衍生品交易盈亏披露会影响瞬时股价吗？——基于2020年A股上市公司的分析

对2020年A股上市公司披露信息中含衍生品交易盈亏信息的数据进行多期双重差分分析，发现衍生品信息无论利好还是利空，皆存在显著负面的公告溢价。衍生品披露当日瞬时股价、3～5个交易日窗口期的累计异常收益率显著下跌，且衍生品信息不会显著影响该股票长期价值。细分披露类型发现，定期披露的衍生品信息导致的瞬时股价波动较小，且具有更显著的公告盈余漂移。     

Stock volatility and trading

Both, rational and behavioral models predict that stock and market volatility affect trading by investors. Tax-induced trading hypothesis predicts that investors increase realization of capital losses short term and capital gains only long term as volatility increases. Behavioral models predict that disposition biases of holding on to losers and disposing of winners intensifies with volatility. We document that market and stock volatility influence stock trading. Evidence on trading in response to rise in market volatility supports tax-loss harvesting hypothesis – abnormal trading of losers increases and winners decreases. However, evidence on trading patterns conditional on individual stock volatility is in support of both tax-loss-harvesting and behavioral models: trading in both losing stocks (tax-loss-harvesting hypothesis) and winning stocks (disposition effect hypothesis) increases with rise in stock volatility.     

交易量适合作为股价波动信息的代理变量吗?——来自中国沪深股市的证据

本文利用中国沪深股市日交易数据,采用多元GARCH模型从信息传递的角度进行实证研究,结果表明:股价对交易量具有显著的波动溢出效应,但交易量对股价的波动溢出效应不明显。这种波动的单向溢出说明在应对信息的冲击上股价比交易量能更快地做出反应,其后才通过波动溢出在交易量上得到反映,股价波动对成交量波动具有先导作用。因此,从波动冲击传导和信息传递的角度看,单纯地将交易量视为股价变动信息的代理变量还缺乏稳健的统计证据。     

Index futures trading and stock price volatility: Evidence from Denmark and France

This study uses an EGARCH methodology to investigate the impact of index futures trading on the price volatility of two European stock markets. The results show that index futures trading has changed the distribution of stock returns in Denmark and France, however, it has not increased stock price volatility. There is evidence that futures trading has dampened stock price fluctuations in France. The results further show that stocks in Denmark and France exhibit strong volatility persistence and asymmetry, especially during the post-futures period.     

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.     

Volatility, Efficiency, and Trading: Further Evidence

Along the lines of Amihud and Mendelson (1987a, 1989,1991), this study investigates the unique trading mechanism of the Korea Stock Exchange (KSE) and its intraday behavior of stock price volatility. The evidence from this study indicates that the introduction of an additional clearing procedure at the afternoon closing makes price discovery process more efficient than before from the viewpoint of stock price volatility. Hence, such trading mechanisms can be applied to emerging stock markets as well as developed stock markets. In addition, based on intraday analysis, stock price volatilities appear to occur mainly during the trading period, not during the lunch break or overnight period. Consequently, the results confirm the previous studies that information arrival and trading activities are the main sources of volatility.     

信息披露与内部人股票交易获利策略——以六起内部人股票交易为基础的案例研究

本文以近期A股市场内部人股票交易活跃的六家公司为例,通过考查信息披露与内部人股票交易间的关系,解释内部人股票交易的获利策略。研究发现,在允许内部人交易本公司股票的情况下,信息披露与内部人股票交易关系密切,内部人存在利用私有信息和策略性信息披露两类获利策略。信息权力是内部人股票交易的获利基础,公司业绩是影响内部人股票交易获利策略选择的重要因素,而法律诉讼风险并没有对我国内部人股票交易和信息披露产生明显约束作用。这些发现对完善我国资本市场内部人股票交易行为规范具有一定借鉴意义。     

成交量、持仓量对我国大豆类期货价差波动影响的实证分析

采用GARCH(1,1)模型就成交量、持仓量对大豆类期货价差波动率的影响进行实证分析,结果显示：当期成交量、持仓量对大豆期货价差波动的整体影响是显著的;滞后成交量、持仓量对大豆期货价差波动的整体影响也是显著的;当成交量、持仓量同时进入条件方差方程时,它们对大豆类期货价差波动的影响整体上也是显著的。这一结论揭示了我国大豆期货市场信息传递过程,验证了我国大豆期货市场的信息非有效性,对期货市场投资者以及期货市场监管者具有一定的借鉴意义。     

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.     

股指期货交易量与股指现货波动关系研究——来自香港恒生指数的实证

文章以香港恒生股票指数及其期货为样本,研究了股指波动性与指数期货交易量之间的关系。研究结果表明,它们之间存在单向因果关系,股指现货市场的日间价格波动并没有明显增加股指期货的交易,但股指期货的交易量却对指数现货的波动性产生延迟影响,这从一定程度上反映了香港市场股指期货主要被投资者用于套利而不是风险对冲的工具。     

考虑交易成本的中小板块动量效应研究

本文根据中国股票市场交易的相关规定,构造出动量效应的成本因子,然后根据构造出的动量效应成本因子对零成本条件下动量策略持有期的累积超额收益进行调整,检验在考虑成本因素以后,中小板市场中的动量效应是否依然存在。     

How does HFT activity impact market volatility and the bid-ask spread after an exogenous shock? An empirical analysis on S&P 500 ETF

In this paper, we empirically analyse infra-second datasets of the SPDR S&P 500 ETF (specifically, the ETF of the S&P 500 exchanged on BATS, named SPY.Z) in order to explain how high-frequency trading (HFT) activities (aggressive and passive) impact market volatility and the bid-ask spread before and after an exogenous shock (i.e., the 2016 US presidential election). Using SPDR S&P 500 ETF datasets as a proxy for the market on regular volume trading days (November 3, 2016) and on high-volume trading days (November 9, 2016), we show that HFT, on average, has a disturbing action mainly on regular volume trading days, whereas on high-volume trading days, it appears to have a stabilizing effect by balancing both the volatility and bid-ask spread. That is, HFT as a whole has a more neutral impact on the market’s volatility and bid-ask spread than the single aggressive and passive components. In fact, aggressive HFT has a consistent negative effect that increases, on average, both the volatility and bid-ask spread, whereas passive HFT displays a positive effect that decreases, on average, the volatility and bid-ask spread.     

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.     

Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?

Solar energy is one of the fastest growing sources of electricity generation. Forecasting solar stock prices is important for investors and venture capitalists interested in the renewable energy sector. This paper uses tree-based machine learning methods to forecast the direction of solar stock prices. The feature set used in prediction includes a selection of well-known technical indicators, silver prices, silver price volatility, and oil price volatility. The solar stock price direction prediction accuracy of random forests, bagging, support vector machines, and extremely randomized trees is much higher than that of logit. For a forecast horizon of between 8 and 20 days, random forests, bagging, support vector machines, and extremely randomized trees achieve a prediction accuracy greater than 85%. Although not as prominent as technical indicators like MA200, WAD, and MA20, oil price volatility and silver price volatility are also important predictors. An investment portfolio trading strategy based on trading signals generated from the extremely randomized trees stock price direction prediction outperforms a simple buy and hold strategy. These results demonstrate the accuracy of using tree-based machine learning methods to forecast the direction of solar stock prices and adds to the broader literature on using machine learning techniques to forecast stock prices.     

Pair trading based on quantile forecasting of smooth transition GARCH models

Pair trading is a statistical arbitrage strategy used on similar assets with dissimilar valuations. We utilize smooth transition heteroskedastic models with a second-order logistic function to generate trading entry and exit signals and suggest two pair trading strategies: the first uses the upper and lower threshold values in the proposed model as trading entry and exit signals, while the second strategy instead takes one-step-ahead quantile forecasts obtained from the same model. We employ Bayesian Markov chain Monte Carlo sampling methods for updating the estimates and quantile forecasts. As an illustration, we conduct a simulation study and empirical analysis of the daily stock returns of 36 stocks from U.S. stock markets. We use the minimum square distance method to select ten stock pairs, choose additional five pairs consisting of two companies in the same industrial sector, and then finally consider pair trading profits for two out-of-sample periods in 2014 within a six-month time frame as well as for the entire year. The proposed strategies yield average annualized returns of at least 35.5% without a transaction cost and at least 18.4% with a transaction cost.     

Asymmetric information and inside management trading in the Chinese market

Insider trading incentives have been widely examined in stock markets, but mainly in developed countries. Given the fact that the volatility of stock exchange markets in emerging economies is typically even higher, there is a need for research to explore the extent to which information asymmetry plays a role in management trading incentives in emerging economies. To address this research need, this study examines management trading incentives in relation to investment efficiency in Chinese listed firms on the main board and on the small- to medium-enterprises (SME) board in the period 2006 to 2017. We find that executives buy shares when firms’ investments are more efficient. The frequency of management buying also increases with investment efficiency. However, managers do not sell their shares according to firms’ investment efficiency. Moreover, executives of firms listed on the main board trade more on the asymmetric information of investment efficiency than those on the SME board.     

Overnight stock returns and realized volatility

The information flow in modern financial markets is continuous, but major stock exchanges are open for trading for only a limited number of hours. No consensus has yet emerged on how to deal with overnight returns when calculating and forecasting realized volatility in markets where trading does not take place 24 hours a day. Based on a recently introduced formal testing procedure, we find that for the S&P 500 index, a realized volatility estimator that optimally incorporates overnight information is more accurate in-sample. In contrast, estimators that do not incorporate overnight information are more accurate for individual stocks. We also show that accounting for overnight returns may affect the conclusions drawn in an out-of-sample horserace of forecasting models. Finally, there is considerably less variation in the selection of the best out-of-sample forecasting model when only the most accurate in-sample RV estimators are considered.     

Program Trading and Stock Index Futures: Blessing or Bane?

'Program trading'and stock index futures and options are often blamed for stock market volatility, and especially so after the Crash. Professor Tyler Cowen, of the University of California at Irvine, claims that these new trading techniques have not added to volatility and that regulation could well increase it.     

股票指数期货：工具与监管

本文从股票指数期货在金融交易中发挥的作用、股票指数期货交易的开设对股票市场波动性的影响、以及我国当前的股票市场交易制度与监管三个层面上对开设股票指数期货交易进行分析研究,并指出:就股票指数期货作为一种金融衍生工具而言,我国应该及早引入股票指数期货,以提高股票市场的运作效率。同时考虑到我国经济正在进行深层次的结构性调整,市场交易制度有其自身的特点,当前更应着重加强资本市场的制度建设,提高监管力度,为早日开设股票指数期货交易创造条件。     

Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction

In this article, we investigate the dynamic conditional correlations (DCCs) with leverage effects and volatility spillover effects that consider time difference and long memory of returns, between the Chinese and US stock markets, in the Sino-US trade friction and previous stable periods. The widespread belief that the developed markets dominate the emerging markets in stock market interactions is challenged by our findings that both the mean and volatility spillovers are bidirectional. We do find that most of the shocks to these DCCs between the two stock markets are symmetric, and all the symmetric shocks to these DCCs are highly persistent between Shanghai’s trading return and S&P 500′s trading or overnight return, however all the shocks to these DCCs are short-lived between S&P 500′s trading return and Shanghai’s trading or overnight return. We also find clear evidence that the DCC between Shanghai’s trading return and S&P 500′s overnight return has a downward trend with a structural break, perhaps due to the “America First” policy, after which it rebounds and fluctuates sharply in the middle and later periods of trade friction. These findings have important implications for investors to pursue profits.