Findings

Best market ever

Kevin Lewis

January 29, 2019

Decision Fatigue and Heuristic Analyst Forecasts
David Hirshleifer et al.
Journal of Financial Economics, forthcoming

Abstract:

Psychological evidence indicates that decision quality declines after an extensive session of decision-making, a phenomenon known as decision fatigue. We study whether decision fatigue affects analysts’ judgments. Analysts cover multiple firms and often issue several forecasts in a single day. We find that forecast accuracy declines over the course of a day as the number of forecasts the analyst has already issued increases. Also consistent with decision fatigue, we find that the more forecasts an analyst issues, the higher the likelihood the analyst resorts to more heuristic decisions by herding more closely with the consensus forecast, self-herding (i.e., reissuing their own previous outstanding forecasts), and issuing a rounded forecast. Finally, we find that the stock market understands these effects and discounts for analyst decision fatigue.


The Economic Impact of Index Investing
Jonathan Brogaard, Matthew Ringgenberg & David Sovich
Review of Financial Studies, forthcoming

Abstract:

We study the impact of index investing on firm performance by examining the link between commodity indices and firms that use index commodities. Around 2004, commodity index investing dramatically increased. This event is referred to as the financialization of commodity markets. Following financialization, firms that use index commodities make worse production decisions, earn 40% lower profits, and have 6% higher costs. Consistent with a feedback channel in which market participants learn from prices, our results suggest that index investing distorts the price signal, thereby generating a negative externality that impedes firms' ability to make production decisions.


Characteristics of Mutual Fund Portfolios: Where Are the Value Funds?
Martin Lettau, Sydney Ludvigson & Paulo Mandel
NBER Working Paper, December 2018

Abstract:

This paper provides a comprehensive analysis of portfolios of active mutual funds, ETFs and hedge funds through the lens of risk (anomaly) factors. We show that that these funds do not systematically tilt their portfolios towards profitable factors, such as high book-to-market (BM) ratios, high momentum, small size, high profitability and low investment growth. Strikingly, there are virtually no high-BM funds in our sample while there are many low-BM “growth” funds. Portfolios of “growth” funds are concentrated in low BM-stocks but “value” funds hold stocks across the entire BM spectrum In fact, most “value” funds hold a higher proportion of their portfolios in low-BM (“growth”) stocks than in high-BM (“value”) stocks. While there are some micro/small/mid-cap funds, the vast majority of mutual funds hold very large stocks. But the distributions of mutual fund momentum, profitability and investment growth are concentrated around market average with little variation across funds. The characteristics distributions of ETFs and hedge funds do not differ significantly from the those of mutual funds. We conclude that the characteristics of mutual fund portfolios raises a number of questions about why funds do not exploit well-known return premia and how their portfolio choices affects asset prices in equilibrium.


Doing Less With More
Rawley Heimer & Alex Imas
Boston College Working Paper, December 2018

Abstract:

According to standard theories of decision-making, access to leverage should make investors better off. The ability to borrow expands investors' choice sets, allowing them to take advantage of trading opportunities without having to liquidate current holdings. This paper argues that leverage can interact with existing behavioral biases -- specifically, the reluctance to realize losses -- to impair decision-making and hurt performance. Two data sources provide support for this claim. First, we exploit regulation that restricts the amount of leverage available to U.S. retail traders of foreign exchange. Traders constrained by the regulation are more willing to realize losses, exhibiting a smaller disposition effect, and improve their market timing. We replicate these findings in an experimental asset market. Access to leverage leads to significantly lower earnings. This decrease in performance is driven by levered participants holding on to losses for longer, deviating further from an optimal trading strategy than those without access to leverage. Together, our findings imply more choice may not always be better than less and suggest scope for policy to improve financial decision-making.


The Favorite-Longshot Midas
Etan Green, Haksoo Lee & David Rothschild
University of Pennsylvania Working Paper, June 2018

Abstract:

The favorite-longshot bias in horse-race betting markets, previously attributed to speculation or irrationality, instead results from profitable deception. Racetracks provide bettors with predictions that overestimate the chances of longshots and underestimate the chances of favorites. This deception creates arbitrage opportunities, which the track monetizes by taxing the arbitrageurs. Similar schemes enrich other market makers, such as investment banks during the boom in mortgage-backed securities.


Selling Fast and Buying Slow: Heuristics and Trading Performance of Institutional Investors
Klakow Akepanidtaworn et al.
University of Chicago Working Paper, December 2018

Abstract:

Most research on heuristics and biases in financial decision-making has focused on non-experts, such as retail investors who hold modest portfolios. We use a unique data set to show that financial market experts - institutional investors with portfolios averaging $573 million - exhibit costly, systematic biases. A striking finding emerges: while investors display clear skill in buying, their selling decisions underperform substantially - even relative to strategies involving no skill such as randomly selling existing positions - in terms of both benchmark-adjusted and risk-adjusted returns. We present evidence consistent with limited attention as a key driver of this discrepancy, with investors devoting more attentional resources to buy decisions than sell decisions. When attentional resources are more likely to be equally distributed between prospective purchases and sales, specifically around company earnings announcement days, stocks sold outperform counterfactual strategies similar to buys. We document managers' use of a heuristic that overweights a salient attribute of portfolio assets - past returns - when selling, whereas we do not observe similar heuristic use for buys. Assets with extreme returns are more than 50% more likely to be sold than those that just under- or over-performed. Finally, we document that the use of the heuristic appears to a mistake and is linked empirically with substantial overall underperformance in selling.


Preliminary findings on cryptocurrency trading among regular gamblers: A new risk for problem gambling?
Devin Mills & Lia Nower
Addictive Behaviors, May 2019, Pages 136-140

Abstract:

Cryptocurrencies are emerging digital currencies that allow anonymity in accessing various risk-taking activities through the Internet (e.g., drugs, gambling). However, given conceptual links to high-risk stocks, the present study sought to assess the association between trading cryptocurrencies and problem gambling. Data was collected through a cross-sectional online survey. Advertisement for the survey was posted on Amazon's Mechanical Turk. Participants were adults who had gambled at least monthly in the past year (N = 876; 58.33% male; M = 33.74 years, SD = 9.73). Participants completed the Problem Gambling Severity Index, Patient Health Questionnaire (2-item version), and Generalized Anxiety Disorder scale (2-item version). Trading cryptocurrencies is strongly associated with problem gambling severity (r = 0.53, p < .001). Results from a linear regression with backwards elimination revealed that sports betting, daily fantasy sports, high-risk stock trading, and problem gambling severity contribute to trading cryptocurrencies more frequently in the past year, whereas gambling in on-land casinos contributed to less cryptocurrency trading. Finally, trading cryptocurrencies overlapped strongly with trading high-risk stocks. Moreover, gamblers who engaged in both forms of trading reported greater problem gambling and depression and anxiety symptoms relative to those trading either cryptocurrencies or high-risk stocks, but not both. The present results suggest that trading cryptocurrencies may be appealing to gamblers that are exhibiting greater problem gambling severity. Future research should begin to include cryptocurrency trading in screening, assessment, and treatment protocols, particularly with regular gamblers.


Analysts to the rescue?
Andreas Charitou, Irene Karamanou & Neophytos Lambertides
Journal of Corporate Finance, forthcoming

Abstract:

This study investigates the role of financial analysts as information providers following an exogenous negative shock in disclosures. We use the SEC's decision to eliminate the reconciliation requirement for cross-listed companies to examine whether this loss of information prompted financial analysts to provide more informative research reports. We first document that the informativeness of analyst earnings forecasts increased, on average, in the post-regulation period for the sample of firms that stopped providing the reconciliation information. We next relate this change in informativeness to stock liquidity, a common proxy for information asymmetry. We find that for firms with greater analyst informativeness, market liquidity was not affected by the loss of information. In contrast, for firms with lower analyst informativeness liquidity actually decreased. We validate these results by showing that analysts increased the informativeness of their reports when the loss of information, captured by the magnitude of the reconciliation, increased. Results are also robust to both an alternative measure of analyst informativeness that controls for the level of forecast surprise, and to the extension of the post-regulation period to mitigate the effects of the financial crisis. These results support the conjecture that, when analysts compensate for the loss of information, the firm's information environment is not affected. We conclude that analysts can play an important role in capital markets and their research can be especially valuable in times of information shortage.


Media Sentiment and International Asset Prices
Samuel Fraiberger et al.
NBER Working Paper, December 2018

Abstract:

This paper assesses the impact of media sentiment on international equity prices using a dataset of more than 4.5 million Reuters articles published across the globe between 1991 and 2015. Media sentiment robustly predicts daily returns in both advanced and emerging markets, even after controlling for known determinants of stock prices. But not all news sentiment is alike. A local (country-specific) increase in news optimism (pessimism) predicts a small and transitory increase (decrease) in local returns. By contrast, changes in global news sentiment have a larger impact on equity returns around the world, which does not reverse in the short run. Media sentiment affects mainly foreign – rather than local – investors: although local news optimism attracts international equity flows for a few days, global news optimism generates a permanent foreign equity inflow. Our results confirm the value of media content in capturing investor sentiment.


A Picture Is Worth a Thousand Words: Market Sentiment From Photos
Khaled Obaid & Kuntara Pukthuanthong
University of Missouri Working Paper, November 2018

Abstract:

This paper proposes a new market-level investor sentiment index (Photo Sentiment) constructed from photos in the financial press. We apply a machine learning technique to classify a large sample of photos in The Economist based on perceived sentiment. Photo Sentiment is measured as the average probability the photos have negative sentiment minus the average probability the photos have positive sentiment. Between 1997 and 2017, Photo Sentiment is found to predict short-term return reversal, trading volume and market volatility, and explains flows between equity and money market funds. A trading strategy based on Photo Sentiment outperforms the market index by 2.6% on an annual basis while assuming less risk.


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