Market-based Accounting Research Research Papers

The Impact of Earnings Surprise on Differential Belief Revisions: The Relative Role of the Cash Flow and Accrual components1

by Neal Mc Arthur

2025, accg.mq.edu.au

We examine the market-relevance of disaggregating earnings into cash flow and accrual components. Unlike the majority of capital markets accounting research to-date, which has restricted analysis to price effects (returns), we focus on... more

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Can we predict the likelihood of financial distress in companies from their corporate governance and borrowing?

by Sara Mariano

2025, International Journal of Accounting & Information Management

PurposeThe purpose of this study is to investigate the impact of corporate governance structures on the likelihood of financial distress in UK listed companies. The paper examines the impact of borrowing and corporate governance... more

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Collaborative Decision-making and Outcomes in a Competitive, Simulated, Industry Environment

by Megan Anderson

2024

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Does value creation drive growth illusion? An evidence from Indonesia stock exchange

by Agus Satrya Wibowo

2024

The main aim of this study is to explore the illusion effect on the growth market of firm value, and to examine the value creation of manufacturing companies listed in the Indonesia Stock Exchange (IDX). The study used pooled data of the... more

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Efek Entrenchment Dan Alignment Pada Manajemen Laba

by Putu Sugiartha Sanjaya

2024

The objective of this research is to investigate whether controlling shareholder manages earnings. The issue is most important to be revealed because ownership of public companies is concentrated and low protections for noncontrolling... more

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Essays on sell-side analyst industry

by Elisa Cavezzali

2024

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A new perspective on post‐earnings‐announcement‐drift: Using a relative drift measure

by Kevin Ow Yong

2024, Journal of Business Finance & Accounting

Prior research finds that there is a delayed reaction to both analyst‐based earnings surprises and random‐walk‐based earnings surprises. Focusing on the market reaction from the post‐announcement window, prior studies show that... more

abnormal return that decreases by 0.03% for each successive quarter. The corresponding strategy for the SUE_AF

Notes: This table reports the summary statistics for the variables used in this study. It includes all firm-quarters with data to calculate SUE_LRW, SUE_AF, and returns during the period Q1/1984 to Q4/2010. See the Appendix for definitions of the variables. TABLE1 Summary statistics

Notes: This table reports the results of regressing three different CARs (i.e., CAR(Total), CAR(Earnings Announcement Window (EAW)), and CAR(Drift)) on DSUELRW and DSUE_AF. DSUE_RW and DSUE_AF are an adjusted decile rank measure which have values between -0.5 and 0.5. Figures in parentheses denote t-statistics. °,”’, “” indicate significance at the 0.10, 0.05, and 0.01 levels, respectively. Mean (Median) drift ratio is the mean (median) quarterly drift ratios over the sample period. t-statistics (Wilcoxon signed-rank statistics) is used for the test of mean (median) difference. See the Appendix for the definitions of variables. TABLE2 Associations between earnings surprises and the market response: Regressions of cumulative abnormal returns (CAR) on DSUE_RW and DSUE_AF

Notes: This table reports the coefficients in the regressions of three different CARs (i.e., CAR(Total), CAR(Earnings Announcement Window (EAW)), and CAR(Drift)) on DSUE_RW and DSUE_AF across three sample periods. Drift ratio is calculated by the slope coefficient in the regression of CAR(Drift) on the DSUE_RW (DSUE_AF) earnings surprise decile rank divided by the slope coeffi- cient in the regression of CAR(Total) on the DSUE_RW (DSUE_AF) earnings surprise decile rank. Mean (Median) drift ratio is the mean (median) quarterly drift ratios over the sample period. t-statistics (Wilcoxon signed-rank statistics) is used for the test of mean (median) difference. See the Appendix for definitions of the variables. TABLE3_ Drift ratios over time: Comparison between RW drift ratio and AF drift ratio average drift ratios across quarters in three different sample periods.? The results in the last two columns show that here is no significant difference between the drift ratios between the RW and AF models in the first sample period i.e., 1984-1992), although the AF drift ratio is lower. Thereafter, the AF drift ratio trended significantly lower than the RW drift ratio at the 1% level.

Notes: This table reports the coefficients in the regression of three different CARs (i.e., CAR(Total), CAR(Earnings Announce- ment Window (EAW)), and CAR(Drift)) on the earnings surprise and its interaction with the recency factor, i.e., DSUE_RW and DSUE_RW Recency or DSUE_AF and DSUE_AF Recency. Recency equals zero if a firm-quarter belongs to Q1/1984, and its value increases by one for each successive firm-quarter up to a maximum of 107 at the most recent quarter (i.e., Q4/2010). , ©, indicate significance at the 0.10, 0.05, and 0.01 levels, respectively. See the Appendix for definitions of the other variables. TABLE4 _ Theeffect of time horizon on the relationship between earnings surprises and the market responses

We find similar results in Panels B and C of Table 5, where we use the number of analysts following the firm and firm

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Market Uncertainty and Sentiment, and the Post-Earnings Announcement Drift

by Danny Yeung

2024, Social Science Research Network

The post-earnings announcement drift (PEAD) first identified over 40 years ago seems to be as much alive today as it ever was. Numerous attempts have been made to explain its continued existence. In this paper we provide evidence to... more

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Intra-Industry Transfer of Information Inferred From Trading Volume

by Jan Hanousek

2024, Social Science Research Network

This study examines the responsiveness of trading volume to a firm's earnings announcements We find that the volume and earnings surprise information generated at the first earnings announcement within an industry help to explain the... more

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The Reluctant Analyst

by Dan Bernhardt

2024, Journal of Accounting Research

ABSTRACTWe estimate the dynamics of recommendations by financial analysts, uncovering the determinants of inertia in their recommendations. We provide overwhelming evidence that analysts revise recommendations reluctantly, introducing... more

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The Reluctant Analyst

by Dan Bernhardt

2024, Journal of Accounting Research

ABSTRACTWe estimate the dynamics of recommendations by financial analysts, uncovering the determinants of inertia in their recommendations. We provide overwhelming evidence that analysts revise recommendations reluctantly, introducing... more

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The Market Sentiment Trend, Investor Inertia, and Post-Earnings Announcement Drift: Evidence from Korea’s Stock Market

by Heejeong Shin

2024, Sustainability

We investigated whether post-earnings announcement drift (PEAD) in the Korean stock market is related to investor inertial behavior under a directional trend in market sentiment. Given that investors tend to procrastinate due to their... more

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The Effect of Industry Homogeneity on the Magnitude of Post-Earnings Announcement Drift: Evidence from Korea

by Heejeong Shin

2024, Asian Academy of Management Journal of Accounting and Finance

We examine the relationship between industry homogeneity and the magnitude of postearnings announcement drift (hereafter, PEAD). Given that firms with more homogeneous operating cost structure are conducive to spillover of knowledge among... more

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Analysis of the Dot-Com Bubble of the 1990s

by Pervaiz Alam

2024, Social Science Research Network

During the dot-com bubble of the 1990s, equity market valuation was a popular topic for investors, financial analysts and academics. Some questioned whether traditional accounting and financial information had lost its value relevance, as... more

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Moderating Effect of Ifrs Konvergence on the Relationship Accrual Reversal with Earning Persistance and Market Response

by Siti khomsatun

2024

The study aims to analyze moderating effect of IFRS convergence on the relationship accrual reversal with earning persistence and market response. The study used 1158 unbalances panel data from non-financial company listed in Indonesian... more

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Testing the Random Walk Theory in the Nigerian Stock Market

by Abel Bala haruna

2023, IRA-International Journal of Management & Social Sciences (ISSN 2455-2267)

This study tests the random walk theory in the Nigerian stock market by analyzing whether stock returns follow a random walk distribution. The study employs the daily returns of the Top 20 most performing stocks on the NSE for the period... more

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Kandungan Informasi Inkremental Manajemen Laba Terhadap Profitabilitas Masa Depan: Studi Pada Perusahaan Publik DI Indonesia

by Windu Mulyasari

2023

This study aimed to test the moderating influence of the investment opportunity set on the relationship between earnings management and future profitability. Earnings management indicates that it has predictive information content that... more

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Analisis Perbandingan Praktik Manajemen Laba Pada Perusahaan Kategori Lapis Pertama (Blue Chip) Dan Kategori Lapis Kedua (Second Liner) Sebelum Dan Sesudah Penerapan Ifrs DI Indonesia

by taryono taryono

2023

Penelitian ini melakukan pengujian secara empiris tentang praktik manajemen laba pada perusahaan kategori lapis pertama ( blue chip ) dan perusahaan kategori lapis kedua ( second liner ) di Indonesia sebelum dan sesudah diterapkannya IFRS... more

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Empirical Analysis of the Risk-Return Characteristics of the Quoted Firms in the Nigerian Stock Market

by Ibrahim Bello

2023, Global Journal of …

This study empirically investigates the risk-return dynamics of the Nigerian quoted firms for the period of 2000-2004 as monthly. The objective of study is to establish what determines the systematic risk (beta) of firms, the magnitude of... more

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An Impact of Accounting Income Numbers on Stock Performance (An Empirical Evaluation in the Context of Indian Stock Market)

by DIPA MITRA

2023, International Journal of Accounting and Financial Management Research

It is a very general understanding that stock prices are driven by the performance of the company. Again, one of the ways to measure a company's performance is to find out the growth of earnings per share. Hence the declaration of the... more

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Return Pasar Modal Dan Pasar Rakyat?

by yusifa pascayanti

2023, Jurnal Aplikasi Akuntansi

The value relevance according to Beaver (1968) is the explanatory power of accounting information, for example accounting earnings and book value are related to firm value represented by stock prices. The phenomenon is that many players... more

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Herding in Analysts' Recommendations: The Role of Media

by Thanh Huynh

2023, SSRN Electronic Journal

This study investigates the impact of media on analysts' herding behavior when making stock recommendations. We find three main results. First, for firms with high news coverage, price reactions following analysts' recommendation... more

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Revenue surprises and stock returns

by J. Livnat

2023, Journal of Accounting and Economics

This paper examines the relation between revenue surprises, and contemporaneous and future stock returns. It also investigates whether analysts update their earnings forecasts in response to revenue surprises in a timely and unbiased... more

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Are financial analysts eager postmen of bubble psychology? Evidence in the United Kingdom

by Cormac O'Keeffe

2023, International Journal of Finance & Economics

This paper examines the investment value of financial analysts' advice (earnings forecasts and stock recommendations) to shareholders around two recent bubble periods in the United Kingdom: the dot-com bubble period and the credit bubble... more

FIGURES 1 The intensity of the (a) dot-com and (b) credit bubble periods Abbreviations: BFI, banking, finance, and insurance; TTM, technology, telecommunication, and media. Note. This table presents the matrix of U.K. analysts’ recommendation revisions in the TTM sector over the dot-com bubble period 1995 to 2002 (in panel A) and in the FBI sector over the credit bubble period 2005-2012 (in panel B). All real-time analyst recommendations are obtained from Morningstar Company Intel- ligence. A rating of 1 reflects a strong buy, 2 a buy, 3 a weak buy, 4 a weak buy/hold, 5 a hold, 6 a hold/sell, 7 a weak sell, 8 a sell, and 9 a strong sell, which are reclassified into five categories: Strong buy (1 and 2), Buy (3 and 4), Hold (5), Sell (6 and 7), and Strong sell (8 and 9). from financial analysts:

FIGURES 2 Mean earnings forecast revision (scaled by price) of stocks in five stock recommendation categories, for the technology. telecommunication, and media sector (a) before and (b) after the dot-com bubble burst in April 2000

FIGURES 3 The cumulative raw returns (CRRs) and cumulative abnormal returns (CARs) of stocks in the technolog telecommunication, and media sector across various stock recommendation categories, over a 13-month event-window (t — 6, t + 6) relative to the recommendation issue date (month 1), before and after the dot-com bubble burst in April 2000

FIGURES 4 Mean earnings forecast revision (scaled by price) of stocks in five stock recommendation categories, for the banking, finance, and insurance sector (a) before and (b) after the credit bubble burst in September 2007

FIGURES 5 The cumulative raw returns (CRRs) and cumulative abnormal returns (CARs) of stocks in the banking, finance, anc insurance sector across various stock recommendation categories, over a 13-month event-window (t — 6, t + 6) relative to the recommendation issue date (month ), before and after the credit bubble burst in September 2007

FIGURES 6 _ F-statistics for significance of structure break over (a) the dot-com bubble period 1995 to 2002 and (b) the credit bubble period 2005 to 2012

FIGURES 7 Rolling correlation (over the past year) between the average monthly return and one of the three major variables of analysts’ advice on stocks in the technology, telecommunication, and media sector over the dot-com bubble period 1995-2002 In order to examine how the predictive value of various elements in Equation (1) varies over time, we plot the rolling correlations (over the past year) between the aver- age monthly sectoral return (R,;) and each of the three major variables of analysts’ advice: (a) the lagged earnings forecast error scaled by price (ME,_;/P;,), (b) earnings fore- cast revision scaled by price (AMF,/P,), and (c) analysts’ recommendation revisions (ARating,) in the two bubble periods. We expect that returns rise (fall) when financial analysts are optimistic (pessimistic). Nevertheless, for the majority of the dot-com bubble period (whether before or after the dot-com bubble burst), the observed correlation between R; and ME,., is either negative or close to 0 (see Figure 7a), implying that analysts’ advice is not heeded by investors in the TTM sector at the aggregate level. Figure 8a illustrates that, during the credit bubble period, the relation between R, and ME,_; is once again

FIGURES 8 _ Rolling correlation (over the past year) between the average monthly return and one of the three major variables of analysts’ advice on stocks in the banking, finance, and insurance sector over the credit bubble period 2005-2012

Note. This table presents the distribution of U.K. analysts’ stock recommendations in the TTM sector over the dot-com bubble period 1995-2002 (in panel A) and in the BFI sector over the credit bubble period 2005 to 2012 (in panel B), according to the three-digit Industry Classification Benchmark (ICB) codes. All real-time analyst recommendations are obtained from Morningstar Company Intelligence. A rating of 1 reflects a strong buy, 2 a buy, 3 a weak buy, 4 a weak buy/hold, 5 a hold, 6 a hold/sell, 7 a weak sell, 8 a sell, and 9 a strong sell, which are reclassified into five categories: Strong buy (1 and 2), buy (3 and 4), hold (5), sell (6 and7), and strong sell (8 and 9). TABLE 1 Distribution of U.K. analysts’ stock recommendations in the TTM and BFI sectors

TABLE 2 Matrix of U.K. analysts’ recommendation revisions in the TTM and BFI sectors

Panel A: The TTM sector over the dot-com bubble period 1995-2002 TABLE 3 Differences in raw and adjusted monthly returns for stocks between strong buy and strong sell categories Panel B: The BFI sector over the credit bubble period 2005-2012

Note. This table presents the difference of the CRRs and the CARs of stocks between strong buy and strong sell categories, over a 13-month event window (t — 6 t + 6) relative to the recommendation month ¢. Panel A reports the results in the TTM sector before and after the dot-com bubble burst in April 2000, wherea: panel B reports the results in the BFI sector before and after the credit bubble burst in September 2007. The CAR, are adjusted by the Fama and French (1993 three-factor model: Ri, — R pe = %+B(Rmt — Rp )+SSMB,+h;HML,+¢;,, where (Ry, - Ry,), SMB, and HML, are tradable monthly factors after accounting fo transaction costs. Specifically, the net return of each tradable factor portfolio is measured as the gross return of the corresponding factor portfolio less the facto: portfolio turnover multiplied by transaction costs. The f-statistics are reported in parentheses. Abbreviations: BFI, banking, finance, and insurance; CAR, cumulative abnormal return; CRR, cumulative raw return; TTM, technology, telecommunication

TABLE 4 Regression of the monthly average stock returns on monthly averages of analysts’ advice conveyed via earnings forecasts and stock recommendations

TABLE 5_ Regressions of mean forecasting EPS on the corre- sponding actual EPS This table presents the results of regressing the mean forecasting EPS on the corresponding actual EPS either of stocks in the technology, telecommunica- tions, and media sector over the dot-com bubble period 1995-2002 or of stocks in the banking, finance, and insurance sector over the credit bubble period 2005 to 2012. We winsorize the extreme values of all variables at 0.5% and 99.5% extrema of the normal distribution of their values prior to regression estimation, to avoid any potential misleading conclusions resulted from outliers. The White heteroscedasticity-consistent t-statistics are reported in parentheses.

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Do Analysts Sacrifice Forecast Accuracy for Informativeness?

by Henock Louis

2023, Management Science

Analysts deviate from management guidance to correct for perceived earnings management. Although the deviations reduce forecast accuracy, they improve forecast informativeness, bringing the forecasts closer to the unmanaged earnings and... more

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Prediksi Harga Saham Menggunakan Model Valuasi Teori Surplus Bersih Berdasarkan Pendekatan Ohlson

by Sarah Yuliarini

2023, AKRUAL: Jurnal Akuntansi

The aim of empirical research is continouing study about clean-surplus theory contributed to valuing firm that listed in Indonesian capital marked. Ohlson (1995) had resolved final counts by assuming that abnormal earning have a... more

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PENGARUH VARIABEL FUNDAMENTAL TERHADAP HARGA SAHAM DAN LABA PER SAHAM (Studi Kasus Pada Industri Properti Yang Go Public di Bursa Efek Jakarta )

by Wahyu Aji Santoso

2023, Wacana Jurnal Sosial Dan Humaniora

This research aims at investigating two issues. First, Whether the several fundamental variables simultantly and partially influence toward the stock price and earning per share on property companies that go public at Jakarta Stock... more

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Revenue surprises and stock returns

by Narasimhan Jegadeesh

2023, Journal of Accounting and Economics

This paper examines the relation between revenue surprises, and contemporaneous and future stock returns. It also investigates whether analysts update their earnings forecasts in response to revenue surprises in a timely and unbiased... more

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Testing the Random Walk Theory in the Nigerian Stock Market

by clement ajekwe

2023, IRA-International Journal of Management & Social Sciences (ISSN 2455-2267)

This study tests the random walk theory in the Nigerian stock market by analyzing whether stock returns follow a random walk distribution. The study employs the daily returns of the Top 20 most performing stocks on the NSE for the period... more

Fig 1: Time Series Plot of Nigerian Stock Exchange daily returns Specifically, Figure 1 indicates a high level of volatility associated with the returns in the NSE. The figure is an indication that sock returns in NSE might be randomly distributed or alternatively migh be a weak form informational efficient.

Table 1: Top 20 Most Performing Stocks on Turnover in Nigeria The daily all shares price is the main data required for analysis and is obtained from the NSE. To test the weak form efficiency of the NSE the daily returns determined by taking a natural logarithmic transformation was employed. The time series of continuously compounded daily returns are computed as follows:

Table 2: Descriptive Statistics for the Daily Returns of the Sample Firms An analysis of the ta the 20 selected +0.07% (Forte). 20 while the remaining positive return. minimum of -2.4 The to -3.97% and 3. 1% stock return on t ble reveals several points. First, the table reveals that the average stock returns for firms as well as the whole market is relatively low ranging from -0.06% (Oando) to percent of the firms have negative returns, another 20 percent have zero returns 60 percent have positive returns. Overall, the whole market has an insignificant able also indicates the minimum and maximum stock returns vary from -17.61% 96% to 24.87% for minimum and maximums respectively. The whole market has a and a maximum return of 2.3%. from the descriptive statistics it is also clear that he NSE are not approximated to normal distribution since the Jarque-Bera’s p-values are all lower than 0.05 (except with respect to Sterlin Bank.

Table 3: Autocorrelation statistics for the daily returns of the sample firms A complementary test was conducted using the runs test since daily returns of the selected samples are not normally distribution (see Table 2). The results of the runs test are presented in Table 4.

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To beat or not to beat? The importance of analysts’ cash flow forecasts

by Kelly Huang

2023, Review of Quantitative Finance and Accounting

We investigate the implications of firms' benchmark-beating pattern with respect to analysts' quarterly cash flow forecasts for current capital market valuation and future firm performance. We contend that nonnegative earnings surprises... more

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Strategic Release of Information on Friday: Evidence from Earnings Announcements

by Joshua Pollet

2023, SSRN Electronic Journal

Do firms time the release of news in response to investor inattention? We consider news about earnings and analyze the reaction of investors to announcements on Friday and on other weekdays. The announcements have two main effects on... more

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Managerial Discretion over Initial Management Earnings Forecasts

by Akinobu Shuto and

2023, SSRN Electronic Journal

The main purpose of this study is to investigate managerial discretion over initial management earnings forecasts issued concurrently with earnings announcements. The unique reporting system for management forecasts in Japan, namely... more

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Efek Entrenchment Dan Alignment Pada Manajemen Laba

by I Putu Eka Adi Sanjaya

2023

The objective of this research is to investigate whether controlling shareholder manages earnings. The issue is most important to be revealed because ownership of public companies is concentrated and low protections for noncontrolling... more

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The Market Sentiment Trend, Investor Inertia, and Post-Earnings Announcement Drift: Evidence from Korea’s Stock Market

by HYEJEONG SHIN

2023, Sustainability

We investigated whether post-earnings announcement drift (PEAD) in the Korean stock market is related to investor inertial behavior under a directional trend in market sentiment. Given that investors tend to procrastinate due to their... more

Note: Please refer to the variable definitions in research model 1. Table 2. Descriptive statistics (N = 15,315).

Note: Please refer to the variable definitions in research model 1. The Pearson correlation coefficients are indicated on the right of the empty diagonal and Spearman correlation coefficients are on the left. The figures in parentheses are p-values. Table 3. Correlations Analysis Results (N = 15,315).

Panel A: Increase in Market Sentiment between Pre- and Post-Announcement (DSENT) Panel B: Increase in Market Sentiment between Pre- and Post-Announcement (CSENT)

Note: Please refer to the variable definitions in research model 1. The notation *, **, and *** represent significance level at the 10%, 5%, and 1%, respectively.

Panel B: Cumulative Market-Adjusted Abnormal Returns (MAR60) Table 5. Portfolio Returns for Standardized Unexpected Earnings (SUE) across Change of Market Sentiment.

Note: This table represents the average abnormal returns on each portfolio conditioned on both SUE quintiles and the change in the market sentiment state (Upward Shift, Downward Shift). SUE denotes the standardized unexpected earnings calculated using a time series forecast of earnings. Market sentiment is the Korean market sentiment index suggested by Kim and Byun [13]. Upward (Downward) shift denotes when the market sentiment rises (falls) between the current and the previous quarter. The abnormal returns, SAR60 and MAR60, are size-adjusted(market-adjusted) cumulative abnormal returns over each trading day from the day after the earnings announcement date (day 0) for quarter t. Hedge returns for a portfolio of 5-1 indicates the abnormal returns from investment strategy that longs the highest portfolio (SUE5) and shorts the lowest portfolio (SUE1). Please refer to the variable definitions in research model 1.

Panel A: Upward Shift in Market Sentiment (DSENT) Note: Please refer to the variable definitions in research model 1. The notation *, **, and *** represent significance level at the 10%, 5%, and 1%, respectively.

Note: This table represents the cumulative abnormal returns on each portfolio, conditional on both the highest (lowest) SUE of quintiles and the change of market sentiment state (Upward Shift, Downward Shift). SUE denotes the standardized unexpected earnings calculated using a time series forecast of earnings. Market sentiment is the Korean market sentiment index suggested by Kim and Byun. Upward (Downward) shift denotes when the market sentiment rises (falls) between the current and the previous quarter. The abnormal returns, SAR60 and MAR60, are size-adjusted (market-adjusted) cumulative abnormal returns over each trading day from the day after the earnings announcement date (day 0) for quarter t. Table 7. Cumulative Abnormal Returns across Positive SUE and Negative SUE by the Change of Market Sentiment.

Table 8. Additional Analysis: the effect of prior-sentiment and following-sentiment on PEAD.

Note: Please refer to the variable definitions in research model 1. The notation *, **, and *** represent significance level at the 10%, 5%, and 1%, respectively. All regression models use t-statistics based on robust standard errors clustered at the firm [48] and include year fixed effects. Panel B: Market Sentiment for Post-Announcement (ASENT)

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The Effect of Industry Homogeneity on the Magnitude of Post-Earnings Announcement Drift: Evidence from Korea

by HYEJEONG SHIN

2023, Asian Academy of Management Journal of Accounting and Finance

We examine the relationship between industry homogeneity and the magnitude of postearnings announcement drift (hereafter, PEAD). Given that firms with more homogeneous operating cost structure are conducive to spillover of knowledge among... more

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Investors' Opinion Divergence and Post-Earnings Announcement Drift in REITs

by Ming-Shiun Pan

2023, Journal of Real Estate Portfolio Management

In this study, we examine whether investors' opinion divergence has explanatory power for post-earnings announcement drift in REITs. We measure investors' opinion divergence using abnormal trading turnover around the earnings... more

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Are financial analysts eager postmen of bubble psychology? Evidence in the United Kingdom

by William Forbes

2022, International Journal of Finance & Economics

This paper examines the investment value of financial analysts' advice (earnings forecasts and stock recommendations) to shareholders around two recent bubble periods in the United Kingdom: the dot-com bubble period and the credit bubble... more

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Investor Attention and the Post Earnings Announcement Drift

by Ernest Tan

2022, SSRN Electronic Journal

We investigate the effect that investor attention has on the post earnings announcement drift (PEAD), and whether investor attention mitigates the drift by reducing the level of information asymmetry for firms prior to earnings... more

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An analytical measure of market underreaction to earnings news

by Sean Yang

2022, International Review of Economics & Finance

Prior studies have provided a number of possible explanations for delayed market reactions to earnings announcements. However, there has been relatively little effort to predict the magnitude of the post-earnings announcement drift... more

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Information Asymmetry, Information Content, and Underreaction to Earnings Announcements

by Sean Yang

2022, SSRN Electronic Journal

We show that strategic informed trading that arises from the information asymmetry between the liquidity demander and the liquidity provider results in underreaction to earnings announcements. Specifically, we show that) 1 (2     k... more

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Insider Trading and Post-Earnings Announcement Drift

by Stephen Hillegeist

2022, SSRN Electronic Journal

We show that trades by corporate insiders after an earnings announcement determine in part the extent of the post-earnings announcement drift anomaly. Contrarian trades mitigate the under-reaction to earnings announcements, and... more

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Model Manajemen Laba Akrual dan Riil Berbasis Implementasi International Financial Reporting Standards

by Agus Samekto

2022, Jurnal Akuntansi dan Investasi

IFRS merupakan standar tunggal pelaporan akuntansi berkualitas tinggi dan kerangka akuntansi berbasiskan prinsip yang meliputi penilaian professional yang kuat dengan disclosure yang jelas dan transparan mengenai substansi ekonomis... more

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Short sale constraints, heterogeneous interpretations, and asymmetric price reactions to earnings announcements

by Liu Zheng

2022, Journal of Accounting and Public Policy

We investigate the effects of heterogeneous interpretations on price reactions to earnings announcements. We find that when investors interpret earnings news homogenously, price reactions are stronger to bad news. However, when... more

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An Impact of Accounting Income Numbers on Stock Performance (An Empirical Evaluation in the Context of Indian Stock Market)

by DIPA MITRA

2022, International Journal of Accounting and Financial Management Research

It is a very general understanding that stock prices are driven by the performance of the company. Again, one of the ways to measure a company's performance is to find out the growth of earnings per share. Hence the declaration of the... more

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Comportamiento asimétrico de los costos en el sector de la construcción del Ecuador

by DENISSE SANCHEZ ARGUELLO

2022, Tendencias

El sector de la construcción en el Ecuador genera gran interés por su aporte al desarrollo económico y territorial del país. Las metodologías y herramientas de análisis para este sector de actividad económica resultan insuficientes, por... more

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Faktor-Faktor yang Mempengaruhi Motivasi Manajemen Laba di Seputar Right Issue

by Yosephine Sembiring

2022, Jurnal Wira Ekonomi Mikroskil

Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi motivasi manajemen untuk melakukan aktivitas manajemen laba di sekitar waktu right issue dan menyelidiki apakah ada perbedaan antara kebijakan akrual sebelum dan... more

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Can we predict the likelihood of financial distress in companies from their corporate governance and borrowing?

by javad izadi

2022, International Journal of Accounting & Information Management

Purpose The purpose of this study is to investigate the impact of corporate governance structures on the likelihood of financial distress in UK listed companies. The paper examines the impact of borrowing and corporate governance... more

Fig. 1. Financial Expenses. Above graph shows the financial Expenses of Non-Distressed and Distressed firms for the 2010-2018 period. Financial expenses are calculated as follows; Interest Paid divided by Total assets at the beginning of the period (FE/RTA:.1), as referenced in Table 2.

Fig.2 illustrates the retained earnings of Non-Distressed and Distressed firms for the 2010-2018 period. Retained earnings are calculated as follows; Retained Profit or Losses divided by Total assets at the beginning of the period (RE/RTA‘1) as referenced in Table 2.

Note: Table 3 presents the frequency of the sample in each industry during the period of study (2010 to 2018). The industries presented were based on the Standard Industrial Classification (SIC): Mining and Quarrying (1), Manufacturing (2), Construction (3), Wholesale and Retail Trade, Vehicles and Motorcycles (4), Information and Communication (5), Real Estate Activities (6), Professional and Scientific and Technical Activities (7), Administrative and Support Service Activities (8), and Other Services Activities (9). Table 3. Sample distribution by industry

Note: Table 4 presents the descriptive statistics of the sample of 270 firm-observations. It summarises the mean, median, standard deviation, 25" percentile and 75% percentile for numeric variables. The variables are presented in Table 2. Table 4. Sample descriptive statistics

Table 4.1. Sample descriptive statistics for categorical variables Note: Table 4.1 describes the dummy variables: CEO Duality and Corporate Loans. They are coded 1 in each case where the position of chairman and CEO are exercised by the same person or where companies do have corporate loans. They are coded as 0 otherwise.

Note: Table 5 presents a comparison of the means for economic and corporate governance variables between non-distressed and distressed companies. The Table s difference of means for the mean, median, standard deviation, 25" percentile, 75 percentile and the t-test for each variable. The sample consists of 270 firm-obser and the variables are presented in Table 2. *Significant at the 10 per cent level; **Significant at the 5 per cent level; *** Significant at the 1 per cent level Table 5: Comparison of means between distressed and non-distressed companies

Table 5.1. Statistics for Categorical variables and Pearson's chi-square test Vote: Table 5.1 presents categorical variables statistics for non-distressed and distressed companies and the Pearson's chi-square test to test the associatic he Financial Distress variable. It is coded | in each case where the position of chairman and CEO are exercised by the same person or where companies ave corporate loans. It is coded as 0 otherwise. ***Significant at the | per cent level.

Table 6. Pearson and Spearman correlation coefficients Note: Table 6 provides the Pearson correlation (below diagonal) and Spearman correlation (above diagonal) between all variables. The sample consists of 270 firm-observations and the variables are presented in Table 2. ** Correlation is significant at the 1 per cent level; * Correlation is significant at the 5 per cent level.

Note: Table 7 shows the results of logistic regression. The regression used was a binomial logistic since the dependent variable (Financial Distress) is binary. The sample consists of 270 firm-observations and the variables are presented in Table 2. *Significant at the 10 per cent level. **Significant at the 5 per cent level. ***Significant at the 1 per cent level. Table 7. Logistic Regression

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