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We propose a novel method of forecasting the level of informed trading at merger announcements. Informed traders typically take advantage of their knowledge of the forthcoming merger by trading heavily at announcement. They trade on positive volume or informed buys for cash mergers and negative volume or informed sells for stock mergers. In response, market makers set wider spreads and raise prices for informed buys and lower prices for informed sells. As liquidity traders trade on these prices, our vector autoregressive framework establishes the link between informed trading and liquidity trading through price changes. As long as the link holds, informed trading may be detected by measuring levels of liquidity trading. We observe the link during the −1 to +1 period for cash mergers and −1 to +5 period for stock mergers.

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.

The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

When a stock is added into the S&P 500 Index, it in effect becomes cross-listed in the Index derivative markets. When index-based trading strategies such as index arbitrage are executed, the component stocks are directly affected by such trading. We find increased volatility of daily returns, plus increased trading volume for the underlying stocks. Utilizing a list of S&P 500 Index composition changes over the period September 1976 to December 2005, we study the market-adjusted volume turnover and return variance of the stocks added to and deleted from the Index. The results indicate that after the introduction of the S&P 500 Index futures and options contracts, stocks added to the S&P 500 experience statistically significant increase in both trading volume and return volatility. Both daily and monthly return variances increase following index inclusion. When stocks are removed from the index, though, neither volatility of returns nor trading volume experiences any significant change. So, we have new evidence showing that Index inclusion changes a firm's return volatility, and supporting the destabilization hypothesis.

We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.

Using intraday prices for the S&P 500 and Nikkei Stock Average stock indexes and aggregate trading volume for the New York and Tokyo Stock Exchanges, we show how short-run comovements between national stock market returns vary over time in a way related to the trading volume and liquidity in those markets. We frame our analysis in the context of the heterogeneous-agent models of trading developed by Campbell, Grossman and Wang (1993) and Blume, Easley and O’Hara (1994) and Wang (1994) which predict that trading volume acts as a signal of the information content of a given price move. While we find that there exists significant short-run dependence in returns and volatility between Japan and the U.S., we offer new evidence that these return “spillovers” are sensitive to interactions with trading volume in those markets. The cross-market effects with volume are revealed in both close-to-open and open-to-close returns and often exhibit non-linear patterns that are not predicted by theory.

While China is currently moving toward the full development of its own financial derivatives markets, to date, China's experience with these has been a negative one. This paper examines the importance to China of developing a fully integrated financial derivatives market from both the economic and financial market perspectives. It examines the best way forward for derivative trading, both market based and over-the-counter, and the types of products best suited to both, given the current state of the Chinese financial markets. Consideration is given to market structure, regulation, trading and settlement systems and international cooperation.

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.

As a financial policy, dividend policy significantly affects firm value. This chapter analyzes how stock prices react to dividend decisions. First, a dividend payment is an extraction of value; therefore, stock price theoretically drops by the dividend amount on the ex-dividend day. In practice, the price drop and the dividend magnitude are not equal because of tax clientele, short-term trading, and market microstructure. Investors are indifferent in trading stocks before and after stocks go ex-dividend if they obtain equal marginal benefits from the two trading times. The difference in tax rates on dividends and capital gains leads to the gap between the price drop and the dividend amount. Moreover, if transaction costs are considerable, investors have high incentives to short-sell stocks until they cannot obtain more profits. The final outcome of this short-term trading is the difference between the price drop and the dividend amount. Furthermore, market microstructure factors such as limit orders, bid-ask spread, and price discreteness also create this gap. Second, dividend announcements convey valuable information to outsiders. When firms announce increases (decreases) in dividends, their stock prices tend to increase (decrease). Third, dividend policy is negatively related to stock price volatility. This negative relationship is explained by duration effect, rate of return effect, arbitrage realization effect, and information effect. Empirical evidence for this relationship is found in many countries. Finally, dividend smoothing is also considered as a signal about firms' future earnings. Consequently, firms with stable dividends have higher market value. In other words, dividend stability has a positive effect on stock prices.