Large price movements and short-lived changes in spreads,volume, and selling pressure

In this paper we examine changes in dollar and relative bid-ask spreads of stocks following large price movements. We investigate large increases and decreases separately and link our results to current market microstructure theories on trading activities and spreads. We also look at changes in volume and selling pressure to interpret the changes in trading activity. Our results show that the market reacts differently to price increases and decreases. For large price decreases, trading increases on the sell side even when spreads have increased. For large price increases, trading increases on the buy side during a period of higher spreads. However, the increases in dollar spreads and price pressure are most pronounced at the end of trading day. Our results are consistent with microstructure models that link trading activities and costs to the level of asymmetric information.     

Trading cost expectations: Evidence from S&P 500 index replacement stock announcements

This paper tests the effect on stock value of an expected change in future trading costs. The capitalized value of a reduction in trading costs is hypothesized to increase the stock value, a trading cost effect. Improved liquidity reduces trading costs. Inclusion as an S&P 500 Index replacement stock is an event hypothesized to increase liquidity. We use 114 observations between January 1, 1983 and October 12, 1989 of stocks added to the Index as replacements for stocks removed. The abnormal return of each stock is regressed against the ratio of the bidask spread to the price of the stock, the change in trading volume of the stock, and the open interest in the Index futures contracts at the close of the month prior to the replacement announcement. We find that the positive abnormal returns for replacement stocks are related to increased daily trading volume after inclusion in the Index. Further, the trading cost effect is proportional to percentage bid-ask spreads prior to inclusion. The trading cost effect increases as trading in derivatives of the Index increases. The volume and stock price changes after replacement are not transitory, indicating an improvement in liquidity. Three alternate hypotheses suggested in prior research to explain the abnormal returns for replacement stocks are tested. Testing each of the three models previously considered: price pressure, inelastic demand curves, and information, we find that none can be accepted with statistical confidence. The abnormal returns of Index replacement stocks are consistent with rational pricing of an anticipated reduction in future transaction costs. This anticipated reduction is capitalized in the value of the stock at the time of the replacement announcement. These results are consistent with a trading cost effect.     

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。     

Forecasting volatility via stock return,range, trading volume and spillover effects: The case of Brazil

For the purpose of developing alternative approach for forecasting volatility, we consider heterogeneous VAR (HVAR) model which accommodates the market effects of different horizons, namely, daily, weekly and monthly effects, and examine the interdependence of stock markets in Brazil and the US, based on information of daily return, range and trading volume. To compare with the new approach, we also work with the univariate and multivariate GARCH models with asymmetric effects, trading volumes and fat-tails. The heteroskedasticity-corrected Granger causality tests based on the HVAR show the strong evidence of such spillover effects. We assess the value-at-risk thresholds for Brazil, based on the out-of-sample forecasts of the HVAR model, finding the new approach works satisfactory for the periods including the global financial crisis, without assuming heavy-tailed conditional distributions.     

资产收益率跳扩散过程的混频数据估计：一个波动率回馈框架

本文提出一个利用混频数据估计资产波动率的框架,该框架使用日内高频数据构造蕴含潜在发生概率的跳跃和扩散波动指标,以外生的滞后项进入回馈函数,既能充分利用样本信息,又能避免无限滞后期的回馈影响。在对沪深300指数的实证分析中,考虑一个跳跃对扩散波动具有非对称性溢出效应的双向波动率回馈模型。相对于基准模型,这一模型对数据的描述更优。分析结果显示,两类波动间存在正向回馈效应：跳跃向扩散的溢出导致自回归条件异方差（ARCH）系数存在两个区制且区制内的变异性明显;扩散向跳跃的溢出致使跳跃强度的自相关性在极端市场环境中出现强化。波动率回馈机制使得信息释放后价格反复调整变化,导致波动率高企;熔断事件折射出A股信息流质量差、融解效率低等问题。由此可以得出结论：相关监管和交易制度亟待完善。     

Retail investors’ trading and stock market liquidity

The paper investigates the relation between retail investors’ participation in trading and aggregate stock market liquidity. The findings show a positive and significant relation between retail investors’ trading and stock market liquidity. Examination of the determinants of retail investors’ trading reveals that, on average, retail investors with more diversified trading activity tend to trade when liquidity is higher, the frequency of their arrival to the market is not affected by the level of liquidity, and retail investors are willing to trade at a lower liquidity level as sellers than as buyers. Moreover, retail investors’ trading does not create price noise at the aggregate market level. Overall, the evidence suggests that retail investors contribute to market quality.     

How useful are signals? A micro-structure analysis

We analyze how the market processes a signaling event by studying a sample of self-tender offers, events often viewed as signals of firm value. By examining changes in the degree of informed trading, we find asymmetric information costs fall at announcement, remain low throughout the event, and increase at offer expiration. By one month following expiration, informed trading returns to a level not significantly different from that prior to the offer. Higher risk firms have significantly larger declines in information asymmetry during the offer. Increases in information asymmetry persist one month following expiration for firms with lower pre-offer informed trading. (JEL G14, G32)     

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。     

An empirical analysis of the Carbon Financial Instrument

This study provides an empirical investigation of the price volatility—trading volume relationship for the Carbon Financial Instrument (CFI). A CFI is a financial contract that is traded on the Chicago Climate Exchange (CCX) and represents the right to emit 100 metric tons of CO₂ equivalent. CFI contracts differ from one another on the basis of their allocation year to CCX member firms, referred to as their respective Vintage year. We provide evidence indicating a positive contemporaneous relationship between price changes and trading volume for the different CFI Vintage contracts. Employing bivariate VAR models that adjust for trade duration, we find that CFI price volatility and trading volume are persistent across time. Furthermore, we provide evidence indicating that lagged volume increases price volatility, in addition to lagged price volatility increasing trading volume levels in the CCX market. Our results are in agreement with prior research documenting significant positive price volatility—volume relationships in traditional equity markets.     

An Investigation of Stock Price Declines Following Corporate Financing Events: Further Evidence

Prior research documents a large downward drift in stock prices following issuances of debt and equity by US firms. We conduct tests based on both stock price and trading volume to provide evidence on the reasons for this apparent market anomaly. We document evidence of earnings management through accruals prior to external financing and lower operating performance afterward that is associated with the amount of capital raised. The earnings management that precedes external financing and the amount of capital raised are associated with both the post-financing decline in stock price and trading volume around earnings announcements that follow for a period of three years. This evidence is consistent with the proposition that firms raise external capital prior to predictable declines in their operating performance and they release upward biased earnings before these events to manage investor expectations. The failure of many investors to incorporate this information into their trading decisions in a timely manner consistent with limited attention and over-confidence appears to drive stock mispricing. Our evidence does not support the conjecture that the financing anomaly is primarily a statistical artifact or that it is a manifestation of the accrual anomaly.     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

Dissemination of Accruals Information,Role of Semi‐Annual Reporting,and Analysts' Earnings Forecasts: Evidence from Japan

Our study investigates the effects of dissemination of accounting accruals information on stock prices using Japanese annual reports as our sample. We conduct month‐by‐month detailed analyses of price adjustment behavior with a particular focus on revisions of analysts' earnings forecasts and changes in trading volume around the period of upcoming semi‐annual reports. We find that analysts' forecasts are often revised around this time, and analysts use this as auxiliary information. In addition, an accompanying re‐adjustment of abnormal returns and an increase in trading volume are observed. Our findings demonstrate that informational uncertainty initially triggered by the announcement of annual reports decreases as semi‐annual reports are disclosed and analysts change their earnings forecasts, and confirms the importance of semi‐annual reporting.     

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.     

Dissecting returns of non-fungible tokens (NFTs): Evidence from CryptoPunks

We use transaction data on CryptoPunks to dissect the factors affecting the returns of non-fungible tokens (NFTs). Our results show that trading volume in the short period before a trader buys (sells) CryptoPunk relates negatively (positively) to the returns on NFTs, suggesting that when market trading volume is at a high level, NFT owners are better off on the sell side, and investors interested in NFTs should avoid joining the herd. Turnover of a token tends to harm its returns. Finally, both traders’ willingness to purchase and trading experience have a positive impact on NFT returns within short-term investment horizons.     

Economic uncertainty and national bitcoin trading activity

This study analyzes the dynamics between bitcoin trading, price activities, and economic surprise shocks from a broad and novel perspective on a national level. We start by estimating the response of bitcoin trading in terms of volume and volatility to economic surprises. Following this, we extend our framework by applying a Generalized AutoRegressive Conditional Heteroskedasticity model to get an indication of the volatility reaction of national bitcoin activities to economic surprise shocks. Our results show that local and global shocks affect local bitcoin activities and trading volatilities, confirming that economic events affect bitcoin markets. We argue that increased trading activity, coupled with a price reaction, indicates that bitcoin might be considered a hedge or safe haven asset against economic uncertainty. We find evidence that bitcoin is treated as a speculative asset against negative economic policy uncertainty shocks in Canada pre-Covid-19. These results change during the Covid-19 pandemic, leading to a significant structural break. Here, we find indications that bitcoin might be treated as a safe-haven asset in New Zealand and Australia. This shows that bitcoin behaves differently depending on the studied country, underlining the importance of country-level studies. It also shows that bitcoin is a new asset that is evolving rapidly and that the period in which it is studied is important.     

Trading patterns in the European carbon market: The role of trading intensity and OTC transactions

This paper examines the effect of trading intensity and OTC transactions on expected market conditions in the early development period of the European Carbon futures market. Past duration and trading intensity are used as information related order flow variables in modelling time between transactions in two new specifications of Autocorrelation Conditional Duration (ACD) models. This allows for specific investigation of non-linear asymmetric effects on expected duration and the impact of OTC transactions. Evidence is presented of two main types of trading episodes of increased and decreased trading intensity. Both have a significant impact on price volatility, which increases further if an OTC transaction intrudes. OTC transactions also play a dual role. They slow down trading activity in the short term (over the next five transactions) but increase it substantially in the long term (over ten transactions). Both the liquidity and information price impact components increase following an OTC trade, but the information impact is greater. Price volatility calms down faster than liquidity effects following an OTC trade, and this is more pronounced in ECX and in Phase II. The combined evidence points towards increased market depth, efficiency and maturity of the trading environment.     

An equilibrium model of insider trading in continuous time

We study a Bayesian–Nash equilibrium model of insider trading in continuous time. The supply of the risky asset is assumed to be stochastic. This supply can be interpreted as noise from nonrational traders (noise traders). A rational informed investor (the insider) has private information on the growth rate of the dividend flow rewarded by the risky asset. She is risk averse and maximizes her inter-temporal utility rate over an infinite time-horizon. The market is cleared by a risk neutral market maker who sets the price of the risky asset competitively as the conditional present value of future dividends, given the information supplied by the dividend history and the cumulative order flow. Due to the presence of noise traders, the market demand does not fully reveal the insider’s private information, which slowly becomes incorporated in prices. An interesting result of the paper is that a nonstandard linear filtering procedure gives an a priori form for the equilibrium strategy to be postulated. We show the existence of a stationary linear equilibrium where the insider acts strategically by taking advantage of the camouflage provided by the noise which affects the market maker’s estimates on private information. In this equilibrium, we find that the insider’s returns on the stock are uncorrelated over long periods of time. Finally, we show that the instantaneous variance of the price under asymmetric information lies between the instantaneous variance of the price under complete and incomplete information. The converse inequalities hold true for the unconditional variance of the price.     

Testing the Markov property with high frequency data

This paper develops a framework to nonparametrically test whether discrete-valued irregularly spaced financial transactions data follow a Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates the irregular spacing that characterizes transactions data. Under such an observation rule, the current price duration is independent of a previous price duration given the previous price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Monte Carlo simulations suggest that the asymptotic test has huge size distortions, though a bootstrap-based variant entails reasonable size and power properties in finite samples. As for an empirical illustration, we investigate whether bid–ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid–ask spread. We robustly reject the Markov assumption for two out of the five stocks under scrutiny. Finally, it is reassuring that our results are consistent with two alternative measures of asymmetric information.     

Mean-variance portfolio selection of cointegrated assets

This paper considers the continuous-time mean-variance portfolio selection problem in a financial market in which asset prices are cointegrated. The asset price dynamics are then postulated as the diffusion limit of the corresponding discrete-time error-correction model of cointegrated time series. The problem is completely solved in the sense that solutions of the continuous-time portfolio policy and the efficient frontier are obtained as explicit and closed-form formulas. The analytical results are applied to pairs trading using cointegration techniques. Numerical examples show that identifying a cointegrated pair with a high mean-reversion rate can generate significant statistical arbitrage profits once the current state of the economy sufficiently departs from the long-term equilibrium. We propose an index to simultaneously measure the departure level of a cointegrated pair from equilibrium and the mean-reversion speed based on the mean-variance paradigm. An empirical example is given to illustrate the use of the theory in practice.     

Crude oil price dynamics with crash risk under fundamental shocks

Our paper presents a crude oil price model in which the price is confined in a wide moving band. A price crash occurs when the price breaches the lower boundary where a smooth-pasting condition is imposed. Using an asymmetric mean-reverting fundamental (supply/demand) shock, the solution derived from the oil price equation for the model shows the oil price follows a mean-reverting square-root process, which is quasi-bounded at the boundary. The oil price dynamics generates left-skewed price distributions consistent with empirical observations. A weakened mean-reverting force for the price increases the probability leakage for the price across the boundary and the risk of a price crash. The empirical results show the oil price dynamics can be calibrated according to the model, where the mean reversion of the price dynamics is positively co-integrated with the oil production reaction to negative demand shocks, and with the risk reversals of the commodity currencies, the Canadian dollar and the Australian dollar in currency option markets. The results are consistent with an increased price crash risk with negative demand shocks and negative risk reversals. The forecasting performance of the oil price model is better than the futures-spread models and random walk models during the crash periods. While the price of oil was above the lower boundary for most of the time, the conditions for breaching the boundary were met in 2008 and 2014 when the price fell sharply.