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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.

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.

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.

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.

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.

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 market response to changes in the annual “Dogs of the Dow” (DOD) portfolio. Specifically, we explore stock prices and trading volumes of the Dow stocks that are newly included into or excluded from the DOD portfolio. Although the historical performance of this popular dividend-driven investment strategy is subject to debate, our study focuses on investigating Harris and Gurel’s (1986) “noninformation-motivated demand shifts” in the sample of DOD additions and deletions. Utilizing standard event study methodology over the period 1996–2016, we find evidence that a Dow stock experiences a significant but temporary increase (decrease) in price when it is newly included into (excluded from) the DOD portfolio. Price reversals occur within one week of the reconstitutions. We also find that trading volumes temporarily increase following both index additions and deletions. The results support the price-pressure hypothesis as the DOD reconstitutions do not generally convey new information.

This paper examines stock price and volume effects associated with a change in the composition of the Nikkei 225 index in Japan in April 2000. Our results include the following: first, we show that newly added firms experience significant positive excess returns of 19% in the five-day period after the announcement of the change; in contrast, deleted and remaining firms’ returns are negatively affected, −36 and −14%, respectively; second, volume tests show significant increase in trading activity after the announcement for both added and deleted firms; third, cross-sectional analysis provides evidence that higher arbitrage risk and demand shocks increase the absolute value of excess returns.

In this chapter, we apply the new measure of speculative activities (hereafter, named the speculative ratio) in Chan, Nguyen, and Chan (2013) to study the relationship between those activities and volatility in the oil futures market. We document that the speculative ratio (trading volume divided by open interest) can isolate speculative elements from total trading activities. Using the oil futures data and dividing the data into two subperiods surrounding Hurricane Katrina, we find an increased speculative trades in the post-Hurricane Katrina period. Our results show that speculative activities create a more volatile oil futures market and they lower the information flow between volatility and speculative activities in the post-Hurricane Katrina period.