Institutional investors' attention to environmental information,trading strategies,and market impacts: Evidence from China

Using a large proprietary database of intraday high‐frequency trading, we investigate the trading strategies of institutional investors in dealing with the negative environmental event disclosure of listed companies and their impact on markets, aiming to reveal the mechanism of the lack of “green efficiency” in China's capital market from the perspective of institutional investors. The results show that institutional investors react to negative environmental events prior to the announcements, indicating premature information leakage in the market; in addition, their trading behaviors mitigate the immediate effect of negative environmental event announcements on stock price. After the event is disclosed, institutional investors engage in short‐term selling and long‐term buy and hold. This trading strategy undermines the irrational selling of individual investors in the event of disclosure, short‐term decline in stock price, and long‐term reversal of market overreaction. In a China context, institutional investors generally take environmental information into consideration. However, they fail to recognize the long‐term value effect of negative environmental events and instead cater to trading strategies towards market volatility.     

Day trading and stock price volatility

When an investor buys and sells the same stock on the same day, he is said to have made a day trade. Using the trading records of Finnish traders, this paper examines whether day trading is related to volatility of stock prices. I find a strong positive time-series relation between the number of day trades by individual investors and intraday volatility among heavily day traded stocks. This effect is robust after controlling for a previously documented volume–volatility relation. The result suggests that the joint hypothesis of price pressure and volatility induced day trading dominates the liquidity effects of day trading.     

Disagreements with noisy signals and asset pricing

We consider a Lucas-type exchange economy with two trees and two investors to analyze the effects of heterogeneous beliefs and signal quality on stock market equilibrium. Our model has the following implications. There are spillover effects, in that the investors’ heterogeneous beliefs and signal quality related to one stock not only affect its own price and pricing moments, but also affect those of the other. Contrary to the conventional wisdom, we show that the volatility of one stock decreases with both its own and the other stock’s disagreements. Additionally, we reveal a negative correlation between the stocks, which decreases as the investors’ dispersions raise but increases as the discrepancy in signal quality reduces. We also show that heterogeneous beliefs and signal quality impact stock market beta mainly through scale and volatility effects, respectively. Furthermore, our findings suggest that both heterogeneous beliefs and signal quality have significant influences on the investors’ optimal portfolio plans.     

Intraday Volatility Spillover between the Shanghai and Hong Kong Stock Markets—Evidence from A+H Shares after the Launch of the Shanghai-Hong Kong Stock Connect

Using minute data of eligible A+H stocks under the Shanghai-Hong Kong Stock Connect (SHHKSC), we investigate the volatility spillover between the Shanghai and Hong Kong stock markets based on a generalized autoregressive conditional heteroskedasticity-X (GARCH-X) model with four exogenous variables, namely, volatilities of the corresponding stocks on the other market, volatilities of the indexes of both stock markets, and volatilities of the correlated stocks, which are selected using the dynamic conditional correlation model and bootstrap approach. Results show that after the launch of the SHHKSC, volatility spillovers are significant in both directions almost all the time, and the volatility spillover between the two stock markets tends to be larger when bidirectional capital flows under the SHHKSC increase or when important financial events occur. We also analyze the influences of the volatilities of correlated stocks and industries on the volatility spillover and volatilities of A+H stocks. The bidirectional volatility spillovers between Shanghai and Hong Kong stock markets do not change qualitatively after incorporating the volatilities of correlated stocks and industries in the GARCH-X model. Moreover, the average volatilities of the correlated stocks are shown to have significant influences on the volatilities of individual A+H stocks, and the influences increase when the local stock market shows a sharp rise or fall. Compared with the market indexes, the correlated stocks could be regarded as a more important and indispensable factor for individual A+H stocks’ volatilities modeling, which may carry more information than the industry.     

Contrarian strategies and investor overreaction under price limits

This study investigates the effects of price limits on investment performance of contrarian trading strategies in Taiwan’s stock market over the period 1997 to 2006. All contrarian strategies in intraday limit-hit stocks lead to superior returns relative to the benchmark index return, and the findings support the overreaction effect. Also, there is evidence of delayed overreaction reflected by price continuations for the overnight period and price reversals for the subsequent trading day. Moreover, investment performance of contrarian strategies is related to firm characteristics where investors tend to overreact more in small-size, high-turnover, and non-high-tech stocks. Finally, price overreaction is strong for up-hit stocks in the aftermath of catastrophic events. If overreaction exists, price-limit regulation designed to cool off investors and reduce price volatility may not be effective.     

Are institutional investors colluding with manipulators?

This paper examines the trading behavior of institutional investors in Taiwan before, during, and after a manipulation event and determines whether institutional investors benefit from their trading behavior during the period from the year 2000 to 2020. We find that stocks with a low turnover and small market capitalization are the main targets of price manipulators. In addition, the stock price of manipulated firms increases from the start date of the manipulation event, peaks at the end of the event, then falls after the event. Foreign institutions collude with manipulators to exaggerate stock prices for self-benefit. In contrast, securities dealers counter the trading behavior of manipulators and act as market stabilizers, causing them to suffer losses. Moreover, foreign institutions earn higher returns on stocks of manipulated firms with a low turnover during and soon after manipulation; however, they earn a higher return on stocks of manipulated firms with a high turnover in the long run after manipulation.     

Stock overreaction to extreme market events

The paper investigates the behavior of individual US stocks during the 21 trading days following the event of extreme movement in the market index on a day. We find that stocks tend to overreact after both positive and negative events, but in a more pronounced way in the latter case. This behavior is more intense when the market exhibits clustered extreme swings, indicating that the overreaction and market volatility are related. We also identify that the overreaction is driven by the performance of loser stocks that revert more strongly, even as they exhibit a lower market beta than winners.     

Impact of leveraged ETF trading on the market quality of component stocks

We investigate the effect of leveraged ETF trading on the trading activity and market quality of their component stocks. The results show that both quoted and effective spreads of component stocks increase about 0.2–3.0 basis points after the inception of leveraged ETFs, while other liquidity measures do not show significant changes. The trading volume of component stocks is positively and significantly correlated with the trading volume of leveraged ETFs, but the volatility of component stocks is not affected by ETF trading either at the daily level or during the last hour of trading. In addition, the volatility of component stocks decreases slightly after ETF inception. These findings do not support the previous claim that the trading of leveraged ETFs increases price volatility of component stocks.     

The impact of option listing on the price volatility and trading volume of underlying OTC stocks

This paper examines the impact of an initial option listing on the price volatility and trading volume of underlying OTC stocks. The sample is divided by market value to determine whether larger firms are impacted differently by option listing than smaller firms. We find relative trading volume increases significantly, with the small and medium market value firms showing the largest gain. However, the tests show no evidence of changes in price volatility following option listing. No significant changes were found in either the firms' betas or variance following option initiation. The results provide further evidence that option listing does not destabilize the market for the underlying stock.     

Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?

We study the potential merits of using trading and non-trading period market volatilities to model and forecast the stock volatility over the next one to 22 days. We demonstrate the role of overnight volatility information by estimating heterogeneous autoregressive (HAR) model specifications with and without a trading period market risk factor using ten years of high-frequency data for the 431 constituents of the S&P 500 index. The stocks’ own overnight squared returns perform poorly across stocks and forecast horizons, as well as in the asset allocation exercise. In contrast, we find overwhelming evidence that the market-level volatility, proxied by S&P Mini futures, matters significantly for improving the model fit and volatility forecasting accuracy. The greatest model fit and forecast improvements are found for short-term forecast horizons of up to five trading days, and for the non-trading period market-level volatility. The documented increase in forecast accuracy is found to be associated with the stocks’ sensitivity to the market risk factor. Finally, we show that both the trading and non-trading period market realized volatilities are relevant in an asset allocation context, as they increase the average returns, Sharpe ratios and certainty equivalent returns of a mean–variance investor.     

Earnings announcements and the variability of stock returns

This article is concerned with the dissemination process of firm-specific annual earnings information in the Norwegian capital market. We find a significant reduction in stock price volatility in the post-announcement period relative to the pre-announcement period for companies traded on the Oslo Stock Exchange in the period 1990–1995. Potential explanations for this phenomenon are tested by relating the observed return volatility to changes in the volatility of the underlying business, the speed at which information is incorporated into stock prices, and the amount of noise in the price process. The empirical analyses reveal no significant changes in either the underlying business variance or the price adjustment coefficients. However, we find a significant decline in the noise term for the largest companies after the earnings release date, supporting the hypothesis that earnings announcements reduce informational asymmetries among investors.     

Do real estate investors trade on momentum?

Real estate markets are known to be less-than-efficient for many reasons, but what roles short-term trading plays are unclear. Do short-term investors bring additional risk to the market and cause prices to deviate from fundamental values? Based on an extensive dataset of property transactions and a policy shock that substantially raised the cost of short-term trading in Hong Kong, we estimate ‘real estate risk’ with and without short-term trading based on return predictability, return volatility, and price dispersion. Our results show that as short-term investors exit the market, market returns are less predictable and less volatile, while prices are less dispersed cross-sectionally. Consistent with herding models in behavioral finance, the findings suggest that short-term investors are momentum traders who do not enhance price efficiency.     

Dynamic and asymmetric effects between carbon emission trading,financial uncertainties,and Chinese industry stocks: Evidence from quantile-on-quantile and causality-in-quantiles analysis

This paper investigates the dynamic and asymmetric effects between carbon emission trading (CET), financial uncertainties, and Chinese stocks in different industries over the period from 19th December 2013 to 21st March 2022. We utilized a novel quantile framework including rolling window quantile regression method, quantile-on-quantile method, and causality-in-quantiles method to implement this research more comprehensively and accurately. Our contributions and findings, empirical in nature, are as follows: (i) In the early establishing stage of the carbon market, with a bullish market situation, carbon emission trading has a negative impact on most industry stocks. In the developing and improving stage of the carbon market, different industries have different impact situations. (ii) We find that the effects of financial uncertainty on stocks are stronger than CET on stocks. We also find that the dependence structures between CET, financial uncertainty, and industry stocks are asymmetric in most industries, and there are many mutation structures with significant risks in extreme situations. (iii) Carbon emissions trading, crude oil volatility, and US stock volatility all have strong causal relationships with Chinese industry stocks. (iv) We also provide policy suggestions to relevant countries to balance carbon market and stock markets and avoid risks from financial uncertainty in different industries.     

Japanese Equity Market Response to U.S. Administered Protection Decisions

The standard capital market event study is used to measure Japanese firm-specific effects resulting from action taken by the US in response to alleged dumping of Japanese imports in US markets. Empirical findings are that winners and losers in the process differ predictably from each other and from the market in the way that Japanese investors view them, with differences being most pronounced at the petition filing date and the final stages of both the ITC and Department of Commerce decisions. © 1997 John Wiley & Sons, Ltd.     

The determinants of momentum in the United Kingdom

This study examines the effects of size, analyst coverage, and book-to-market in explaining momentum profits in UK stocks. We document a pattern of momentum in UK stocks and find that momentum profits are negatively related to firm size, analyst coverage, and book-to-market. We find that book-to-market is more important than coverage and coverage is more important than size in explaining momentum profits. We examine the book-to-market effect closely and find that a value premium exists for past stock losers, but a growth discount exists for past stock winners. Finally, the results of this study provide mixed support for the information diffusion hypothesis of Hong and Stein (1999).     

中国股市的最大值效应

本文证实我国股市的投资者们长期存在对股票历史业绩的反应过度现象。我们发现历史上拥有最高收益率的股票在之后业绩都表现不佳。其主要原因是我国股市的投资者们在做投资选择时都遵循一条简单的规则:即在其他条件都相同的情况下,选择拥有最高的历史收益率的股票进行投资。集中投资使拥有最高的历史收益率的股票被过高评价,导致其后来的业绩表现要比那些拥有较低历史收益率的股票差。我们称之为"最大值效应"。通过使用Fama and Macbeth(1973)横断面回归分析方法,我们确认了"最大值效应"要比CAPM理论,Blitz and Pim van Vliet(2007)发现的"波动性效应"等更为有效地解释我国股市横断面股票收益率。     

Availability and settlement of individual stock futures and options expiration-day effects: evidence from high-frequency data

This study examines whether the expiration-day effects of stock options traded in Australian Stock Exchange on return, volatility, trading volume, and temporary price changes of individual stocks vary with the availability and the settlement method of individual stock futures contracts. Using transaction data of the stocks that have both options and futures contacts from 1993 to 1997, we find that options expiration has significant effects on return and volatility of the underlying stocks in absence of individual stock futures. After introduction of a cash-settled stock futures contract, the effects decrease notably. However, the switch of a futures contract from cash settlement to physical delivery promotes the expiration effects on return and volatility and boosts temporary price changes on expiration days. Finally, options expiration has little effect on trading volume. Trading activity tends to behave normally regardless whether stock futures contracts are available or not.     

President’s Tweets,US-China economic conflict and stock market Volatility: Evidence from China and G5 countries

This study provides empirical evidence that the tweets from US President Donald J. Trump influence the trading decisions of investors worldwide. We examine the effects of Trump’s tweets related to China on stock market volatility in China and the G5 countries. Our results show that Trump’s original tweets related to the US-China economic conflict expand volatility in stock markets worldwide, and the US-China trade friction intensifies this effect. Furthermore, Trump’s tweets with different sentiments have different impacts on the returns of global stock markets. Our findings confirm that international investors may make their investment decisions based on information conveyed in these tweets.     

The impact of individual investor trading on information asymmetry in the Korean stock market

This paper examines the impact of individual investor trading on information asymmetry in the market. In particular, we examine the relationship between the trading volume by individual investors and the corresponding bid-ask spread in the Korean stock market, where the majority of the trading activity is driven by individual investors and therefore information asymmetry can be evident. We find that high trading activity by individual investors increases the bid-ask spread in a short investment horizon, suggesting that individual investors, as uninformed and unsophisticated traders, amplify the degree of information asymmetry in the market through trading.     

Do price limits hurt the market?

Under an artificial stock market composed of bounded-rational and heterogeneous traders, this paper examines whether or not price limits generate the negative effects on the market. Through testing the volatility spillover hypothesis, the delayed price discovery hypothesis, and the trading interference hypothesis, we find that no evidence of volatility spillover is observed. However, the phenomena of delayed price discovery and trading interference indeed exist, and their significance depends on the level of the price limits.