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Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: how can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly's literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis.

While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975–2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies – “daily return,” “lag one daily return,” and “weekly return” – to alleviate the potential effect of irregular data observation.

I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential, and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis.

I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.

Objective – This chapter examines the performance of the market to discover efficient equilibrium under alternative auction designs.

Background – Auctions are increasingly being used to allocate emissions allowances (“permits”) for cap and trade and common-pool resource management programs. These auctions create thick markets that can provide important information about changes in current market conditions.

Methodology – This chapter uses experimental methods to examine the extent to which the predicted increase in the Walrasian price due to a shift in willingness to pay (perhaps due to a shift in costs of pollution abatement) is reflected in observed sales prices under alternative auction formats.

Results – Price tracking is comparably good for uniform-price sealed-bid auctions and for multi-round clock auctions, with or without end-of-round information about excess demand. More price inertia is observed for “pay as bid” (discriminatory) auctions, especially for a continuous discriminatory format in which bids could be changed at will, in part because “sniping” in the final moments blocked the full effect of the demand shock.

Conclusion – Uniform-price auctions (clock and sealed-bid uniform-price, and continuous uniform-price) generate changes in purchase prices that are reasonably close to predicted changes. There is some evidence of tacit collusion causing prices to be too low relative to predictions in most cases. The worst price tracking was observed for discriminatory auctions.

Application – Uniform-price auctions appear to perform at least as well as other auction designs with respect to discovery of efficient market prices when there are unexpected and unannounced changes in willingness to pay for permits.

This study examines the impact of the trading volume on Initial Public Offering (IPO) initial return in the context of an emerging market from January 2006 to December 2016. Models consist of hierarchical and multiple regressions have been evaluated. Our results show, firstly, IPO provides an average of 21.90% of initial return to investors on the first trading day, 9.08% of return on the second day of trading, and 7.12% of return on the third day of return. Secondly, there is a positive relationship between the oversubscription ratio and initial return and no relationship between trading volume and initial return on the first three trading day. Thirdly, the trading volume does not act as a moderator that worsens the relationship between the oversubscription ratio and initial return. Lastly, this study shows that investors should actively participate in the subsequent trading of an IPO. Higher participation will bring greater liquidity and shareholder wealth in the stock market. To the authors' knowledge, this is the first study on the moderating effect of trading volume on IPO initial return in an emerging market.

The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R² values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.

This research investigated the market conditions caused by IPO advertising by examining the impact of IPO advertising, based on the US stock market from 1986 to 2009. The relationship between advertising intensity in the IPO year and the degree of IPO underpricing was examined. It was found that an increase in advertising intensity around an IPO event increases the initial returns. Simultaneously, however, advertising intensity around an IPO event also increases the degree of overvaluation, which raises the question as to whether advertising serves primarily as a mechanism to convey a firm’s true value to investors. The theoretical valuation of IPO and the relation between IPO advertising and the degree of stock overvaluation are discussed. Based on the Peasnell’s (1982) residual-income valuation framework (henceforth RIV), IPO advertising was proved to cause stock price to be more overvalued in the secondary market: a positive relationship was found between advertising and the degree of stock overvaluation relative to its theoretical value. Accordingly, an alternative hypothesis, that advertising inflates the short-run stock price, was proposed. The results of this study are consistent with the view of Purnanandam and Swaminathan (2004), namely that the stock price of newly listed firms can be overvalued.

The purpose of this chapter is to establish whether director trades provide information to investors about the future prospects of the company they form part of and thus reduce the information asymmetry beyond what is already conveyed in the financial statements.

Director Dealings were dealt with as an investment strategy by looking at past transactions of directors executed between January 2005 and December 2014 on the Malta Stock Exchange (MSE) and evaluating whether there was an increase in returns for investors who copy director trades. The study focused on whether short-term abnormal returns for up to 12 months after the transaction date, being either a buy or a sale, were made by directors in Malta when trading in their own companies.

The results show that in the short-term period of up to 12 months after the transaction date, Maltese directors do transmit information to the market both when they purchase shares in their own companies and also when they sell shares. The interesting fact about the study is that in Malta sale transactions are more valuable to the outsiders than purchase transactions. Apart from this, the results also show that some companies which are listed on the MSE are more indicative as to their future performance than others. It was ultimately concluded that even though there are informational asymmetries between directors in a company and outsiders, an outsider cannot trade solely by following director trades. The implications of the findings are discussed.

This study attempts to determine the level of significance that each insider trade has on the Maltese market, what each director trade conveys to the said market and if these trades are valuable to the outside investors even though such investors do not have knowledge of the grounds upon which the directors trade.

This paper examines secondary equity offerings that were done in the Canadian markets through “installment receipts” (IRs). Previous studies on seasoned equity offerings tend to focus on the price reaction around the announcement date. We extend the analysis to cover a longer period so that the issues of liquidity effect and information asymmetry can be adequately addressed. We also offer evidence to indicate that the use of IRs in secondary offerings can reduce the liquidity impact in markets where market depth is not as substantial as in the U.S.

Recently, there has been much progress in developing Markov switching stochastic volatility (MSSV) models for financial time series. Several studies consider various MSSV specifications and document superior forecasting power for volatility compared to the popular generalized autoregressive heteroscedasticity (GARCH) models. However, their application to option pricing remains limited, partially due to the lack of convenient closed-form option pricing formulas which integrate MSSV volatility estimates. We develop such a closed-form option pricing formula and the corresponding hedging strategy for a broad class of MSSV models. We then present an example of application to two of the most popular MSSV models: Markov switching multifractal (MSM) and component-driven regime switching (CDRS) models. Our results establish that these models perform well in one-day-ahead forecasts of option prices.