The Evidence-Based Investor

Tag Archive: Itzhak Ben-David

1. How a 52-week high hurts returns

   September 22, 2022 8:42 am Comments Off on How a 52-week high hurts returns

    

    

   LARRY SWEDROE

    

   The 52-week high (52WH), the highest price a stock has traded for over the prior 365 days, is one of the key pieces of information communicated by the financial press. Research has found increased trading volume near the 52WH as well as subsequent price continuation (momentum). Explanations for the 52WH effect have come from the field of behavioral finance and include the disposition effect, prospect theory, attention and anchoring.

    

   The disposition effect

   The disposition effect, initially described by Hersh Shefrin and Meir Statman in their 1985 paper The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence, is the tendency to sell winning investments prematurely to lock in gains, and hold on to losing investments too long in the hope of breaking even. Standard explanations for the disposition effect—such as tax considerations, portfolio rebalancing and informed trading—have been proposed and dismissed, leaving explanations that rely on investor preferences such as prospect theory. Prospect theory implies a willingness to maintain a risky position after a loss and to liquidate a risky position after a gain. It also requires that investors derive utility as a function of gains and losses rather than the absolute level of consumption. 

   As Toby Moskowitz explained in his 2010 paper Explanations for the Momentum Premium, the disposition effect “creates an artificial headwind: when good news is announced, the price of an asset does not immediately rise to its value due to premature selling or lack of buying. Similarly, when bad news is announced, the price falls less because investors are reluctant to sell.” The disposition effect therefore creates predictability in stock returns and thus provides an explanation for the momentum premium. Further support for the disposition effect has been provided by Itzhak Ben-David and David Hirshleifer, authors of the 2010 study Are Investors Really Reluctant to Realize Their Losses? Trading Responses to Past Returns and the Disposition Effect, who found that investors sell more when they have larger gains and losses. Stocks with both larger unrealised gains and larger unrealised losses (in absolute value) will thus experience higher selling pressure. This temporarily pushes down current prices and leads to higher subsequent returns when future prices revert to their fundamental values.

   More evidence on the important role played by prospect theory was provided by Nicholas Barberis, Lawrence Jin and Baolian Wang, authors of the 2019 study Prospect Theory and Stock Market Anomalies, who found that it helped explain 13 of the most prominent anomalies in finance, including momentum.

    

   Investor attention

   Studies on the role of investor attention have found that individual investors are net buyers of attention-grabbing stocks, which consequently leads to contemporaneous positive price pressure and thus lower future returns. For example, Hung Nguyen and Mia Pham, authors of the 2021 study Does Investor Attention Matter For Market Anomalies, examined the impact of investor attention on 11 stock market anomalies in U.S. markets and found that they were well explained by measures of investor attention—levels of investor attention are associated with the degree of mispricing, with anomalies being stronger following high rather than low attention periods. Their findings led them to conclude: “The results are consistent with the conjecture that too much attention allocated to irrelevant information triggers investor overreaction to information. Once the mispricing is corrected, more anomaly returns are realized following high attention periods.” Their findings were consistent with those of Jian Chen, Guohao Tang, Jiaquan Yao and Guofu Zhou, authors of the 2020 study Investor Attention and Stock Returns, who also found that investor attention helps explain anomalies. The findings on investor attention explain why individual investors are referred to as “noise traders” — they react to irrelevant information. The result, as demonstrated by Noah Stoffman, author of the 2014 study Who Trades with Whom? Individuals, Institutions, and Returns, is that when institutions and individuals engage in trade with each other, prices move, and individuals tend to be on the losing side. 

   Further evidence on individual investor behaviour was provided by Brad Barber and Terrance Odean, who have performed a series of studies on retail investors, including Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors and Too Many Cooks Spoil The Profits: Investment Club Performance, demonstrating that the stocks individual investors buy tend to underperform on average, and the ones they sell go on to outperform — they are the proverbial suckers at the poker table who don’t know they are the suckers. 

    

   Anchoring

   Anchoring, the subconscious use of irrelevant information (such as the purchase price of a security) as a fixed reference point (or anchor) for making subsequent decisions about that security, is another well-documented cognitive investor bias and another reason individuals are referred to as noise traders. For example, market participants with an anchoring bias tend to hold investments that have gone down in price because they have anchored their fair value estimate to the higher price rather than to fundamentals. As a result, market participants assume greater risk by holding an investment in the hope the security will return to its original purchase price or previous high.

    

   Investor attention and the 52-week high

   Joshua Della Vedova, Andrew Grant and Joakim Westerholm, authors of the July 2022 study Investor Behavior at the 52-Week High, examined individual investor behaviour around the 52WH for stocks and how that behavior impacted performance. Their data sample was investor account-level data on all trades from the clearinghouse of the Nasdaq Helsinki exchange over the period 2000-2009. This dataset allowed them to classify traders as institutions or individuals and executed order types (limit order or market order), at and around the 52-week high price. That allowed them to see which party was demanding (via a market order) or supplying (via a limit order) liquidity with the corresponding trade price and quantity. Following is a summary of their findings:

   • As stock prices approached the 52WH, there was an exponential increase in household selling — it increased by 21 percent when a stock was at the 52WH.
   • On an average day, there was no trade imbalance between households and institutions.  However, stocks within 3 percent of the 52WH exhibited a net trade imbalance of -12 percent (net sellers were households). When a stock opened at the 52WH, the net trade imbalance increased to -31 percent, representing a large-scale transfer of ownership from households to institutions. 
   • There was a sharp increase in the use of limit order by households when selling near the 52WH. Conditional on selling, household limit order usage rose from 50 percent of all household orders when prices were at 97 percent of the 52WH, to 59 percent of household orders when at the 52WH price, compared to a baseline of 46 percent of household orders on non-52WH day s — there was an abnormal increase in liquidity provision by households to institutional investors.
   • When households were selling primarily with limit orders, returns averaged an excess of 0.7 percent over the following 90 days — in aggregate, substantial household limit order selling is a positive predictor of future returns. Stocks with high levels of limit order use by households exhibited even larger increases in returns.
   • The longer the time since the 52WH, the greater the trading volume.
   • While increased volatility (uncertainty) did not spark an increase in general selling, it did result in individuals using limit orders to anchor directly to the price. This finding is of interest because, during periods of uncertainty, liquidity provision tends to be more costly due to either increased spreads or higher adverse selection costs. By providing liquidity in an order book during periods of high uncertainty, individuals are adding a valuable option to other traders in the market.

   Vedova, Grant and Westerholm’s findings of the negative impact of the 52WK effect on individual investors is consistent with Terrance Odean’s finding in his 1998 study, Are Investors Reluctant to Realize Their Losses?, that stocks investors sold too quickly as a result of the disposition effect continued to outperform over the subsequent periods, while the losing assets they held on to for too long remained underperformers. 

   The authors’ findings led them to conclude: “Overall, the results support our expectations that households suffer, in the form of post-event returns, due to their anchoring behaviour. Moreover, the post-52WH returns are intensified by household liquidity provision. The disposition effect, anchoring, and the placement of unsupervised limit orders by households allow counter-parties to open up momentum-like positions that, in turn, generate significantly higher post-52WH returns and help to explain the continual under-performance of household investors.”  

    

   Investor takeaways

   The research demonstrates that the well-documented disposition effect, fuelled by investor attention, leads to an increase in the likelihood that individual investors will sell a stock as it begins to accumulate capital gains by increasing in price and that proximity to the 52-week high exacerbates the household willingness to sell to institutions. It also provides us with explanations for behavioral-based anomalies such as momentum, as well as an opportunity to better understand how our behaviours can negatively impact our results. 

   We cannot learn from our behavioural mistakes unless we are aware of them. Once we are aware of our biases, we can take actions to minimise the effect by setting investment goals and establishing rules (such as when to harvest losses). Having a written and signed investment plan, including a rebalancing table and defined goals, can help you avoid emotion-driven mistakes that lead to poor outcomes — the disposition effect can be de-biased. Do you have such a plan?

    

    

   For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice.  Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of Buckingham Strategic Wealth® and Buckingham Strategic Partners®, collectively Buckingham Wealth Partners.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency have approved, determined the accuracy, or confirmed the adequacy of this article. LSR-22-360

    

   LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.

    

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2. More evidence that specialised ETFs are best avoided

   March 8, 2022 6:16 pm Comments Off on More evidence that specialised ETFs are best avoided

    

    

    

   There has been a large increase in recent years in the number of specialised ETFs that offer exposure to different investment themes. But a new study has confirmed that thematic funds tend to underperform — and the very worst time to buy them is when they launch. That is mainly because specialised ETFs usually launch just after their theme has peaked, and immediately before a steep fall in returns. LARRY SWEDROE has the details.

    

   Since the introduction of the first ETF in 1993, more than 3,400 exchange-traded funds (ETFs) have been launched in the U.S. alone, with more than 1,000 investing in U.S. equities. By mid-2021 ETFs had captured more than $9 trillion in assets globally. ETFs have captured market share by offering investors the ability to track various indexes (or invest in various asset classes or thematic strategies) at lower costs (with expense ratios as low as 3 basis points), lowering fees, providing greater tax efficiency for taxable investors and allowing investors to trade during the day.  

   In their December 2021 study Competition for Attention in the ETF Space, authors Itzhak Ben-David, Francesco Franzoni, Byungwook Kim and Rabih Moussawi examined how the interplay between investors’ demand and providers’ incentives has shaped the evolution of ETFs. Their data sample included ETFs traded in the U.S. from the Center for Research in Security Prices (CRSP) between 1993 and 2019. Although all U.S. equity ETFs were included in the sample, some of the data items (e.g., holdings data) had limited availability in the pre-2000 period. Given data limitations, most of their empirical analysis began in January 2000, including all ETFs launched earlier, and ended December 2019. The sample contained 554 broad-based  (90 broad index and 464 smart beta) ETFs and 526 specialised (411 sector/industry and 115 thematic) ETFs. Following is a summary of their findings:

   • The ETF industry evolved along two separate paths. Early ETFs invested in broad-based indexes (mean/median expense ratio of 0.42 percent/0.35 percent), providing diversification at a low cost. Later products tracked niche (specialised, thematic, sector-based) portfolios and charged higher fees (mean/median expense ratio of 0.55 percent/0.58 percent) — investors who buy these ETFs are willing to overlook the higher fees or loss of diversification as long as they can gain exposure to their desired investment themes or can attempt to gain alpha. 
   • The specialised offerings cater to investor demand (sentiment) for popular, yet often overvalued, investment themes — stocks that are included in specialised ETFs have been favourably covered in the media. For example, in 2019 new ETFs included products focusing on cannabis, cybersecurity and video games. In 2020 new specialised ETFs covered stocks related to the Black Lives Matter movement, COVID-19 vaccines and the work-from-home trend. In 2021, tracking the recovery after the COVID recession, new specialised ETFs covered the travel industry and space travel as well as real estate and construction. The sentiment of the media, however, drops sharply after the time of ETF launch.
   • The portfolio of specialised stocks displayed significantly higher earnings growth forecasts on average. These forecasts became increasingly more positive in the period leading up to the launch. However, after the ETF launch, these stocks experienced a marked downward revision in growth expectations. No such pattern was found for the stocks in the broad-based portfolios.
   • While competition in the broad-based index category has led to a trend toward even lower fees, specialised ETFs fees have remained at higher levels. 
   • In 2019 specialised ETFs managed 18 percent of the industry’s assets, yet they generated about 36 percent of the industry’s fee revenues.
   • Specialised ETFs generated more volatile returns than did broad-based ETFs—not surprising, as they hold fewer names.
   • Flows to broad-based ETFs displayed a significantly higher sensitivity to fees, whereas flows to specialised ETFs were unrelated to fees and responded more strongly to past performance. Their low fees allowed the broad-based ETFs to show risk-adjusted returns after fees to be just slightly negative, though statistically indistinguishable from zero, versus the Fama-French-Carhart four-factor model (-0.24 percent per annum after fees).
   • ETF providers are unable to identify sectors and themes that deliver positive risk-adjusted returns. A portfolio of all specialised ETFs achieved risk-adjusted (relative to the four-factor model) returns of -3.24 percent per annum after fees. The results were only about half as bad when benchmarked against the Fama-French five-factor model. The underperformance could not be explained by high fees or hedging demand—they were driven by the overvaluation of the underlying stocks at the time of the launch (subject to recency bias, investors are performance chasers) that was reversed post-launch. 
   • The underperformance of specialised ETFs is especially severe in the first few years after their launch. Over their first 60 months, specialised ETFs generated four-factor alphas of -6.0 percent (t-stat = 4.0). Beyond 60 months alphas were -1.4 percent, a significant improvement, though still economically (though not statistically) significant (t-stat = 1.5). 
   • Specialised ETFs that were launched following lower prelaunch returns and media sentiment underperformed less—by “only” -2.4 percent per year. In contrast, specialised ETFs with portfolios in which stocks experienced prelaunch high returns and high media sentiment underperformed by 6.4 percent a year.
   • There was no evidence of hedging motives for the specialised ETFs, for which investors were willing to pay an insurance premium.
   • Specialised ETFs were more likely to experience capital outflows over their existence and experienced closures at a significantly higher rate (and the likelihood of closure was more sensitive to past performance). 
   • The price impact of flows could be sizeable under certain assumptions — negative flows could amplify the underperformance of specialised ETFs by up to 2.7 percent per year over the five-year horizon since inception.
   • Retail investors are likely to own a greater share of the specialised ETFs universe than that of the broad-based ETF universe — unsophisticated investors are more likely to be attracted to specialised ETFs. As an example, the number of Robinhood users scaled by market capitalisation was substantially higher for specialised ETFs than for broad-based ETFs in their first year of existence. 

   Overall, the cumulative evidence in the study supports the hypothesis that ETF providers cater to performance-chasing investors. Specifically, they launch new ETFs focused around themes that are popular among naive investors. The excitement around these popular investment themes, however, means that the related securities tend to be overvalued. As a result, the portfolios of new specialised ETFs tend to contain overvalued securities. As illustrated below in Figure 6 from the paper, the overvaluation dissipates over time, delivering poor returns to investors who chased performance. 

    

   

   Performance of the indexes underlying newly-launched ETFs

    

   Their findings led Ben-David, Franzoni, Kim and Moussawi to conclude: “Our results are consistent with providers catering to investors’ extrapolative beliefs by issuing specialised ETFs that track attention-grabbing themes. … Before ETFs inception, smart beta, sector/industry, and thematic ETFs, experience a price run-up.”

   The authors noted that their findings are consistent with prior literature showing that “mutual funds cater to investor sentiment in order to attract flows by heavily weighting past winners and changing their names to trendy ones.” They found that their measure of media sentiment (the sum of each news article’s composite sentiment score from RavenPack scaled by market capitalisation) was 0.22 for broad-based ETFS but almost three times that, at 0.64, for specialised ETFs.

   Ben-David, Franzoni, Kim and Moussawi also found that the stocks held by specialised ETFs displayed more positive skewness (0.17 versus 0.01), which would be appealing for investors who have a preference for stocks with lottery-like payoffs (that have subsequently delivered poor returns historically). Finally, they noted that specialised ETFs tend to have more exposure to small growth stocks that have high valuation multiples (notably the market-to-book, price-to-sales, and enterprise value-to-earnings before interest, taxes, depreciation and amortisation ratios) and higher short interest: “All these characteristics are associated with lower future returns.”  

    

   Investor takeaways

   The evidence presented demonstrates that specialised ETFs at inception tend to own popular stocks about which investors are very enthusiastic (due to recency bias, resulting in performance chasing). Relative to broad-based portfolios, stocks in specialised ETFs experience greater media exposure with more positive sentiment. However, investor enthusiasm fades over time as performance deteriorates because sentiment has driven prices to excessive levels. 

   The above findings demonstrate that the ETF industry is great at capitalising on naïve retail investors’ preference for investment fads. In general, they are issued in response to the demand for trendy investment themes — the fund sponsors are responding to investor sentiment, which studies such as Global, Local, and Contagious Investor Sentiment, The Short of It: Investor Sentiment and Anomalies, Investor Sentiment and the Cross-Section of Stock Returns and Investor Sentiment: Predicting the Overvalued Stock Market have found to be a negative predictor of future returns. The high fees and cash flows into these poorly performing securities is just another example of retail investors behaving badly. 

   While broad-based and factor-based ETFs have brought investors the benefits of lower costs and greater tax efficiency, the specialised ETFs have created negative value — except for their sponsors, of course.

   The evidence demonstrates that specialised ETFs, on average, do not create value for investors. In other words, popularity is a curse in investing, not a blessing. Investors are best served by having a well-thought-out investment plan and, like a stamp to a letter, adhere to it until they reach their destination. Forewarned is forearmed.

    

   For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice.  Certain information is based upon third party data which may become outdated or otherwise superseded without notice.  Third party information is deemed to be reliable, however its accuracy and completeness cannot be guaranteed. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of the Buckingham Strategic Wealth® or Buckingham Strategic Partners®, collectively Buckingham Wealth Partners. Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency have approved, determined the accuracy, or confirmed the accuracy of this article. LSR-22-2

    

   LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.

    

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3. Disposition effect hampers active managers, study shows

   March 4, 2022 2:24 pm Comments Off on Disposition effect hampers active managers, study shows

    

    

   By LARRY SWEDROE

    

   In their 1985 study, The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence, Hersh Shefrin and Meir Statman introduced into the behavioural finance literature the disposition effect — the tendency of individual investors to sell assets that have increased in value while keeping assets that have dropped in value. This trading behaviour has been documented using evidence from both individual and institutional investors across different asset markets and around the world. 

   In their 2018 study, Are Investors Really Reluctant to Realize Their Losses? Trading Responses to Past Returns and the Disposition Effect, Itzhak Ben-David and David Hirshleifer investigated this behavioural pattern further and found that the probability of selling as a function of profit is actually V-shaped: At short holding periods, investors are more likely to sell big losers than small ones — individual investors trade in response to the size as well as the sign of profits (gains or losses). They also found that the V is asymmetric: The right branch is steeper than the left branch — the main source of the disposition effect. They also found that the Vs for both selling and buying are steeper for frequent traders and for male investors (who tend to be more overconfident)—consistent with a speculative motive for trading as a contributor to the V. And they found little evidence that tax-loss selling steepens the left branch in the last quarter or last month of the year.

    

   New research

   Li An and Bronson Argyle contribute to the behavioural finance literature with their study Overselling Winners and Losers: How Mutual Fund Managers’ Trading Behavior Affects Asset Prices, published in the September 2021 issue of the Journal of Financial Markets, in which they examined the selling pattern of mutual fund managers to determine if they exhibited the same trading behaviours found in individual investors. They began by noting: “While studying the trading behaviour of retail investors is interesting and significant, mutual fund managers command much more capital, are arguably more sophisticated than retail investors, and play a larger role in deciding equilibrium prices.” Their database is from Thomson Reuters and covers the period 1980-2018. Following is a summary of their findings:

   • U.S. mutual fund managers, like presumably less sophisticated retail investors, are more likely to sell holdings with large unrealised gains and losses rather than those with small unrealised gains and losses (they exhibit a V-shaped pattern). 
   • The V-shaped pattern creates selling pressure, pushing down current prices (for non-fundamental reasons), leading to higher future returns — their behaviour temporarily depresses the price of affected securities. As future prices revert to fundamental values, affected stocks will outperform, creating return predictability in the cross-section. 
   • Aggregating across funds, securities for which investors have large unrealised gains and losses outperform in the subsequent month. The price effect is both economically and statistically significant — a 10 percentage point increase in the aggregate unrealised gains (losses) for a stock predicts a 9 (5) basis point increase in next month’s returns. (The price effect of gain overhang is 1.8 times as large as that of loss overhang.) A long-short portfolio strategy based on this effect can generate a monthly alpha of approximately 0.5 percent, with a Sharpe ratio equal to 1.2. 
   • The results were strongest in smaller cap stocks.
   • Fund managers’ selling responses to unrealised profit weakens as the holding time becomes longer — consistent with findings on retail investors.
   • Funds with larger turnover, shorter holding period and higher expense ratios are significantly more likely to manifest this trading pattern, and unrealised profits from such funds have stronger return predictability. 
   • Decomposing security-level unrealised gains and losses into those from “more-disposition-prone” funds and those from “less-disposition-prone” funds, they found that unrealised profits from the more-disposition-prone funds are stronger in predicting future returns. 
   • The price impact of the V-shaped trading behaviour is unrelated to flow pressure — the trading tendency of mutual fund managers is the source of the price deviation from fundamentals.
   • Investors’ selling response to unrealised profit is not likely be the source of the momentum effect, as loss overhang and the loser leg in momentum have opposite return predictions.

   Interestingly, An and Argyle found that stocks with large gain and loss overhangs tend to be those with high idiosyncratic volatility (IVOL). Yet, the historical evidence demonstrates that stocks with high IVOL tend to have low future returns. However, when An and Argyle controlled for IVOL, the results of their predictive overhang variables were strengthened.

    

   Investor takeaways

   An and Argyle demonstrated that retail investors are not alone in exhibiting V-shaped trading behaviour that affects asset prices in predictable ways — actively managed mutual fund managers are just as guilty of being subject to behavioural biases, as they trade in response to the size as well as the sign of their gains or losses. And that behaviour negatively impacts their performance, just as it does the performance of individual investors. Thus, their evidence provides another contributing factor to the persistently poor performance of actively managed funds. For individual investors who still trade individual stocks, their findings should at least provide a wake-up call. Being aware of a bias is the first and necessary step in avoiding actions based on that bias. Forewarned is forearmed.  

    

   For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is based upon third party information and may become outdated or otherwise superseded without notice.  Third party information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed.   By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of the Buckingham Strategic Wealth® or Buckingham Strategic Partners®, collectively Buckingham Wealth Partners. LSR-21-206

    

    

   LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.

    

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4. The disposition effect: why traders sell at the wrong time

   November 23, 2021 11:56 am Comments Off on The disposition effect: why traders sell at the wrong time

    

    

   To be a successful active investor, you don’t just need to buy the right stocks at the right time; you also have to decide which stocks to sell and when to sell them. The problem is, investors are prone to what behavioural finance experts call the disposition effect, or the tendency to sell winning investments prematurely to lock in gains and hold on to losing investments too long in the hope of breaking even. And, as new research shows, it’s not just individual investors who sell at the wrong time: professionals fund managers are very much to prone it as well.

    

   A large body of academic evidence demonstrates that individual investors are subject to the “disposition effect”. It has been documented among U.S. retail stock investors, foreign retail investors, homeowners, corporate executives and in experimental settings. Those suffering from this phenomenon, which was initially described by Hersh Shefrin and Meir Statman in their 1985 paper, The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence, tend to sell winning investments prematurely to lock in gains and hold on to losing investments too long in the hope of breaking even.

   Standard explanations for the disposition effect — such as tax considerations, portfolio rebalancing and informed trading — have been proposed and dismissed. That leaves explanations that rely on investor preferences, such as prospect theory. Prospect theory implies a willingness to maintain a risky position after a loss and to liquidate a risky position after a gain. It also requires that investors derive utility as a function of gains and losses rather than the absolute level of consumption. Other behavioural explanations include (1) mental accounting (how individuals classify personal funds differently and are therefore prone to irrational decision-making in their spending and investment behaviour), (2) pride seeking and regret aversion, and (3) lacking self-control.

   As Toby Moskowitz explained in his 2010 AQR working paper, Explanations for the Momentum Premium, the disposition effect “creates an artificial headwind: when good news is announced, the price of an asset does not immediately rise to its value due to premature selling or lack of buying. Similarly, when bad news is announced, the price falls less because investors are reluctant to sell.” The disposition effect therefore creates predictability in stock returns and thus provides an explanation for the momentum premium.

   Additional research into the disposition effect, including a 2012 study by Itzhak Ben-David and David Hirshleifer, Are Investors Really Reluctant to Realize Their Losses? Trading Responses to Past Returns and the Disposition Effect, found that investors sell more when they have larger gains and losses. Stocks with both larger unrealised gains and larger unrealised losses (in absolute value) will thus experience higher selling pressure. This temporarily pushes down current prices and leads to higher subsequent returns when future prices revert to their fundamental values. They also found that the average propensity to sell following a gain is higher than the average propensity to sell following a loss.

   Li An, Joseph Engelberg, Matthew Henriksson, Baolian Wang and Jared Williams contribute to the research on the disposition effect with their January 2018 study, The Portfolio-Driven Disposition Effect, in which they sought to determine whether the disposition effect operates at the individual asset level or at the portfolio level. They found:

   • There is no disposition effect for a stock if the remaining portfolio is up. However, if the remaining portfolio is down, a stock with a gain is more than twice as likely to be liquidated than a stock with a loss. (Note that, at least for taxable accounts, this is the opposite of what efficient tax management requires, which is the harvesting of losses). The results were significant at well below the 1 percent level of statistical significance (t-stats were in the 20s).
   • The authors reached the same results when they considered proxies for investor sophistication, such as professional jobs or high income.

   An, Engelberg, Henriksson, Wang and Williams concluded that the most likely explanation for the effect “is that investors derive utility from both paper gains and realized gains and that they take utility by realising gains when they have disutility from unrealised losses.” The authors added: “When their portfolio has paper losses, they compensate by realising gains.” They explained: “When an investor’s overall portfolio is down, the investor will receive a lot of negative utility from the paper losses, so she should be especially likely to seek a burst of positive utility from realising a paper gain to offset some of the negative utility she has received due to the poor performance of her portfolio. This could explain why we find such a strong disposition effect when an investor’s portfolio is down.”

   Another interesting finding was that when a stock is at a gain but the portfolio is at a loss, upon realising the gain, investors are most likely to keep the proceeds in cash — it is important to investors that the gain “stay” realized.

   The bottom line is that the disposition effect entails adverse consequences for investors’ investment performance. For example, in his 1998 study, Are Investors Reluctant to Realize Their Losses?, Terrance Odean found that the stocks investors sold too quickly as a result of the disposition effect continued to outperform over the subsequent periods, while the losing assets they held on to for too long remained underperformers.

    

   Latest research

   Li An and Bronson Argyle contribute to the behavioural finance literature with their study Overselling Winners and Losers: How Mutual Fund Managers’ Trading Behavior Affects Asset Prices published in the September 2021 issue of the Journal of Financial Markets, in which they examined the selling schedule of mutual fund managers in response to unrealised profits. Their data sample covered the period 1980-2018. Following is a summary of their findings:

   • Given an unrealised gain and loss of the same magnitude, mutual fund managers are 1.8 times as likely to sell the gain as to sell the loss.
   • Larger magnitudes in both unrealised gains and losses are associated with more selling.
   • Consistent with findings on retail investors, managers’ selling response to unrealised profit weakens as the holding time becomes longer.
   • U.S. equity mutual fund managers, like supposedly less sophisticated retail investors, tend to sell both their big winners and big losers — the selling pressure pushes down current prices for non-fundamental reasons and thus leads to higher future returns.
   • Stocks with large unrealised gains and losses outperform in the next month, and the price effect is both economically and statistically significant — a 10 percentage point increase in the aggregate unrealised gains (losses) for a stock predicts a 9 (5) basis points increase in the next month’s returns. A long-short portfolio strategy based on this effect produced a monthly alpha of approximately 0.5%, with a Sharpe ratio of 1.2.
   • Aggregating across funds, securities for which investors have large unrealised gains and losses outperform in the subsequent month. 
   • Funds with larger turnover, shorter holding period and higher expense ratios are significantly more likely to manifest this trading pattern, and unrealised profits from such funds have stronger return predictability. This tendency was not stronger among funds whose managers graduated from institutions with higher average SAT scores, consistent with this being a biased behaviour.
   • The price effect of the disposition effect is absent in the largest firms.
   • Their findings were robust to several alternative measures.

   Their findings led An and Argyle to conclude: “Mutual fund managers, like individual retail investors, exhibit a V-shaped disposition effect — they are more likely to sell both their big winners and losers. Aggregated across fund managers, this behaviour has an impact on equilibrium prices.

   “The subset of funds with higher turnover, shorter holding period, and higher expense ratios are more likely to exhibit the V-shaped disposition effect, and paper gains and losses aggregated across these subsets of funds have stronger return predictability.

   “Taken together, this evidence [provides] insight on the pattern, the pricing implications, and the underlying mechanism of the disposition effect. Our results closely tie observed price variation to investors’ behaviour and suggest that seemingly biased trading tendencies can aggregate to predictably affect equilibrium prices.”

    

   Investor takeaway

   The well-documented disposition effect not only provides us with explanations for behavioural-based anomalies, such as momentum, but also with an opportunity to better understand how our behaviours (including those of professional fund managers) can negatively impact our results.

   We cannot learn from our behavioural mistakes unless we are aware of them. However, once we become aware of our biases, we can take actions to minimise the effect by setting investment goals and establishing rules (such as when to harvest losses and when to rebalance). Having a written and signed investment plan, including a rebalancing table and defined goals, can help you avoid emotion-driven mistakes that lead to poor outcomes. Do you have such a plan?

    

   For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is based upon third party data which may become outdated or otherwise superseded without notice. Third party information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of the Buckingham Strategic Wealth® and Buckingham Strategic Partners®, collectively Buckingham Wealth Partners. Neither the Securities and Exchange Commission (SEC) nor any state or federal agency has approved, confirmed the accuracy, or determined the adequacy of this article. LSR-21-164

    

   LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.

    

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