Findings

Following the Market Science

Kevin Lewis

March 16, 2021

Bull, bear, or rat markets: Rat “stock market” task reveals human-like behavioral biases
Annamarie Huttunen, Hayley Reeve & Eric Bowman
Journal of Neuroscience, Psychology, and Economics, December 2020, Pages 204–229

Abstract:

Investors often exhibit behavioral biases (e.g., loss aversion) that are putatively underpinned by mechanisms supporting reinforcement learning in the brain, which are largely evolutionarily conserved across mammalian species. Although previous research has demonstrated that rats, similar to humans, exhibit behavioral economic biases in certain contexts, asset market contingencies have gone largely unexplored. Thus, we developed an experimental “stock market”’ task in which cohorts of 4 rats drove asset prices up and down by selecting and subsequently buying, selling, or holding “stocks” to earn sweet liquid reward. Profits and losses were operationalized as reward volumes larger than and smaller than a reference volume of reward, respectively. Following a loss, rats moved more slowly to collect the reward and spent less time licking at the reward spigot, indicative of lower motivation to approach and “savor” a loss reward. Rats also tended to respond suboptimally following a loss, which corresponded to an increase in risk-seeking behavior characterized by a bias against the optimal “hold” option in that context. Rats’ choice of the sell option demonstrated a robust tendency toward realizing gains more quickly than losses, which is characteristic of the “disposition effect” in human stock markets. Our results indicate that rats exhibit behavioral biases similar to human investors, emphasizing the suitability of the rat stock market model to future work into the behavioral neuroscience of suboptimal financial decision-making.


Replicating the Dow Jones Industrial Average
Jacky Lin et al.
NBER Working Paper, March 2021

Abstract:

The Dow Jones Industrial Average has historically been the most quoted stock index in the United States. It has several unique features. It uses price weights, it ignores cash dividend payments, and it also treats stock dividends, rights issues, and other corporate actions inconsistently. We show that price indices which use alternative weighting methods and more systematic inclusion criteria perform similarly to the Dow. However, ignoring cash and stock dividends underestimates the long-run returns earned by stock market investors dramatically. If the DJIA had consistently adjusted for dividends and other corporate actions since 1928, the index would have closed at 1,113,047 instead of 28,538 points at the end of 2019.


Face It: Quantifying the Impact of Nonverbal Communication in FOMC Press Conferences
Filippo Curti & Sophia Kazinnik
Federal Reserve Working Paper, February 2021

Abstract:

We apply facial recognition methods to FOMC press conference videos, and quantify one of the most important aspects of nonverbal communication - facial expressions. Using minute-level data, we align our nonverbal communication measure with a set of financial assets to estimate the impact of the Federal Reserve Chairs' facial expressions on investor expectations. We find that investors adversely react to negative expression revealed during the press conference, even when controlling for the verbal component of the press conference and additional explanatory variables. The effect is heightened in meetings that draw more attention and when the Chair is discussing forward guidance.


Policy Rules and Economic Performance
Alex Nikolsko-Rzhevskyy, David Papell & Ruxandra Prodan
Journal of Macroeconomics, June 2021

Abstract:

Debates about the conduct of monetary policy have evolved over time from “rules versus discretion” to “policy rules versus constrained discretion.” We propose a metric to evaluate monetary policy rules that are consistent with constrained discretion by calculating quadratic loss ratios, the (inflation plus unemployment) loss in high deviations periods divided by the loss in low deviations periods, with policy rules with higher loss ratios preferred to rules with lower loss ratios. The central results of the paper are (1) economic performance is better in periods of low deviations from policy rule prescriptions than in periods of high deviations from policy rule prescriptions for the vast majority of rules, and (2) rules with larger coefficients on the inflation gap than on the output gap are preferred to rules with larger coefficients on the output gap than on the inflation gap. These results are robust to policy lags between one and two years, different weights on inflation loss than on unemployment loss, various definitions of high and low deviations periods, fixed and time varying neutral real interest rates, fixed and time-varying inflation targets, and measuring economic slack by either the output gap or the unemployment gap. We conclude that (1) the Fed should “constrain” constrained discretion by following a rule that responds more strongly to inflation gaps than to output gaps and (2) this type of rule should be added to the Fed's semi-annual Monetary Policy Report.


Science and the Market for Technology
Ashish Arora, Sharon Belenzon & Jungkyu Suh
NBER Working Paper, March 2021

Abstract:

Well-functioning Markets for Technology (MFT) allow inventors to sell their inventions to others that may derive more value from them. We argue that the growing reliance on science in inventions enhances MFT. In addition to higher quality inventions, reliance on science may enhance gains from trade and reduce the transfer cost of knowledge and other transaction costs. Using large scale data, we show that patents citing science are more likely to be traded, especially for novel patents and for smaller inventors. Leveraging the fall of the Berlin Wall as a source of exogenous variation in the relevant scientific knowledge to technological fields, we confirm reliance on science increases the likelihood that the invention will be traded.


Algorithmic Trading and Firm Value
Brian Hatch et al.
Journal of Banking & Finance, April 2021

Abstract:

Using data from 2002 to 2013, we show that algorithmic trading has a positive impact on firm value. Most of this positive impact flows through the channels of stock liquidity, idiosyncratic volatility, and idiosyncratic skewness, but algorithmic trading also has a large economic effect outside those channels. We use the advent of auto quotation on the New York Stock Exchange as an exogenous shock to algorithmic trading to rule out reverse causality. The positive effects of algorithmic trading on firm value are stronger for larger firms and in the post-2007 period when algorithmic trading intensity is higher.


Is Beauty Skin Deep?
Gajanan Ganji, Arati Kale & Devendra Kale
University of Chicago Working Paper, June 2020

Abstract:

In this paper, we investigate if the perceived attractiveness of mutual fund managers influences mutual fund flows. We hand collect professional photographs of mutual fund managers and use machine learning algorithms to develop two objective proxies of attractiveness. We find that, even after controlling for fund characteristics, performance measures and manager characteristics, mutual funds managed by ‘attractive’ managers receive higher fund flows. Our results are robust to matched sample analysis, Heckman two-stage selection, alternate model specifications as well as use of an alternate proxy. We also find that the attractiveness bias is predominantly witnessed within retail investors. We further find that manager attractiveness does not entail superior fund performance. Our results thereby suggest that mutual fund investors exhibit a bias for seemingly attractive mutual fund managers.


Face Value: Trait Inference, Performance Characteristics, and Market Outcomes for Financial Analysts
Lin Peng et al.
City University of New York Working Paper, December 2020

Abstract:

Using machine learning-based algorithms, we extract key impressions about personality traits from the LinkedIn profile photos of sell-side analysts. We find that these face-based factors are associated with analyst behavior, performance, and capital- and labor-market outcomes. The trustworthiness (TRUST) and dominance (DOM) factors are positively associated with analyst forecast accuracy and report length. Analysts with high TRUST scores tend to herd with managerial guidance forecasts; those with high DOM scores actively participate in conference calls. The positive association of the attractiveness (ATTRACT) factor on forecast accuracy diminishes with market learning and after Reg-FD. Forecasts from analysts with higher TRUST and DOM scores generate stronger price reactions. High DOM scores help male analysts but hurt female analysts to attain All-Star status. These findings suggest that impressions formed from observing analysts’ physical facial attributes are associated with analysts’ economic behaviors. Some of the investor and peer responses to these impressions seem to reflect societal biases and gender stereotypes.


When a Master Dies: Speculation and Asset Float
Julien Pénasse, Luc Renneboog & José Scheinkman
Review of Financial Studies, forthcoming

Abstract:

An artist’s death constitutes a negative shock to his future production; death permanently decreases the artist’s float. We use this shock to test predictions of speculative trading models with short-selling constraints. As predicted in our model, we find that an artist’s premature death leads to a permanent increase in prices and turnover; this effect being larger for more famous artists. We document that premature death increases prices (by 54.7%) and secondary market volume (by 63.2%).


Gauging the effects of stock liquidity on earnings management: Evidence from the SEC tick size pilot test
Dan Li & Ying Xia
Journal of Corporate Finance, April 2021

Abstract:

This paper studies whether stock market liquidity has a causal effect on real earnings management. We introduce a new and cleaner identification of liquidity shock - the 2016 Tick Size Pilot Program - to show that firms with less liquid stocks are more likely to engage in real earnings management. We provide direct evidence that stock liquidity helps to deter real earnings management via enhancing governance by long-term institutional investors through trading and direct intervention, and via facilitating short selling to discipline managers. The effect is stronger in firms that do not pay dividends.


Information shocks, disagreement, and drift
Will Armstrong, Laura Cardella & Nasim Sabah
Journal of Financial Economics, forthcoming

Abstract:

We examine the effects of investor disagreement on price discovery using a recurring public information event in the highly liquid crude oil futures market, a market free of short sale constraints. We show that prices reflect positive news within one-half second of trading but continue to drift for five minutes when news is negative. Evidence suggests the drift arises from a systematic surge in buying pressure that impedes the price discovery process when news is negative. Our results are consistent with price drift arising from differences in trading horizons, where traders taking long positions condition trades on information beyond the news.


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