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The purpose of this paper is to study whether mergers and acquisitions (M&As) create value in Indian and Chinese markets.

The authors study abnormal returns (AR) created by the acquiring firms in Indian and Chinese markets relating to M&A announcements, using the following three different statistical methods: i.e. mean, market and ordinary least squares adjusted return models.

On average, M&A announcements do not create value for the firms in Chinese and Indian economies. For the mean model, M&As create value for Chinese firms, whereas for the Indian firms no such value is created for the same event windows. The regression results showed that debt has a positive impact on the AR and cumulative average abnormal returns at 1, 5 and 10 per cent significance levels, respectively.

This study suggests increasing the sample size and period and using the instrumental variables regression to ensure the estimator’s impartiality, consistency and efficiency. With the investigative period surrounding a financial crisis, the estimators may have omitted bias.

Multiple methods used in this paper made it possible to capture the level of method variance in the AR, which is unusual in the Chinese and Indian context. Hence, the current study provides local knowledge and further strengthens the literature about M&As. The authors also regress AR with firm-specific factors, the consideration of which is scarce in the previous literature. Furthermore, much of what the authors know about M&A is relevant to developed economies.

With a sample of 22 banks, this study examines the significance of the news contents about the privatization of two public sector banks in India. New information does impact the stock markets. This study provides evidence on how the privatization of public sector banks impacted the returns of the Indian banking sector.

This study employs the standard event study methodology with the market model for estimating the normal returns.

The statistical results indicate that while the private sector banks experienced positive average abnormal returns on the event day, the cumulative effect of the announcement is negatively significant for both private and public sector banks. The statistical results also provide evidence of information leakage, with significant results before the announcement date. The shorter event windows analysis exhibits significant positive returns in the 5-days [−2, +2] window for the private sector banks and the entire sample, signifying a positive short-term impact on the private sector banks.

The event study literature captures the impacts of many events. However, to the best of our knowledge, the impacts of the privatization of the Indian public sector banks have never been examined using the event study methodology. Hence, this study anticipates being the first-ever study to fill this gap and extend the available literature in finance. In addition, although we provide Indian evidence, future studies may be oriented to capture cross-country impacts.

This study examines the pricing of knowledge‐based firms compared with firms that are less dependent on human resources. The results show that an increasing dependence on human resources is followed by a rise in abnormal return. The results indicate that investors are not able to distinguish personnel investments from expenses, leading to an underestimation of earnings and return. The findings suggest that investors may need accounting information on human resources to help improve investment decisions. There is no evidence in the present material to suggest that investors perceive knowledge‐based firms as more risky compared with firms with more accountable (tangible) assets.

Over a short interval of time (i.e. 2011-2014), Egypt has experienced tectonic political shifts, including the toppling of a long-entrenched dictator, two presidential elections, and a military coup. The purpose of this paper is to provide an analysis of the impact of such events on the country’s equity market behaviour, both in terms of returns and volatility.

The data set is composed of daily stock index closing prices for the overall market and top eight most actively traded sectors. To assess the impact of the considered events on the market and sector returns, an event study approach is applied. On the other hand, a univariate VAR-EGARCH model is employed to explore whether, and to what extent, volatilities at the market and sector levels respond to such events.

The results suggest that political uncertainty has a profound impact on the risk-return profiles of almost all market sectors, with different degrees of intensity. By and large, the price and volatility effects are most pronounced in banks, financial services excluding banks and chemicals sectors, whilst food and beverages as well as construction and materials sectors are found to be the least responsive to these events. The 2013 military coup turns out to be the most pervasive event impinging on the market and sector-specific indices.

The results have a number of practical implications that could be of interest to many parties involved. More specifically, with political dysfunction overshadowing business and investment activities in Egypt, genuine democratic reforms, which entail proper regard for human rights and the rule of law, must have the highest priority of policymakers, in order to secure a positive investment climate and to foster investor confidence. Furthermore, in tandem with considering other relevant factors, multinational companies need to have a thorough assessment of Egypt’s future political course and to develop more robust contingency plans to effectively combat potential threats generated by political vicissitudes.

To the author’s best knowledge, this study is the first attempt to empirically examine the price and volatility effects of the recent presidential events in Egypt, thereby contributing to the relevant literature in this area.

The rise in hostile corporate takeover attempts during the 1980s motivated many states to pass antitakeover legislation, often after lobbying by the management of affected firms. Empirical attempts to assess the impact of such statutes on firm value have yielded mixed results finding either no effect or a significant negative effect. We hypothesize that, while there may be a negative market reaction associated with state antitakeover legislation, the effect is temporary. In empirically examining the effects from the actions of nineteen states, we find that any negative market reactions tend to be followed by roughly equal positive counter‐reactions, suggesting a market overreaction.

The purpose of this paper is to explore whether share ownership structure plays a role in determining the ex-day pricing of dividends. If share ownership structure, specifically the proportion of the firm’s stock held by individuals vs institutions, has an effect on the ex-dividend day stock price behavior, the ex-day premium is expected to be different for firms with different ownership structures.

To investigate whether the ex-day pricing of dividends is affected by the proportion of the firm’s stock held by individuals vs institutions, the author look into the ex-day premium. The ex-day premium is calculated by dividing the difference between the closing price on the cum-dividend day and the closing price on the ex-dividend day by the amount of the dividend.

Consistent with both the tax-based theory and the dynamic trading clientele theory, the author find that the ex-day premium decreases with the level of individual ownership. Consistent with the short-term trading theory, the author also find that the ex-day premium increases with the degree of investor heterogeneity, defined as the product of the proportion of the firm’s stock held by individual investors and the proportion held by institutional investors.

The author believe that this study contributes to the literature by providing useful evidence that share ownership structure affects the ex-day pricing of dividends, and thus this study will be of interest to the readers of managerial finance.

This paper examines the controversy surrounding the use of the Inverted‐Sum‐Of‐Years‐Digits (ISOYD) method of goodwill amortisation and events leading to its banning by the Australian accounting regulatory bodies. Companies using the method claimed that a prohibition would reduce their share price and international competitiveness. On the other hand, efficient capital market proponents argued that the amortisation method was irrelevant to the economic position of a firm in the absence of any cash flow effects. This paper discusses these conflicting views and investigates possible motives for the choice of goodwill amortisation method through a cross‐company analysis of key characteristics. In addition, sharemarket reaction to key events leading to the change of policy was examined using conventional event‐study methodology. The cross‐company analysis revealed significant differences in the goodwill characteristics between ISOYD companies and non‐ISOYD companies which may have motivated their choice. The result of the event‐study found that no significant abnormal return could be unequivocally attributed to any of the key events or announcements.

We searched JM from 1990 to 2005 to identify all studies that employed OLS regression.¹ The search resulted in 83 articles with 147 OLS regressions. Many authors specifically state that they used OLS and these were promptly included in the sample. Other authors acknowledged regression as a methodological procedure without explicitly specifying an estimation technique. To inquire whether OLS was used, we communicated with all of these authors. In all, 51 authors were contacted, with 44 responding. Of the 44 that responded 43 had used OLS; the only exception was subsequently excluded from the analysis. The remaining seven articles were checked once more, and consensus was reached that OLS had most likely been used. Therefore, they were also included in the study.

This paper aims to investigate the intervalling effect bias in ETFs' systematic risk expressed by beta. The authors' findings reveal the existence of a significant intervalling effect on ETFs' beta obtained by the ordinary least squares method (OLS). Also investigated is the impact of ETFs' capitalization on beta. Results provide evidence that small cap ETFs have greater betas than large cap ETFs. Results also reveal that the OLS beta of all ETFs increases when the return interval is lengthened regardless of capitalization. The impact of ETFs' trading activity on systematic risk is assessed too. Findings give evidence that the OLS betas of the ETFs that trade infrequently are biased downwards while the beta of the frequently traded ETFs is biased upwards. Finally, the paper reveals a strong intervalling effect on ETFs' tracking error.

The authors employ a sample of 40 broad‐based ETFs listed on Nasdaq Stock Exchange to test whether beta estimates change when the return interval measurement changes. Their data cover a maximum period of ten years starting from September 16, 1998 using daily, weekly and monthly return data. The authors estimate beta applying three alternative methods: the market model applied with the OLS method, the Scholes and Williams model (SW beta) and the Dimson model (Dim beta).

Results indicate that the average beta of ETFs derived by the OLS method increases when the return interval increases. The differences among the daily, weekly and monthly OLS betas are statistically significant at the 1 per cent level. This finding implies a strong intervalling effect bias in ETFs' OLS beta. On the other hand, the authors did not find any statistically significant differences in daily, weekly and monthly Scholes and Williams and Dimson betas. Moreover, results show that the daily and weekly OLS and Scholes and Williams betas and weekly OLS and Dimson betas are significantly different from each other.

In this paper using a sample of 40 broad‐based ETFs listed on Nasdaq Stock Exchange, the authors have examined various issues concerning: the intervalling effect bias in ETFs' systematic risk, the relation between beta and capitalization of ETFs, the relation between beta and trading frequency of ETFs and, finally, the intervalling effect bias in ETFs' tracking error. While the literature on intervalling effect on securities' beta and the relation between systematic risk and market value and trading activity is voluminous, this is the first attempt to examine these issues with respect to ETFs.

The paper introduced the use of a hybrid system of neural networks support vector machines (NNSVMs) consisting of artificial neural networks (ANNs) and support vector machines (SVMs) to price single-family properties.

The mechanism of the hybrid system is such that its output is given by the SVMs which utilise the results of the ANNs as their input. The results are compared to other property pricing modelling techniques including the standalone ANNs, SVMs, geographically weighted regression (GWR), spatial error model (SEM), spatial lag model (SLM) and the ordinary least squares (OLS). The techniques were applied to a dataset of 3,225 properties sold during the period, January 2012 to May 2014 in Cape Town, South Africa.

The results demonstrate that the hybrid system performed better than ANNs, SVMs and the OLS. However, in comparison to the spatial models (GWR, SEM and SLM) the hybrid system performed abysmally under with SEM favoured as the best pricing technique.

The findings extend the debate in the body of knowledge that the results of the OLS can significantly be improved through the use of spatial models that correct bias estimates and vary prices across the different property locations. Additionally, utilising the result of the hybrid system is thus affected by the black-box nature of the ANNs and SVMs limiting its use to purposes of checks on estimates predicted by the regression-based models.