Publications

Forecasting Earnings Using k-Nearest Neighbors

Published in The Accounting Review, 2024

Abstract:

We use a simple k-nearest neighbors algorithm (hereafter, k-NN) to forecast earnings. k-NN forecasts of one-, two-, and three-year-ahead earnings are more accurate than those generated by popular extant forecasting approaches. k-NN* forecasts of two- and three-year (one-year)-ahead EPS and aggregate three-year EPS are more (less) accurate than those generated by analysts. The association between the unexpected earnings implied by k-NN* and the contemporaneous market-adjusted return (i.e., the earnings association coefficient (EAC)) is positive and exceeds the EAC on unexpected earnings implied by alternate approaches. A trading strategy that is long (short) firms for which k-NN* predicts positive (negative) earnings growth earns positive risk-adjusted returns that exceed those earned by similar trading strategies that are based on alternate forecasts. The k-NN* algorithm generates an empirically reliable ex ante indicator of forecast accuracy that identifies situations when the k-NN* EAC is larger and the k-NN* trading strategy is more profitable.

Recommended citation:

Peter D. Easton, Martin M. Kapons, Steven J. Monahan, Harm H. Schütt, Eric H. Weisbrod; Forecasting Earnings Using k-Nearest Neighbors. The Accounting Review 1 May 2024; 99 (3): 115–140. https://doi.org/10.2308/TAR-2021-0478

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The Roles of Data Providers and Analysts in the Production, Dissemination, and Pricing of Street Earnings

Published in Journal of Accounting Research, 2022

Abstract:

In September 2009, Thomson Reuters (TR) discontinued its practice of relying on analysts to determine the treatment of unexpected charges and gains in favor of their immediate exclusion from GAAP earnings. Adopting a difference-in-differences approach, we show that this plausibly exogenous change in TR’s methodology resulted in street earnings that are more predictive of future performance; and timelier, more accurate, and less dispersed analyst forecasts of future earnings, consistent with TR enhancing the properties of street earnings and analyst forecasts. Finally, using path analysis we show that a significant portion of TR’s effect on price discovery is through its effect on analysts; and that the change in TR’s treatment of unexpected items increased (decreased) the relative influence of TR (analysts) on the pricing of street earnings. We conclude that forecast data providers like TR are more than a conduit of information from analysts to investors.

Recommended citation:

BOCHKAY, K., MARKOV, S., SUBASI, M. and WEISBROD, E. (2022), The Roles of Data Providers and Analysts in the Production, Dissemination, and Pricing of Street Earnings. Journal of Accounting Research, 60: 1695-1740. https://doi.org/10.1111/1475-679X.12457

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Stockholders’ Unrealized Returns and the Market Reaction to Financial Disclosures

Published in Journal of Finance, 2019

Abstract:

Using both investor- and stock-level data, I examine the relation between stockholders’ unrealized returns since purchase and the market response to earnings announcements. I demonstrate that stockholders’ unrealized gain/loss position moderates their trading behavior in response to earnings announcements. I also find that this behavior generates a short-window return underreaction to earnings news. My results are generally consistent with predictions from prospect theory regarding the manner in which stockholders’ unrealized returns moderate their trading response to belief shocks. However, my results also suggest that an emotional component (i.e., regret-avoidance/pride-seeking) is necessary to explain the observed investor behavior.

Recommended citation:

WEISBROD, E. (2019), Stockholders’ Unrealized Returns and the Market Reaction to Financial Disclosures. The Journal of Finance, 74: 899-942. https://doi.org/10.1111/jofi.12743

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Joint Audit Engagements and Client Tax Avoidance: Evidence from the Italian Statutory Audit Regime

Published in Journal of the American Taxation Association, 2019

Abstract: Under the Italian statutory audit regime, three individual accountants are jointly appointed to audit each client’s annual financial statements and sign off on the tax return. These individuals can belong to the same or different accounting firms and through multiple and repeated collaborations they form a professional network. We use network measures of centrality to capture individuals’ ability to acquire and apply tax expertise across clients. We demonstrate that clients engaging better-connected individual auditors have comparatively lower effective tax rates. Our results are robust to controlling for a number of client, individual, and accounting firm characteristics, as well as for alternative network connections between clients. We also use instrumental variables, individual fixed effects, and matching to mitigate the effect of endogenous pairing of clients and auditors. Our findings demonstrate that in a joint audit environment, individual auditor professional networks have consequences for tax outcomes.

Recommended citation:

Pietro A. Bianchi, Diana Falsetta, Miguel Minutti-Meza, Eric Weisbrod; Joint Audit Engagements and Client Tax Avoidance: Evidence from the Italian Statutory Audit Regime. Journal of the American Taxation Association 1 March 2019; 41 (1): 31–58. https://doi.org/10.2308/atax-52151

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Determinants and Consequences of Information Processing Delay: Evidence from Thomson Reuters’ Institutional Brokers’ Estimate System

Published in Journal of Financial Economics, 2018

Abstract: We present new evidence that highlights the role of information intermediaries in the distribution and processing of earnings estimates in capital markets. We find that the time taken to activate an analyst’s earnings forecast in the Thomson Reuters Institutional Brokers’ Estimate System is related to measures of investor demand for timely information processing, processing difficulty, and limited attention. Furthermore, we find that forecast announcement returns are muted and post-announcement drift is magnified for forecasts with longer unexpected activation delay and that market inefficiency is concentrated in neglected stocks and potentially exploitable. Finally, analyzing intraday returns, we find that activations facilitate price discovery.

Recommended citation:

Akbas, F., S. Markov, M. Subasi, and E. Weisbrod, 2018. Determinants and Consequences of Information Processing Delay: Evidence from Thomson Reuters’ Institutional Brokers’ Estimate System. Journal of Financial Economics, 127: 366-388. https://doi.org/10.1016/j.jfineco.2017.11.005

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The Information Content of Tax Expense for Firms Reporting Losses

Published in Journal of Accounting Research, 2013

Abstract: We investigate whether management’s decision regarding the recognition of the valuation allowance (VA) for deferred tax assets provides incremental information about the persistence of accounting losses. We introduce a classification scheme that assigns loss firm-years into three categories based on whether management appears to have recognized a material change in the VA, and whether or not the firm has positive taxable income (e.g., a net operating loss). The results of our study show that our tax categories contain information about the persistence of accounting losses over the following three years beyond variables previously identified to predict loss persistence. This incremental information is consistent with management using private information about the firm’s future prospects in setting the VA. Finally, we find that investors’ pricing of the VA varies with the saliency of the tax signal and the information environment of the firm.

Recommended citation: DHALIWAL, D.S., KAPLAN, S.E., LAUX, R.C. and WEISBROD, E. (2013), The Information Content of Tax Expense for Firms Reporting Losses. Journal of Accounting Research, 51: 135-164. https://doi.org/10.1111/j.1475-679X.2012.00466.x

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The role of affect and tolerance of ambiguity in ethical decision making

Published in Advances in Accounting, 2009

Abstract:

This research note extends the research on ethical decision making in accounting by examining the effect of two variables, affect and tolerance of ambiguity, on ethics-related decisions made in two contexts: both personal and organizational settings. I conduct an experimental study among undergraduate accounting students and find that tolerance of ambiguity significantly influences ethical decisions in both personal and organizational settings. The results also reveal a significant interactive effect between negative affect and tolerance of ambiguity.

Recommended citation:

Weisbrod, E., 2009. The role of affect and tolerance of ambiguity in ethical decision making. Advances in Accounting, 25(1), pp.57-63.

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