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The authors examine the factors that impact the growth of exchange traded funds (ETFs) from 1990 to 2020. The authors show the first-mover and winner-takes-all effects from top ETF issuers. Besides the longer history and larger asset under management (AUM), the ETFs being managed by top issuers have exhibited lower risks and higher trading volume. Delisted ETFs on the contrary has a shorter history, lower AUM, higher risks, and lower trading volume. For zombie ETFs, the authors find longer history, lower risks but lower AUM and trading volume, controlled for total expense ratio, return, volatility, Amihud (2002) illiquidity, bid-ask spread, turnover ratio, as well as year, issuer, asset class and region fixed effects. The authors further study the ETFs’ AUM and trading activities over the 2008 Global Financial Crisis (GFC) and COVID-19 pandemic crisis, and find that the GFC has a significant negative impact while the COVID-19 has a positive impact on the ETFs’ popularity. The significant increase in AUM of ETF relative to common stocks during the COVID-19 is associated with retail investors’ holdings, as the authors document a significant reduction of institutional holdings at the aggregate level.

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.

We examine the informational roles of trades and time between trades in the domestic and overseas US Treasury markets. A vector autoregressive model is employed to assess the information content of trades and time duration between trades. We find significant impacts of trades and time duration between trades on price changes. Larger trade size induces greater price revision and return volatility, and higher trading intensity is associated with a greater price impact of trades, a faster price adjustment to new information and higher volatility. Higher informed trading and lower liquidity contribute to larger bid–ask spreads off the regular daytime trading period.

Stock markets during the day are relatively centralized, while night markets, due to the dominance of electronic trading venues, are fragmented. Though electronic markets at night allow more competition for order flow, they may result in decreased order interaction and decreased transparency. Using transaction data for three exchange traded funds (ETFs), we find that bid–ask spreads are wider at night due to higher order processing costs, market maker rents, and inventory holding costs. Results show that night markets are informationally fragmented and are not able to impound information available in net order flow to the same degree as day markets.

While organization theories acknowledge the influence of specific assets on dependence and increasingly represent the latter as a structure of mutual dependence (dependence of A on B and dependence of B on A), there is, to the best of our knowledge, no empirical test concerning the impact of specific assets on a structure of dependence. Our chapter aims to fill this gap. It is all the more original in that it considers a case study where dependence changes sides according to the characteristics of the transaction. We examine the dependence between Chilean exporters and European importers when trading fresh produce. Such dependence originates with the need for just-in-time coordination and compliance with a compelling demand in a context of high price uncertainty.

Using a unique dataset from international trade in fresh produce between Chile and the rest of the world, we justify the use of a concentration sales ratio as a proxy for dependence and test the influence of a variety of specific assets on the side of dependence by using both categorical and dimensional approaches. Original findings show that certain transaction attributes have a strong influence on the side of dependence. In particular, the higher the frequency and the level of specific assets such as volume, niche varieties, and joint sales with other products, in the transaction, the greater the likelihood of a higher ratio of dependence for the importer rather than the exporter. Conversely, in the event of low levels of specific assets and less frequent operations, dependence tends to be greater on the side of the exporter.

The annual general meeting (AGM) constitutes, at least in theory, one of the main instruments to ensure good corporate governance. It also involves the release of corporate information to the financial market. We have examined the effects of the AGM on the volatility of stock returns and on the volume of shares traded. We have investigated the informative role of the AGM in the Spanish stock market during the period 2003–2009. This chapter constitutes the first investigation of the issue in a civil-law country. Extant research is scarce and limited to two common-law countries: the United States and the United Kingdom, where the AGM has been found to involve the release of relevant information to the market. Nevertheless, since the influential paper by La Porta, López de Silanes, Shleifer, and Vishny (1998), evidence reported in common-law countries cannot be automatically extrapolated to countries with a different legal tradition. As expected our results indicate that the information content of the AGM is lower in Spain than in common-law countries. In fact, no relevant information is released during the AGM in the Spanish stock market. This result is robust to company characteristics like size and the level of insider shareholders within its capital. Our findings support that the AGM plays a less significant role in ensuring good corporate governance in civil-law compared with common-law countries.

While differences in stock price behaviours among developed countries have been extensively researched and documented, investigations of this nature for emerging economies are, however, much less comprehensive. We undertake a quantitative analysis that investigates six different types of panel data models to define the best one that explains the stock price behaviour of publicly traded companies in emerging countries. The research is based on a sample from Compustat Global, including 5,167 stocks of companies from 38 emerging countries, covering 119 months (1998–2007), totalling 235,621 observations. This analysis of the elasticities of regressors corresponding to stock transactions in stock markets, through a considerable sample, contributes to a deeper discussion about stock price behaviour in countries with less developed stock markets. The findings demonstrate that stock quantity and total volume traded per month significantly influence closing price behaviour over time, with more efficient estimators for the fixed effect model. Moreover, different elasticities are verified among countries. This chapter does not take into account the macroeconomic reasons why the differences among countries occur. Further, the consideration of developed countries, such as United States, United Kingdom, France or Australia, could bring the possibility of comparison of stock prices among countries in a broader perspective. Overall this analysis can help governments and private initiative for the formulation and implementation of strategic actions, in order to constantly improve the quality of their stock markets and, consequently, to increase the entry of resources destined to the development of nations.

We propose a novel method of forecasting equity option spreads using the degree of multiple listing as a proxy for expectations of future spreads. Spreads are a transactions fee for traders. To determine the future spreads on options being considered for purchase, traders must take current market trends affecting spreads into account. One such trend is the continued decline in spreads due to the multiple listing of options. Options listed on 4–6 exchanges compete more intensely than those listed on fewer exchanges, so that they may be expected to experience greater future declines in spreads. This study identifies the listing dates and number of listed exchanges for options listed on up to six exchanges as of May 2005. Listing criteria for multiple listing are defined with short- and long-term volumes, market capitalization, net income, and total assets being significant determinants of multiple listing. Short- and long-term volumes were found to have no explanatory power for multiple listing. Ranges of listing criteria are specified so that traders may locate the options of their choice.