Allen Huang
Associate Professor, Department of Accounting, HKUST
Email: allen.huang@ust.hk
Selected Working Papers
"Federal Judge Ideology: A New Measure of Ex-Ante Litigation Risk" (with Kai Wai Hui and Reeyarn Li).
Drawing on the political theory of judicial decision-making, our paper proposes a parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics, and is economically meaningful in predicting litigation occurrence. Firms in more liberal circuits are more likely to be sued in securities class action lawsuits, an effect that is economically significant. This result is stronger after the U.S. Supreme Court’s ruling in the Tellabs case. We also find that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and those with higher expected litigation costs. We further validate the measure by examining judicial appointments. Finally, using the new measure, we document that litigation risk deters managers from providing long-term earnings guidance, a result that existing measures of litigation risk cannot show.
Federal Judge Ideology Data.
Based on our calculation, between 2006 and 2014, judge retirements and President Obama's appointment of six judges to the Fourth Circuit increased the securities class action lawsuit likelihood of firms located in the circuit by 50.9% (2.69% to 4.06%).
Drawing on the political theory of judicial decision-making, our paper proposes a parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics, and is economically meaningful in predicting litigation occurrence. Firms in more liberal circuits are more likely to be sued in securities class action lawsuits, an effect that is economically significant. This result is stronger after the U.S. Supreme Court’s ruling in the Tellabs case. We also find that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and those with higher expected litigation costs. We further validate the measure by examining judicial appointments. Finally, using the new measure, we document that litigation risk deters managers from providing long-term earnings guidance, a result that existing measures of litigation risk cannot show.
Federal Judge Ideology Data.
Based on our calculation, between 2006 and 2014, judge retirements and President Obama's appointment of six judges to the Fourth Circuit increased the securities class action lawsuit likelihood of firms located in the circuit by 50.9% (2.69% to 4.06%).
"An Unintended Benefit of the Risk Factor Mandate of 2005" (with Jianghua Shen and Amy Zang).
The risk factor disclosure mandate effective in 2005 was intended to provide the market with useful information on firm risk. However, because risk factors qualify as “meaningful cautionary language” under the safe harbor provision of the Private Securities Litigation Reform Act, the mandate resulted in an exogenous increase in legal protection for forward-looking statements by firms that started to disclose risk factors due to the mandate. Using a difference-in-differences design, we find that these firms became more willing to provide forward-looking statements, particularly positive ones, and management forecasts, and their management forecasts are more positive, have higher precision and longer horizons, compared to firms that had voluntarily disclosed risk factors prior to the mandate. Cross-sectional tests show that this effect is stronger for firms whose forward-looking statements are more susceptible to potential litigation. Last, we find that the increased willingness to provide forward-looking information has improved these firms’ information environment. Our study suggests that the 2005 risk factor mandate has an unintended benefit—it has spurred firms’ voluntary disclosure of forward-looking information.
The risk factor disclosure mandate effective in 2005 was intended to provide the market with useful information on firm risk. However, because risk factors qualify as “meaningful cautionary language” under the safe harbor provision of the Private Securities Litigation Reform Act, the mandate resulted in an exogenous increase in legal protection for forward-looking statements by firms that started to disclose risk factors due to the mandate. Using a difference-in-differences design, we find that these firms became more willing to provide forward-looking statements, particularly positive ones, and management forecasts, and their management forecasts are more positive, have higher precision and longer horizons, compared to firms that had voluntarily disclosed risk factors prior to the mandate. Cross-sectional tests show that this effect is stronger for firms whose forward-looking statements are more susceptible to potential litigation. Last, we find that the increased willingness to provide forward-looking information has improved these firms’ information environment. Our study suggests that the 2005 risk factor mandate has an unintended benefit—it has spurred firms’ voluntary disclosure of forward-looking information.
"The Long-Term Consequences of Short-Term Incentives" (with Alex Edmans and Vivian Fang).
This paper shows that short-term stock price concerns induce CEOs to take value-reducing actions. Vesting equity, our measure of short-term concerns, is positively associated with the probability of a firm repurchasing shares, the amount of shares repurchased, and the probability of the firm announcing a merger or acquisition (M&A). When vesting equity increases, stock returns are more positive in the two quarters surrounding both repurchases and M&A, but more negative in the two years following repurchases and four years following M&A. A potential driver of the negative longrun returns to M&A is subsequent goodwill impairment. These results are inconsistent with CEOs buying underpriced stock or companies to maximize long-run shareholder value, but consistent with these actions being used to boost the short-term stock price and improve the conditions for CEO equity sales. CEOs sell their own stock shortly after using company money to buy the firm’s stock, also inconsistent with the latter being motivated by undervaluation.
This paper shows that short-term stock price concerns induce CEOs to take value-reducing actions. Vesting equity, our measure of short-term concerns, is positively associated with the probability of a firm repurchasing shares, the amount of shares repurchased, and the probability of the firm announcing a merger or acquisition (M&A). When vesting equity increases, stock returns are more positive in the two quarters surrounding both repurchases and M&A, but more negative in the two years following repurchases and four years following M&A. A potential driver of the negative longrun returns to M&A is subsequent goodwill impairment. These results are inconsistent with CEOs buying underpriced stock or companies to maximize long-run shareholder value, but consistent with these actions being used to boost the short-term stock price and improve the conditions for CEO equity sales. CEOs sell their own stock shortly after using company money to buy the firm’s stock, also inconsistent with the latter being motivated by undervaluation.
Publications
"Analyst Information Discovery and Interpretation Roles: A Topic Modeling Approach" (with Reuven Lehavy, Amy Zang, and Rong Zheng), Management Science, June 2018, Vol. 64, Iss. 6, pp. 2833-2855.
This study examines analyst information intermediary roles using a textual analysis of analyst reports and corporate disclosures. We employ a topic modeling methodology from computational linguistic research to compare the thematic content of a large sample of analyst reports issued promptly after earnings conference calls with the content of the calls themselves. We show that analysts discuss exclusive topics beyond those from conference calls and interpret topics from conference calls. In addition, we find that investors place a greater value on new information in analyst reports when managers face greater incentives to withhold value-relevant information. Analyst interpretation is particularly valuable when the processing costs of conference call information increase. Finally, we document that investors react to analyst report content that simply repeats managers’ discussion. Overall, our study shows that analysts play the information intermediary roles by discovering information beyond corporate disclosures and by clarifying and confirming corporate disclosures.
Internet Appendix to Huang, Lehavy, Zang and Zheng (2016).
Java package to implement Topic Modeling (LDA) algorithm used in the paper.
Another Java based package (MALLET).
Python package to implement LDA.
This study examines analyst information intermediary roles using a textual analysis of analyst reports and corporate disclosures. We employ a topic modeling methodology from computational linguistic research to compare the thematic content of a large sample of analyst reports issued promptly after earnings conference calls with the content of the calls themselves. We show that analysts discuss exclusive topics beyond those from conference calls and interpret topics from conference calls. In addition, we find that investors place a greater value on new information in analyst reports when managers face greater incentives to withhold value-relevant information. Analyst interpretation is particularly valuable when the processing costs of conference call information increase. Finally, we document that investors react to analyst report content that simply repeats managers’ discussion. Overall, our study shows that analysts play the information intermediary roles by discovering information beyond corporate disclosures and by clarifying and confirming corporate disclosures.
Internet Appendix to Huang, Lehavy, Zang and Zheng (2016).
Java package to implement Topic Modeling (LDA) algorithm used in the paper.
Another Java based package (MALLET).
Python package to implement LDA.
"Imperfect Accounting and Reporting Bias?" (with Vivian Fang and Wenyu Wang), Journal of Accounting Research, September 2017, Vol. 55, Iss. 4, pp. 919-962.
Errors and bias are both inherent features of accounting. In theory, while errors discourage bias by lowering the value relevance of accounting, they can also facilitate bias by providing camouflage. Consistent with theory, we find a hump-shaped relation between a firm’s propensity to engage in intentional misstatement and the prevalence of unintentional misstatements in the firm’s industry for the whole economy and a majority of the industries. The result is robust to using firms’ number of items in financial statements and exposure to complex accounting rules as alternative proxies for errors and to using the restatement amount in net income to quantify the magnitude of bias and errors. To directly test for the two effects of errors, we show that, when errors are more prevalent, the market reacts less to firms’ earnings surprises and bias is more difficult to detect. Our results highlight the imperfectness of accounting, advance understanding of firms’ reporting incentives, and shed light on accounting standard setting.
Errors and bias are both inherent features of accounting. In theory, while errors discourage bias by lowering the value relevance of accounting, they can also facilitate bias by providing camouflage. Consistent with theory, we find a hump-shaped relation between a firm’s propensity to engage in intentional misstatement and the prevalence of unintentional misstatements in the firm’s industry for the whole economy and a majority of the industries. The result is robust to using firms’ number of items in financial statements and exposure to complex accounting rules as alternative proxies for errors and to using the restatement amount in net income to quantify the magnitude of bias and errors. To directly test for the two effects of errors, we show that, when errors are more prevalent, the market reacts less to firms’ earnings surprises and bias is more difficult to detect. Our results highlight the imperfectness of accounting, advance understanding of firms’ reporting incentives, and shed light on accounting standard setting.
"Short Selling and Earnings Management: A Controlled Experiment" (with Vivian Fang and Jonathan Karpoff), Journal of Finance, June 2016, Vol. 71, Iss. 3, pp. 1251-1294.
During 2005 to 2007, the SEC ordered a pilot program in which one-third of the Russell 3000 index were arbitrarily chosen as pilot stocks and exempted from short-sale price tests. Pilot firms’ discretionary accruals and likelihood of marginally beating earnings targets decrease during this period, and revert to pre-experiment levels when the program ends. After the program starts, pilot firms are more likely to be caught for fraud initiated before the program, and their stock returns better incorporate earnings information. These results indicate that short selling, or its prospect, curbs earnings management, helps detect fraud, and improves price efficiency.
List of pilot stocks published SEC's release No. 50104.
During 2005 to 2007, the SEC ordered a pilot program in which one-third of the Russell 3000 index were arbitrarily chosen as pilot stocks and exempted from short-sale price tests. Pilot firms’ discretionary accruals and likelihood of marginally beating earnings targets decrease during this period, and revert to pre-experiment levels when the program ends. After the program starts, pilot firms are more likely to be caught for fraud initiated before the program, and their stock returns better incorporate earnings information. These results indicate that short selling, or its prospect, curbs earnings management, helps detect fraud, and improves price efficiency.
List of pilot stocks published SEC's release No. 50104.
"Evidence on the Information Content of Text in Analyst Reports" (with Amy Zang and Rong Zheng), The Accounting Review, November 2014, Vol. 89, No. 6, pp. 2151-2180.
We document that textual discussions in a sample of 363,952 analyst reports provide information to investors beyond that in the contemporaneously released earnings forecasts, stock recommendations, and target prices, and also assist investors in interpreting these signals. Cross-sectionally, we find that investors react more strongly to negative than to positive text, suggesting that analysts are especially important in propagating bad news. Additional evidence indicates that analyst report text is more useful when it places more emphasis on nonfinancial topics, is written more assertively and concisely, and when the perceived validity of other information signals in the same report is low. Finally, analyst report text is shown to have predictive value for future earnings growth in the subsequent five years.
Data mining software to implement the naive Bayes algorithm.
We document that textual discussions in a sample of 363,952 analyst reports provide information to investors beyond that in the contemporaneously released earnings forecasts, stock recommendations, and target prices, and also assist investors in interpreting these signals. Cross-sectionally, we find that investors react more strongly to negative than to positive text, suggesting that analysts are especially important in propagating bad news. Additional evidence indicates that analyst report text is more useful when it places more emphasis on nonfinancial topics, is written more assertively and concisely, and when the perceived validity of other information signals in the same report is low. Finally, analyst report text is shown to have predictive value for future earnings growth in the subsequent five years.
Data mining software to implement the naive Bayes algorithm.
"CEO Reputation and Earnings Quality" (with Jennifer Francis, Shivaram Rajgopal and Amy Zang), Contemporary Accounting Research, Spring 2008, Vol. 25, Iss. 1, pp. 109-147.
We examine the relation between CEO reputation and measures of the firm’s earnings quality. Using press coverage (media counts) to proxy for CEO reputation, we find that more reputed CEOs are associated with poorer earnings quality. This finding is inconsistent with an efficient contracting view, which predicts that reputed CEOs take actions that result in good earnings quality. This seemingly counterintuitive result is, however, consistent with two other theories: a rent extraction hypothesis (which predicts that reputed managers are more likely to use their discretion to manipulate earnings in order to manage labor and stock market perceptions) and a matching hypothesis (which predicts that selection on the part of firms gives rise to a demand for reputed CEOs for firms where earnings quality is inherently poor). Further analyses provide little support for the rent extraction explanation and some support for the matching explanation.
We examine the relation between CEO reputation and measures of the firm’s earnings quality. Using press coverage (media counts) to proxy for CEO reputation, we find that more reputed CEOs are associated with poorer earnings quality. This finding is inconsistent with an efficient contracting view, which predicts that reputed CEOs take actions that result in good earnings quality. This seemingly counterintuitive result is, however, consistent with two other theories: a rent extraction hypothesis (which predicts that reputed managers are more likely to use their discretion to manipulate earnings in order to manage labor and stock market perceptions) and a matching hypothesis (which predicts that selection on the part of firms gives rise to a demand for reputed CEOs for firms where earnings quality is inherently poor). Further analyses provide little support for the rent extraction explanation and some support for the matching explanation.
