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This paper aims to assess the impact of different financing strategies used in the cross-border acquisitions on the shifts in the risk profile of the acquiring companies in India. The purpose is to discern which of the stated modes of payment, viz., cash, stock and earnout, enables an acquiring company in better hedging the risk of adverse selection in cross-border acquisitions.

Analysis has been conducted by computing unsystematic (alphas, αs) and the systematic (betas, βs) risk of the acquiring companies, for three different estimation periods, that is the pre-acquisition estimation period, the post-acquisition estimation period and the pooled estimation period. The computations of αs and βs, for each company, have been done by using the market model, whereas further analysis of the average αs and average βs has been done by applying analysis of variance and paired sample t-test.

It has been found that of the three modes of payment, earnouts provide best hedge to the acquiring companies for minimizing the risk of adverse selection in cross-border acquisitions.

The paper recommends earnouts as a prudent strategy for the acquiring companies from India as well as other emerging markets for their future global acquisitions.

This is the pioneering study on analyzing the impact of the different financing strategies on the shifts in the risk profile of acquiring companies.

This paper explores the relationship between size, book-to-market, beta, and expected stock returns in the U.S. Information Technology sector over the July 1990–June 2001 period. Two models, the multivariate model and the three-factor model, are employed to test these relationships. The risk-return tests confirm the relationship between size, book-to-market, beta and stock returns in IT stocks is different from that in other non-financial stocks. However, the sub-period results (the periods before and after the technology crash in April 2000) show that the nature of the relationship between stock returns, size, book-to-market, and market factors, or the magnitude of the size, book-to-market, and market premiums, is on average unchanged for both sub-periods. This result suggests the technology stock crash in April 2000 was not a correction of stock prices.

This paper has demonstrated the impacts of default risk, personal taxes, leverage‐related costs, and the limited liability of security‐holders on the systematic risk of equity. Since more than one of the aforementioned market imperfections exists in the real world, the results derived in this paper have been shown to be more general in specification than Hamada and Rubinstein's traditional formulation. The analysis also demonstrates that failure to recognize these market imperfections tends to bias the estimation of systematic risk.

We investigate the effect standard time series β‐adjustments have on the OLS‐β. We report that most changes are not statistically significant and the β‐adjustments appear to have no relationship to the extent of thin trading. Researchers using β face the difficult choice of using an estimate known to be biased by thin trading, or making an adjustment that may not be statistically significant.

A unit trust is a vehicle by which a large number of investors can pool their varying amounts of money into one trust fund. In return they are issued with “units” in proportion to the fraction of the fund that they own. The fund is then invested, by the managers, on the Stock Exchange. Investors buy units from the managers at what is known as the offer price and can sell them back to the managers at what is known as the bid price. These purchases and sales can be made through direct contact with the managers or via an agent such as a bank, stockbroker, accountant or solicitor.

The purpose of this paper is to examine the impact of the March 28, 1979 accident at the Three Mile Island (TMI) nuclear power facility on the risk and return of General Public Utilities (TMI's owner) and other electric utilities heavily invested in nuclear power facilities. The results have implications for the returns required by investors and, therefore, on the economic viability of nuclear power for electricity generation. A recent article by Bowen, Castanias, and Daley used cumulative abnormal residual (CAR) analysis to examine the impact of the TMI accident on the electric utility industry. However, as has been shown by Larcker, Gordon, and Pinches, CAR results may be misleading due to systematic risk changes and autocorrelation in the data. Intervention analysis is proposed as an alternative to CAR analysis. This paper compares the results of a traditional cumulative abnormal residual analysis with the results of intervention analysts. It is found that the CAR analysis indicates abnormal negative returns occurred immediately after the TMI accident. However, intervention analysis shows the assumptions necessary for the CAR method to be appropriate are violated. When adjustments are made for a shift in systematic risk and autocorrelation, no abnormal returns are observed for GPU, for other utilities with nuclear facilities or for non‐nuclear utilities. These results are in conflict with those reported by BCD.

The main purpose of this study is to examine whether macroeconomic variables could subsume the size and book‐to‐market (BM) anomalies for longer‐return intervals using Tokyo Stock Exchange‐listed stocks.

The Fama‐MacBeth cross‐sectional regressions of various models over time‐intervals ranging from one month to one year are performed.

The empirical results show that most macroeconomic variables explain short‐term returns within six months, with the industrial production as the only variable that persistently explains returns of all horizons ranging from one month to one year. Firm size does bear significant risk premium, but its significance diminishes for return‐intervals beyond three months when macroeconomic variables are included in the regression. BM is the only variable that significantly accounts for the cross‐section of stock returns for all horizons, regardless of the inclusion of macroeconomic variables.

These empirical findings suggest that stock returns are determined by both rational factors such as macroeconomic variables and behavioral factors such as BM.

The findings suggest that potential trading strategies indeed can be formed to exploit the persistent predictability, especially the BM regularity.

This paper is the first study that examines the competing explanatory power of various asset‐pricing models over different investment horizons.

The information of pledging stocks for liquidity by controlling shareholders of publicly traded firms in Taiwan has been required to disclose since 1998. A common perception by market practitioners in Taiwan is that stock pledging by controlling shareholders is an indication of expropriation of firms. This study first examines the determinants of the tendency that controlling shareholders of firms in Taiwan pledge their stocks to financial institutions for liquidity and then evaluates how stock pledging by controlling shareholders affects their firms' accounting and financial performances. Determinants of firm attributes, market conditions, and corporate governance are identified. The tendency of stock pledging by controlling shareholders has a negative effect on accounting and financial performances. The negative effect on firm performance is reduced when the firm has a higher level of working capital. These findings indicate that stock pledging by controlling shareholders is an indication of weak corporate governance when the firm has lower liquidity. These findings may provide insights to the equity markets of the other countries in which public firms have more concentrated ownerships.

Earlier studies establish a positive relationship between volatility index (VIX) and the stock index returns. These studies are mainly restricted to developed markets and research in this regard in emerging markets is scarce. The purpose of this paper is to fill this gap.

The paper studies the direct and cross‐sectional relationship of India VIX in relation to three important parameters: viz., stock beta, market to book value of equity and market capitalization. The paper constructs value weighted portfolio sorted on the basis viz., stock beta, market to book value of equity and market capitalization. The paper employs three‐factor multiple regression to find out the results.

The paper finds that India VIX has a positive and significant relationship with the returns of the value‐weighted high‐low portfolios sorted on the basis of the above parameters. The paper examines the behavior of India VIX in the presence of the above two parameters. The India VIX yields a positive and significant relationship with the above sorted portfolio returns.

India VIX was recently introduced in November, 2007 and therefore the research is expected to suffer from small sample bias.

The findings suggest India VIX is a distinct risk factor capable of predicting the price discovery mechanism of the market.

In the rapidly expanding emerging markets the introduction of Volatility Index is a recent phenomenon. Research in this regard is scarce, particularly in the area of finding predictive ability of the Volatility Index. This research is in this direction and would definitely help the market regulators and policy‐makers with their understanding of the market and market direction. It would help them to correct the market imbalances and avert crisis, which has been recently witnessed.

This paper aims to seek answers to a primary question: “How much do divergent leverage factors account for fluctuations in time-varying financial leverage in leading hospitality sub-sectors decomposed by four exclusive sub-portfolios?” In the path of seeking answers, this paper investigated the effects of both firm-specific and macroeconomic indicators to firms’ varying financial leverage in those primary sub-sectors overtime.

In each sub-sector portfolios, firms were sorted based on market-to-book values (Mktbk _it ) with median breakpoint percentiles. For hypothesis testing, this paper constructed panel regression models with firm fixed-effects to layout fluctuant financial leverage phenomenon engaged with a set of 11 leverage factors in each Mktbk _it sorted sub-sector portfolios.

Results exhibited assorted evidences. The bottom line was: firms with different market capitalization rates in each portfolio acted differently in regard to the magnitude of financial leverage across time.

The final sample of 415 firms in four sub-sector portfolios sufficiently embraced financial leverage composition in the hospitality industry across time. However, by reason of lack of data in the other intra-hospitality industries, such as gaming and/or cruise lines, findings did not represent the firms operated in those sub-industries.

This paper departed from the established context of the previous literature in the manner that it expects to add to the literature by demonstrating the core drivers causing the deviations in financial structure in four exclusive, hospitality industry sub-sector portfolios with varying leverage proxies overtime.