition effect? An analysis of a long-standing preference-based explanation. Journal of Finance. Realization utility.
Journal of Financial Economics. Are investors really reluctant to realize their losses? Trading responses to past returns and the disposition effect. Review of Financial Studies. Information disclosure, cognitive biases, and payday borrowing. The Journal of Finance.
Salience and consumer choice.
Selling winning stocks just because they're going up is not a winning strategy. The best strategy is to accept that portfolio concentration is inevitable and enjoy having big winners. If a stock insists on doubling over and over again, I wouldn't deliberately reduce my allocation to it unless I felt it had become significantly overvalued. That said, although winners tend to keep winning, you don't want your entire portfolio in one stock. In my opinion, letting a position grow to over 40 percent is likely too much concentration in one position.
The key thing to know however is that it grew to that number, so we aren't necessarily risking flushing our principal down the drain. If this sounds like a somewhat unscientific number, it's because it is. Investors selling too much too early causes the observed momentum effect in stocks in my opinion, so benefiting from the momentum effect trumps the benefit of diversifying away from winners too early in my decision-making process.
Also, while riskier than an "academically" diversified portfolio, having percent of your portfolio in AAPL due to the amazing rally over the last 10 years is nothing compared to the risk of having all your capital tied up in a small business, like a family restaurant or store. One painless way to diversify away from winning positions is to reinvest the dividends from the winners in new ideas.
At some point, however, you need to start diversifying and sell, even if it is beneficial to have a higher tolerance for stocks taking over your portfolio than your peers. If your portfolio is over 40 percent Apple or Amazon because you've owned it for long enough, make the easy call and get yourself to the nearest Mercedes dealership.
The other takeaway you should get from this is that our natural tendency is towards loss aversion. While asset allocation works great on an asset class level, in an equity portfolio it's a good way to have a portfolio full of losers. I'll use an example to show what not to do. Don't focus too much on the individual companies, only on the concept.
There are hundreds of studies on loss aversion as it relates to economics, but in this case, consider your options. The most popular option is going to be to sell the winner to raise cash. However, by consistently selling winners, portfolio managers slowly poison their portfolios with junk companies and pare back their positions of winning stocks. This causes major underperformance. This is actually what passive ETFs do to combat the disposition effect.
To sell proportionally, all you have to do is find the weight each holding has in your portfolio and take a little from each stock according to your weighting. By doing this, you ensure that pulling money out does not affect your asset allocation, only your investment decisions do. Note that the AAPL weighting in this portfolio is exaggerated by there only being two securities in the portfolio. I did a 2 stock portfolio only to simplify things.
More institutional investors need to make this a rule and enforce it, by the way. It would eliminate a major cause of underperformance. In our model portfolio you likely would be concentrating too much risk in one holding percent! I would typically recommend option number 2, as I believe there is something to be said for your asset allocation being driven by your investment decisions and not your personal ones. In case you were wondering, both investments ended up holding their own from , at which point AAPL took off and GE tanked.
Today, if you chose option 3, you'd be closing in on having a million dollars worth of AAPL and not a penny invested in the GE dumpster fire. Investing in a company with the returns of Apple or Amazon is an amazing experience, but strong performers tend to take over your portfolio.
This is inevitable. Academic research shows that tolerating a somewhat higher concentration caused by prior outperformance leads to better returns via the momentum effect. That said, you don't want half your portfolio in one stock. By understanding statistics and psychology, you can benefit from the biases of other investors, let winners ride longer and avoid filling up your portfolio with losers.
Enjoy this article? Scroll to the top of the page and follow me! I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it other than from Seeking Alpha. I have no business relationship with any company whose stock is mentioned in this article.
Logan Kane The authors of the disposition effect, Shefrin and Statman, identified 4 possible causes for this behavioural bias. The theory suggests that when a person is given two equal choices, one described from the perspective of probable gains and the other from the perspective of probable losses, the person will more likely choose the former variant, even though both could bring the same economic result.
The theory predicts that traders feel the pain of loss twice stronger than the joy of gain. Selling at a loss, even if it seems totally rational, means admitting a trader was wrong, which is hard for many people. Holding the stock allows him to avoid the feeling of regret, which follows the mistakes we make. In case of a winning trade, holding onto it means risking the profit a trader has already made. Taking a small profit instead creates the feeling of pride.
By doing so, they focus on the performance of each and every trade, instead of tracking the performance of their portfolio as a whole. This is an example of a narrow framing. It makes hard to sell a losing stock, because traders see it as closing the mental account at a loss. Though the rational part of our mind reminds us that selling winners and not letting losers go is a wrong behavioural pattern, we still often struggle to take the necessary actions.
Tied strongly to emotions, the key to overcoming the disposition bias is by looking towards logic rather than emotion. Ask yourself — do you have a tendency to remain idle during losses and hope for a price swing in the expected direction? How quickly do you close your profitable positions? Do you fear losing the minimum profit?
If you answered yes to any of these questions, you could be influenced by the disposition effect. Overcome it by treating the markets logically and understanding their movements, and in doing so, you can start making more logical, successful trades.
By being aware of the disposition effect, you are on your first step to overcoming it. The next step is to be able to cut your losses and let your profits run. Menu Search en. Log In Trade Now My account. Healthcare ETF Education Investmate. Market updates Webinars Economic calendar Capital. Learn to trade The basics of trading Glossary Courses. Popular markets guides Shares trading guide Commodities trading guide Forex trading guide Cryptocurrency trading guide Indices trading guide ETFs trading guide.
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What is a disposition effect? Who was the first to describe the disposition effect? Disposition bias in trading and investing Suffering from the disposition effect, traders usually hold on to losing trades and sell the winning ones. Great stocks are hard to find Did you know how difficult and rare it is to find truly great companies to trade? Selling winners is tax inefficient Taxes could drastically reduce the benefits of growth over time.
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