The Effect of Trading Volume on Analysts’ Forecast Bias

2011 ◽  
Vol 86 (2) ◽  
pp. 451-481 ◽  
Author(s):  
Anne Beyer ◽  
Ilan Guttman
Keyword(s):  
Private Information ◽  
Trading Volume ◽  
Forecast Error ◽  
Bad News ◽  
Earnings Forecast ◽  
Risk Averse ◽  
Forecast Bias ◽  
Optimal Trading ◽  
Trading Decisions ◽  
Separating Equilibrium

ABSTRACT: This study models the interaction between a sell-side analyst and risk-averse investors. It derives an analyst’s optimal earnings forecast and investors’ optimal trading decisions in a setting where the analyst’s payoff depends on the trading volume the forecast generates as well as on the forecast error. In the fully separating equilibrium, we find that the analyst biases the forecast upward (downward) if his private signal reveals relatively good (bad) news. The model predicts that: (1) the analyst biases the forecast upward more often than downward and the forecast is on average optimistic; (2) the magnitude of the analyst’s bias is increasing in the per-share benefit from trading volume he receives; and (3) the analyst’s expected squared forecast error may increase in the precision of his private information. Finally, we characterize the circumstances under which the (rational) analyst acts as if he overweights or underweights his private information.

scholarly journals Earnings Predictability And Broker-Analysts’ Earnings Forecast Bias

2017 ◽  
Vol 33 (6) ◽  
pp. 1285-1302
Author(s):  
Michael Eames ◽  
Steven Glover
Keyword(s):  
Private Information ◽  
Alternative Model ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Earnings Expectations ◽  
Forecast Bias ◽  
Analyst Expectations ◽  
Earnings Predictability ◽  
Using Data ◽  
Short Horizon

Scholars have reasoned that analysts issue optimistic forecasts to improve their access to managers’ private information when earnings are unpredictable. While this requires a managerial preference for analyst forecast optimism, the observed walk-down of analyst expectations to beatable forecasts is consistent with a managerial preference for pessimism in short-horizon forecasts. Using data from various sample periods, alternative model specifications, and various measures of earnings unpredictability, we find that pessimism, not optimism, in short-horizon forecasts is associated with increasingly unpredictable earnings. Our results suggest that firms can more effectively manage analysts’ earnings expectations downward when earnings are relatively unpredictable.

Earnings Predictability and the Direction of Analysts' Earnings Forecast Errors

2003 ◽  
Vol 78 (3) ◽  
pp. 707-724 ◽  
Author(s):  
Michael J. Eames ◽  
Steven M. Glover
Keyword(s):  
Private Information ◽  
Forecast Error ◽  
Control Variable ◽  
Earnings Forecasts ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Effective Mechanism ◽  
Earnings Predictability

Das et al. (1998) suggest that as earnings become less predictable, analysts issue increasingly optimistic forecasts to please managers and consequently gain, or at least limit the loss of, access to managers' private information. We reexamine the association between earnings forecast error and earnings predictability because there is evidence suggesting that deliberate earnings forecast optimism is not an effective mechanism for gaining access to managers' information (e.g., Eames et al. 2002; Matsumoto 2002). We document associations between earnings level and both forecast error and earnings predictability. These associations suggest that earnings level may be an important control variable when examining the association between forecast error and earnings predictability. When we control for the level of earnings we find no significant association between forecast error and earnings predictability. Thus, we find no evidence that analysts intentionally issue optimistically biased earnings forecasts.

Do Managers Disclose or Withhold Bad News? Evidence from Short Interest

2018 ◽  
Vol 94 (3) ◽  
pp. 1-26 ◽  
Author(s):  
Dichu Bao ◽  
Yongtae Kim ◽  
G. Mujtaba Mian ◽  
Lixin (Nancy) Su
Keyword(s):  
Private Information ◽  
Voluntary Disclosure ◽  
Stock Price ◽  
Data Availability ◽  
Bad News ◽  
General Tendency ◽  
Litigation Risk ◽  
Novel Approach ◽  
Conflicting Evidence ◽  
Short Interest

ABSTRACT Prior studies provide conflicting evidence as to whether managers have a general tendency to disclose or withhold bad news. A key challenge for this literature is that researchers cannot observe the negative private information that managers possess. We tackle this challenge by constructing a proxy for managers' private bad news (residual short interest) and then perform a series of tests to validate this proxy. Using management earnings guidance and 8-K filings as measures of voluntary disclosure, we find a negative relation between bad-news disclosure and residual short interest, suggesting that managers withhold bad news in general. This tendency is tempered when firms are exposed to higher litigation risk, and it is strengthened when managers have greater incentives to support the stock price. Based on a novel approach to identifying the presence of bad news, our study adds to the debate on whether managers tend to withhold or release bad news. Data Availability: Data used in this study are available from public sources identified in the study.

ECONOMIC POLICY UNCERTAINTY AND THE BITCOIN MARKET: AN INVESTIGATION IN THE COVID-19 PANDEMIC WITH TRANSFER ENTROPY

2021 ◽  
pp. 1-27
Author(s):  
TOAN LUU DUC HUYNH ◽  
MEI WANG ◽  
VINH XUAN VO
Keyword(s):  
Economic Policy ◽  
Risk Premium ◽  
Trading Volume ◽  
Transfer Entropy ◽  
Policy Uncertainty ◽  
Risk Averse ◽  
Entropy Model ◽  
Economic Policy Uncertainty ◽  
Bid Ask Spread ◽  
Practical Implications

This paper investigates the prediction power of economic policy uncertainty on Bitcoin trading (return, volume, and volatility) over the period from May 2013 to June 2019. We employ the Transfer Entropy model with the following two different regimes (i) stationary and (ii) nonstationary assumption. We construct different algorithm calculations for returns, volume and volatility to test how this proxy impacts. We find that the global Economic Policy Uncertainty negatively causes Bitcoin volumes and volatilities. Therefore, under uncertain regimes, investors are risk-averse to trade, which makes the market less volatile. Our findings confirm the existence of pessimistic risk premium, the theory of deteriorating liquidity and the widen bid-ask spread, which lead to a decline in trading volume under uncertainties in the Bitcoin market. By using different reliable data sources as well as expanding timeframe until May 2020 with COVID-19 pandemic, our results remain robust. Hence, the practical implications will be the useful tools for different parties in the Bitcoin market in the financial turbulence context.

Institutional Dual-Holders and Managers' Earnings Disclosure

2021 ◽  
Author(s):  
Leila Peyravan ◽  
Regina Wittenberg-Moerman
Keyword(s):  
Adverse Effect ◽  
Commercial Bank ◽  
Private Information ◽  
Voluntary Disclosure ◽  
Information Environment ◽  
Earnings Forecast ◽  
Excess Returns ◽  
Lending Relationships ◽  
Playing Field ◽  
Information Advantage

We investigate how institutional (non-commercial bank) investors that simultaneously invest in a firm's debt and equity (dual-holders) influence the firm's voluntary disclosure. Because institutional dual-holders trade on private information gleaned through lending relationships, we predict and find that borrowers increase earnings forecast disclosure to reduce these investors' information advantage following the origination of loans with their participation. We also show that the increase in disclosure is stronger when the access to a borrower's private information endows dual-holders with a greater information advantage and when the consequences of this access are likely to be more pronounced. We further find that institutional dual-holders earn excess returns when trading equity of non-guider firms following loan origination, but not when firms issue guidance, confirming that earnings disclosure helps level the playing field among investors. Our findings highlight that firms actively use disclosure to mitigate the adverse effect of dual-holders on their information environment.

scholarly journals Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage

2015 ◽  
Vol 105 (12) ◽  
pp. 3766-3797 ◽  
Author(s):  
Alex Edmans ◽  
Itay Goldstein ◽  
Wei Jiang
Keyword(s):  
Private Information ◽  
Firm Value ◽  
Bad News ◽  
Good News ◽  
Asymmetric Effect ◽  
Trading Behavior ◽  
Feedback Effects ◽  
Limits To Arbitrage ◽  
Corporate Decisions ◽  
Fundamental Value

We analyze strategic speculators’ incentives to trade on information in a model where firm value is endogenous to trading, due to feedback from the financial market to corporate decisions. Trading reveals private information to managers and improves their real decisions, enhancing fundamental value. This feedback effect has an asymmetric effect on trading behavior: it increases (reduces) the profitability of buying (selling) on good (bad) news. This gives rise to an endogenous limit to arbitrage, whereby investors may refrain from trading on negative information. Thus, bad news is incorporated more slowly into prices than good news, potentially leading to overinvestment. (JEL D83, G12, G14)

Investors overconfidence behaviour at Bombay Stock Exchange

2018 ◽  
Vol 14 (5) ◽  
pp. 613-632 ◽  
Author(s):  
Venkata Narasimha Chary Mushinada ◽  
Venkata Subrahmanya Sarma Veluri
Keyword(s):  
Private Information ◽  
Trading Volume ◽  
Negative Impact ◽  
Stock Exchange ◽  
Public Information ◽  
Response Analysis ◽  
Content Type ◽  
Daily Data ◽  
Level Data ◽  
Attribution Bias

PurposeThe purpose of the paper is to empirically test the overconfidence hypothesis at Bombay Stock Exchange (BSE).Design/methodology/approachThe study applies bivariate vector autoregression to perform the impulse-response analysis and EGARCH models to understand whether there is self-attribution bias and overconfidence behavior among the investors.FindingsThe study shows the empirical evidence in support of overconfidence hypothesis. The results show that the overconfident investors overreact to private information and underreact to the public information. Based on EGARCH specifications, it is observed that self-attribution bias, conditioned by right forecasts, increases investors’ overconfidence and the trading volume. Finally, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.Research limitations/implicationsThe study focused on self-attribution and overconfidence biases using monthly data. Further studies can be encouraged to test the proposed hypotheses on daily data and also other behavioral biases.Practical implicationsInsights from the study suggest that the investors should perform a post-analysis of each investment so that they become aware of past behavioral mistakes and stop continuing the same. This might help investors to minimize the negative impact of self-attribution and overconfidence on their expected utility.Originality/valueTo the best of the authors’ knowledge, this is the first study to examine the investors’ overconfidence behavior at market-level data in BSE, India.

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