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This study aims to find the response by stock market against the announcements of quarterly earnings is empirically tested by exploiting event study methodology. Efficient market hypothesis (EMH) on Saudi stock exchange is also tried on.

The market model is applied to help gauge the expected returns and to illustrate abnormal returns around the event date.

The results established that Saudi Stock Market does not bear semi-strong form of EMH. How efficient is the Saudi market is also reflected through evidence of significant abnormal returns and post-earnings announcement drift around earning announcements dates.

The authors have not used analysts’ forecast as the expected earnings which are the limitation. As mentioned earlier, the authors used the quarterly earnings of the previous year as a proxy and that proxy could have been replaced by analysts’ forecast. Another limitation is that the trading volume in the event window is not considered.

The behavior of Saudi capital market is of much concern, and the study of this with a perspective of EMH is the significance of this paper.

All stakeholders closely watch earnings announcements and its share price movement around the announcement date. Recently, Saudi Arabia has opened its doors to foreign investors, and big foreign investors are going to enter into Saudi capital market, and after their entry, the behavior of market could be different. In the authors’ opinion, this is the right time to study the efficiency of Saudi market before the entry of foreign investors.

This study is based on the gap created by EMH of Saudi market using event methodology, observed in the existing literature, and it will be a contribution to literature.

The purpose of this study is to investigate whether the earnings surprise influences decision to make earnings announcements during or after the trading hours is influenced by the earnings surprise resulting from the difference between consensus earnings estimates and the actual reported earnings.

Event study methodology was employed to test the hypotheses relating to earnings surprise and timing of earnings announcements. Twelve quarterly earnings announcements of 30 companies, drawn from BSE SENSEX of India, were studied to test the hypothesized relationships.

The study has found statistically significant differences in the market responses to the earnings announcements made during and after the trading hours. The market demonstrated a negative response to the earnings announcements made after the trading hours. Further, the results of the logistic regression have shown that the presence of significant earnings surprises is likely to induce firms to make earnings announcements after the trading hours. The results indicate that those firms that intend to reduce the overreaction and underreaction to earnings surprises are likely to make earnings announcements after the trading hours.

This paper highlights the market response to the earnings announcement made during and after the regular trading hour. Further, the paper examines if the earnings surprise influences the decision to announce the results.

The purpose of this paper is to assess the information value of earnings announcements for the 2007–2017 period in Borsa Istanbul.

Abnormal volatility (AVOL) and abnormal absolute return (AAR) in the three-day window around the earnings announcement are used as proxies for information content. A pooled regression of AVOL and AAR is conducted to test for the existence of information content and analyze its time trend along with its determinants.

The authors find significantly positive AVOL and AAR which shows that earnings have information content for investors during the sample period. Furthermore, both proxies demonstrate a positive time trend after controlling for various firm characteristics and surprise measures. The authors take this as evidence that overall informativeness of earnings has increased over time. The authors observe that this increase is most prevalent for growth companies and earnings announcements with high absolute surprise. This study provides partial support for the hypothesis that value of earnings announcements has increased after an improvement in information dissemination technology with the inception of the online disclosure platform, KAP.

Understanding information value of earnings announcements is of interest for companies which prepare earnings reports, regulators who set standards on their content and frequency and investors which make investment decisions based on information released at these announcements.

There had been few non-US studies related to information value of earnings announcements. The overwhelming majority of these are conducted using limited data sets from the latter part of the last century and only analyze annual earnings announcements. The authors aim to shed light on the subject using a broad and recent sample of quarterly earnings announcements from a major emerging market, Turkey.

This study examines the relation between the presence of analysts’ long-term growth (LTG) forecasts and the post-earnings-announcement drift (PEAD).

Using a sample of firm-quarters from 1995 to 2013, the author conducts various regression analyses.

The author finds that the magnitude of PEAD is significantly smaller for firms with LTG forecasts. The relationship holds after controlling for a wide range of explanatory variables for PEAD returns or for the presence of LTG forecasts. The author further investigates three nonexclusive hypotheses to explain this relationship. First, LTG forecasts may convey incremental value-relevant information that facilitates investors’ processing of short-term earnings information. Second, the presence of LTG forecasts may indicate superiority in analysts’ short-term forecast ability and identify firms with more efficient short-term forecasts. Third, the presence of LTG forecasts may be associated with cross-sectional differences in the persistence of earnings surprises. The author finds that none of these fully accounts for the negative relationship between the presence of LTG forecasts and PEAD returns. Instead, the relationship may be a result of the presence of LTG forecasts capturing some unobservable firm characteristics beyond those identified in prior studies.

This study contributes to the PEAD literature by identifying a novel analyst-based predictor of the cross-sectional variation in PEAD returns.

For Chinese companies that cross-list in Chinese A share and Hong Kong (H share) markets, the H share price has been consistently lower than the A share price by an average of 85% in recent years. This is puzzling because most institutional differences between the two markets have been eliminated since 2007. The purpose of this study is to explain the puzzle of the price difference of A+H companies.

Using all A and H share Chinese firms in the period 2007–2013 and a simultaneous equations approach, this study identifies three new explanations for the recent price difference.

First, utilizing a unique earning quality measure that is directly related to non-persistent components of fair value accounting under International Financial Reporting Standards (IFRS), this study finds that the lower the earnings quality, the lower the H share price relative to the A share price, and hence the greater the price difference. Second, the higher the myopic investor ownership in A share firms, the larger the A share price relative to the H share price. Third, the short-selling mechanism introduced to the A share market since 2010 helps reduce the price difference.

First, this study identifies three new explanations for the puzzle of the AH price difference which remains substantial even after the institutional and accounting standards differences between the two markets were eliminated. Second, we examine the impact of the implementation of fair value accounting under IFRS in an emerging market on the pricing difference of cross-listed shares and reveal that it can induce an unintended negative consequence on the pricing difference of cross-listed shares. Third, this study contributes to the literature on short sales by providing its mitigating role in pricing differences across two different markets. Finally, this study makes improvements in research design, which utilizes a unique measure of earnings quality that is directly related to the implementation of IFRS and a simultaneous equations approach that minimizes endogeneity concern.

The dividend month premium is the phenomenon that firms have abnormal returns in predicted dividend month. This study aims to examine the dividend month premium in the Korean stock market, using common stocks listed on the KOSPI and KOSDAQ from January 1999 to December 2016. Abnormal returns are estimated using the following asset price models: capital asset pricing model, Fama–French three-factor model and the Fama–French–Carhart four-factor model. This study finds positive abnormal returns in predicted dividend months, and even for the within-firm portfolio that buys stocks in the predicted dividend months and sells the same stocks in other months. The price impact and the subsequent reversals are greater with lower liquidity and higher dividend yield, implying that the price pressure from dividend-seeking investors affects this dividend month premium. In addition, the anomalies with the pre-declaration stock are smaller than the post-declaration stock, suggesting the necessity to improve the cash dividend policy of post-declaration for market efficiency.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

The impact of volatility crush can be devastating to an option buyer and results in a substantial capital loss, even with a directionally correct strategy. As a result, most volatility plays are for option sellers, but the profit they can achieve is limited and the sellers carry unlimited risk. This paper aims to demonstrate the dynamics of implied volatility (IV) as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the exploratory factor analysis (EFA), they extract four constructs and the results from the confirmatory factor analysis (CFA) indicated a good model fit for the constructs.

This section describes the methodology used for conducting the study. This includes the study area, study approach, sources of data, sampling technique and the method of data analysis.

Although there is extensive literature on methods for estimating IV dynamics during earnings announcement, few researchers have looked at the impact of expected market maker move, IV differential and IV Rank on the IV path after the earnings announcement. One reason for this research gap is because of the recent introduction of weekly options for equities by the Chicago Board of Options Exchange (CBOE) back in late 2010. Even then, the CBOE only released weekly options four individual equities – Bank of America (BAC.N), Apple (AAPL.O), Citigroup (C.N) and US-listed shares of BP (BP.L) (BP.N). The introduction of weekly options provided more trading flexibility and precision timing from shorter durations. This automatically expanded expiration choices, which in turned offered greater access and flexibility from the perspective of trading volatility during earnings announcement. This study has demonstrated the impact of including market sentiment and liquidity into the forecasting model for IV during earnings. This understanding in turn helps traders to formulate strategies that can circumvent the undefined risk associated with trading options strategies such as writing strangles.

The first limitation of the study is that the firms included in the study are relatively large, and the results of the study can therefore not be generalized to medium sized and small firms. The second limitation lies in the current sample size, which in many cases was not enough to be able to draw reliable conclusions on. Scaling the sample size up is only a function of time and effort. This is easily overcome and should not be a limitation in the future. The third limitation concerns the measurement of the variables. Under the assumption of a normal distribution of returns (i.e. stock prices follow a random walk process), which means that the distribution of returns is symmetrical, one can estimate the probabilities of potential gains or losses associated with each amount. This means the standard deviation of securities returns, which is called historical volatility and is usually calculated as a moving average, can be used as a risk indicator. The prices used for the calculations are usually the closing prices, but Parkinson (1980) suggests that the day’s high and low prices would provide a better estimate of real volatility. One can also refine the analysis with high-frequency data. Such data enable the avoidance of the bias stemming from the use of closing (or opening) prices, but they have only been available for a relatively short time. The length of the observation period is another topic that is still under debate. There are no criteria that enable one to conclude that volatility calculated in relation to mean returns over 20 trading days (or one month) and then annualized is any more or less representative than volatility calculated over 130 trading days (or six months) and then annualized, or even than volatility measured directly over 260 trading days (one year). Nonetheless, the guidelines adopted in this study represent the best practices of researchers thus far.

This study has indicated that an earnings announcement can provide a volatility mispricing opportunity to allow an investor to profit from a sudden, sharp drop in IV. More specifically, the methodology developed by Tan and Bing is now well supported both empirically and theoretically in terms of qualifying opportunities that can be profitable because of the volatility crush. Conventionally, the option strategy of shorting strangles carries unlimited theoretical risk; however, the methodology has demonstrated that this risk can be substantially reduced if followed judiciously. This profitable strategy relies on a set of qualifying parameters including liquidity, premium collection, volatility differential, expected market move and market sentiment. Building upon this framework, the understanding of the effects of persistence and leverage resulted in further reducing the risk associated with trading options during earnings announcements. As a guideline, the sentiment and liquidity variables help to qualify a trade and the effects of persistence and leverage help to close the qualified trade.

The authors find a positive association between the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement. These findings substantiate further the four factors that influence IV dynamics during earnings announcement and conclude that just looking at persistence and leverage alone will not generate profitable trading opportunities.

The impact of volatility crush can be devastating to the option buyer with substantial capital loss, even for a directionally correct strategy. As a result, most volatility plays are for option sellers; however, the profit is limited and the sellers carry unlimited risk. The authors demonstrate the dynamics of IV as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the EFA, they extracted four constructs and the results from the CFA indicated a good model fit for the constructs. Using EFA, CFA and Bayesian analysis, how this model can help investors formulate the right strategy to achieve the best risk/reward mix is demonstrated. Using Bayesian estimation and IV differential to proxy for differences of opinion about term structures in option pricing, the authors find a positive association among the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement.