Testing the bivariate mixture hypothesis using German Stock market data

According to the bivariate mixture hypothesis (BMH) as proposed by Tauchen and Pitts (1983) and Harris (1986, 1987) the daily price changes and the corresponding trading volume on speculative markets follow a joint mixture of distributions with the unobservable number of daily information events serving as the mixing variable. Using German stock market data of 15 major companies the distributional properties of the BMH is tested employing maximum-likelihood as well as generalised method of moments estimation techniques. In addition to providing a new approach for the pointwise estimation of the latent information arrival rate based on the maximum-likelihood method, we investigate the time-series properties of the BMH. the major results can be summarised as follows: (i) the distributional characteristics of the data (especially leptokurtosis and skewness in the distribution of price changes and volume respectively) cannot be explained satisfactorily by the BMH; univariate mixture models for price changes and trading volume separately reveal a possible specification error in the model; (ii) a univariate normal mixture model can account for the observed distributional characteristics of price changes; (iii) the estimated process of the latent information rate cannot fully explain the time-series characteristics of the data (especially the volatility clustering or ARCH-effects).     

An empirical analysis of the stock price-volume relationship

This paper investigates the empirical relationship between absolute stock price changes and trading volume in the stock market. Using Granger causality tests we find that there is a significant causal relationship between absolute price changes and volume at the firm level and that this relationship is stronger in periods surrounding earnings announcements. We view this as suggesting that information arrival follows a sequential rather than a simultaneous process, although the results do not support an extreme version of either information arrival model.     

Macroeconomic announcements and price discovery in the foreign exchange market

This study shows that the dominance of the overlapping trading hours of London and New York in the price discovery of the EUR/USD and USD/JPY markets only applies on days with U.S. announcements. Different from Cai et al. (2008) and Wang and Yang (2011), we highlight the informational advantage of local traders at the arrival of macroeconomic announcements in the local market, and find that macroeconomic announcements affect the pattern of price discovery across different markets, consistent with Chen and Gau (2010) and Jiang et al. (2012). We also examine changes in information shares before and after the announcement. A significant increase in price discovery before the announcement suggests the possibility of information leakage, while enhanced price discovery efficacy after the announcement suggests that prices gradually adjust to new information, not just immediately respond to the arrival of announcements.     

The Effect of Sequential Information Arrival on Asset Prices: An Experimental Study

A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid-ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong-form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi-strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger-form market models predict equilibrium prices better than weaker-form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival (SIM) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid-ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.     

THE EMPIRICAL RELATIONSHIP BETWEEN TRADING VOLUME,RETURNS AND VOLATILITY

This paper presents an empirical analysis of the relationship between trading volume, returns and volatility in the Australian stock market. The initial analysis centres upon the volume-price change relationship. The relationship between trading volume and returns, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market. This finding also provides basic support for a positive relationship between trading volume and volatility. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for non-negative returns, thereby supporting an asymmetric relationship which is hypothesised to exist because of differential costs of taking long and short positions. Analysis at the individual stock level shows weaker support for the relationship. A second related hypothesis is tested in which the formation of returns is conditional upon information arrival which similarly affects trading volume. The hypothesis is tested by using the US overnight return to proxy for expected “news” and trading volume to proxy for news arrival during the day. The results show a reduction in the significance and magnitude of persistence in volatility and hence are consistent with explaining non-normality in returns (and ARCH effects) through the rate of arrival of information. The findings in this paper help explain how returns are generated and have implications for inferring return behaviour from trading volume data.     

Hawkes model for price and trades high-frequency dynamics

We introduce a multivariate Hawkes process that accounts for the dynamics of market prices through the impact of market order arrivals at microstructural level. Our model is a point process mainly characterized by four kernels associated with, respectively, the trade arrival self-excitation, the price changes mean reversion, the impact of trade arrivals on price variations and the feedback of price changes on trading activity. It allows one to account for both stylized facts of market price microstructure (including random time arrival of price moves, discrete price grid, high-frequency mean reversion, correlation functions behaviour at various time scales) and the stylized facts of market impact (mainly the concave-square-root-like/relaxation characteristic shape of the market impact of a meta-order). Moreover, it allows one to estimate the entire market impact profile from anonymous market data. We show that these kernels can be empirically estimated from the empirical conditional mean intensities. We provide numerical examples, application to real data and comparisons to former approaches.     

Public information arrival: Price discovery and liquidity in electronic limit order markets

How information is translated into market prices is still an open question. This paper studies the impact of newswire messages on intraday price discovery, liquidity, and trading intensity in an electronic limit order market. We take an objective ex ante measure of the tone of a message to study the impacts of positive, negative, and neutral messages on price discovery and trading activity. As expected, we find higher adverse selection costs around the arrival of newswire messages. Negative messages are associated with higher adverse selection costs than positive or neutral messages. Liquidity increases around positive and neutral messages and decreases around negative messages. Available order book depth as well as the trading intensity increases around all news. Our results suggest that market participants possess different information gathering and processing capabilities and that negative news messages are particularly informative and induce stronger market reactions.     

Long-lived information and intraday patterns

This paper studies the effect of clustering of liquidity trades on intraday patterns of volatility and market depth when private information is long-lived. The assumption of long-lived information allows us to distinguish between the patterns of information arrival and information use. Our results are: (i) volatility follows the same pattern as liquidity trading, (ii) there are no systematic patterns in the price impacts of orders, and (iii) the timing of information arrival is unimportant. Result (i) is the same as that obtained by Admati and Pfleiderer (1988) in a model of short-lived private information, but (ii) and (iii) are different.     

Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information

The arrival of public information in the U.S. Treasury market sets off a two-stage adjustment process for prices, trading volume, and bid-ask spreads. In a brief first stage, the release of a major macroeconomic announcement induces a sharp and nearly instantaneous price change with a reduction in trading volume, demonstrating that price reactions to public information do not require trading. The spread widens dramatically at announcement, evidently driven by inventory control concerns. In a prolonged second stage, trading volume surges, price volatility persists, and spreads remain moderately wide as investors trade to reconcile residual differences in their private views.     

Investor Attention and Time‐varying Comovements

This paper analyses the effect of an increase in market‐wide uncertainty on information flow and asset price comovements. We use the daily realised volatility of the 30‐year treasury bond futures to assess macroeconomic shocks that affect market‐wide uncertainty. We use the ratio of a stock's idiosyncratic realised volatility with respect to the S&P500 futures relative to its total realised volatility to capture the asset price comovement with the market. We find that market volatility and the comovement of individual stocks with the market increase contemporaneously with the arrival of market‐wide macroeconomic shocks, but decrease significantly in the following five trading days. This pattern supports the hypothesis that investors shift their (limited) attention to processing market‐level information following an increase in market‐wide uncertainty and then subsequently divert their attention back to asset‐specific information.     

Information Flows Between the US and China’s Agricultural Commodity Futures Markets—Based on VAR–BEKK–Skew-t Model

The information flow in the volatility and the skewness of returns are two factors closely influences the hedging risks for cross-border transactions. This article adopts a VAR–BEKK–MGARCH model with multivariate skew-t error terms to investigate the mean and volatility spillovers, while accounting for the potential skewness. The model is applied to real returns of corn, wheat, and soybeans futures in United States and China. The empirical results indicate the major role of United States in information transmission, and the increasing volatility spillovers of China to United States in highly marketized commodities and after trading structure changes. The analysis of skewness provides evidences for market inefficiency and implication on the investment decision and trading strategies.     

Liquidity skewness in the London Stock Exchange

We study liquidity on the London Stock Exchange. We find that the average bid-ask spread declines, but that the skewness of the spread increases. These results are robust to firm size, trading volume and price level. Our findings hold when the bid-ask spread is estimated utilising high frequency data. We find that the bid-ask spread prior to earnings announcements dates is significantly higher than that of post earnings announcements, suggesting that asymmetric information has driven the increase in liquidity skewness. We also find that the effect of earnings announcements is more pronounced in the 2007 global financial crisis, consistent with the notion that extreme market downturns amplify asymmetric information. Our overall evidence also implies that increased competition and transparent trading environments limit market makers' abilities to cross-subsidize bid-ask spreads between periods of high and low levels of asymmetric information.     

市场摩擦对特质风险溢价的影响效应——基于A股主板市场的实证分析

与国外发达市场相比,我国A股主板市场的市场摩擦因素对市场微观结构和资产定价的影响更大。在防范和化解系统性风险的过程中,进一步分析市场摩擦如何作用于特质风险定价效应的问题具有重要的理论和现实意义。本文通过采用多维市场摩擦指标来代理信息不对称、交易成本、买卖限制、卖空限制、风险对冲和外部冲击,检验中国股市特质风险和预期收益率的关系,并判断出市场摩擦因素间的差异性影响机制。回归发现,市场摩擦和特质风险因子(特质波动率和特质偏度)都具有定价效应。各维度市场摩擦因素降低了股票流动性,进而增强了特质波动率的负向定价效应,部分解释了“特质波动率之谜”,但市场摩擦对特质偏度因子溢价的影响较为微弱。同时,基于特质波动率和特质偏度因子的投资策略能够产生超越CAPM、三因子和五因子模型的绝对收益,并印证了市场摩擦对特质风险因子绝对收益的影响作用。     

Asset Price Dynamics and Infrequent Feedback Trades

This article combines the continuous arrival of information with the infrequency of trades, and investigates the effects on asset price dynamics of positive and negative-feedback trading. Specifically, we model an economy where stocks and bonds are traded by two types of agents: speculators who maximize expected utility, and feedback traders who mechanically respond to price changes and infrequently submit market orders. We show that positive-feedback strategies increase the volatility of stock returns, and the response of stock prices to dividend news. Conversely, the presence of negative-feedback traders makes stock returns less volatile, and prices less responsive to dividends.     

The intertemporal risk-Return relation,investor behavior,and technical trading profits: evidence from the G-7 countries

The intertemporal risk-return relation and investor behavior are both important pricing factors that jointly determine the expected market risk premium. Using the price adjustment process as a control variable, we find that the intertemporal risk-return relation is positive conditional on bad market news, but is non-positive conditional on good market news. This implies that good (bad) market news weakens (strengthens) the positive risk-return relation. The pattern in the distortion of the risk-return relation is consistent with short-term mispricing in which investors overvalue (undervalue) the stock market in reaction to good (bad) market news. We also show that ignoring the price adjustment process in the estimation of the risk-return relation leads to model misspecification and induces an upward (downward) bias in estimates of the relative risk aversion parameter conditional on good (bad) news. Our model of the asymmetric risk-return relation along with the price adjustment process is capable of generating the return dynamics that is attributable to technical trading profits. We suggest that the profitability of technical trading rules is not a violation of market efficiency, but a consequence of trading rules exploiting the asymmetric effect of price changes on the risk-return relation, along with the persistence property of price changes.     

Effectiveness and Market Reaction to the Stock Exchange's Inquiry in Australia

Abstract:  This paper examines a unique stock market monitoring program used by the Australian Stock Exchange (ASX) . When the ASX observes unusual share price or trading volume changes of a listed company, it sends a letter demanding an explanation. Companies need to respond publicly to several stylized questions. Such public communications between the stock exchange and listed companies contain information. This paper documents how companies respond to the ASX inquiry and how the market reacts to the replies. It is found that some companies do release new information to the market when asked. After the firm's reply is posted, the average trading volume and the bid-ask spread are reduced, and in most cases, the share price is also stabilized with the following two exceptions: (1) The price will continue to rally on average if the company releases only partial information when questioned after a significant price jump; (2) The downward price trend will be reversed if the company states that no new information could explain the decline. Furthermore, there are statistically significant, positive abnormal returns for the first five trading days, which are not conditional upon the replies firms give to the ASX inquiries.     

Abnormal trading volume,news and market efficiency: Evidence from the Jamaica Stock Exchange

This paper investigates market efficiency of the Jamaica Stock Exchange (JSE). Together, weak and semi-strong form efficiency claim that historical and newly released public information do not predict future stock price movement. We test both forms of market efficiency by analyzing stock price behavior during times of abnormal trading volume and around the release dates of earnings information. Abnormal trading volume may be driven by liquidity demand or reflect new or private information flow to the market. Using JSE data over the period 2000 to 2021, we find price dynamics consistent with price pressure as firms experience negative abnormal returns on the day of abnormal trading activity but offsetting positive abnormal stock returns on the following day. Further findings show post earnings announcement drift on the JSE. Taken as a whole, the evidence suggests violations of market efficiency and has implications for capital allocation in this emerging market.     

The Influence of Information Arrival on Market Microstructure: Evidence from Three Related Markets

This study examines the influence of information arrival on market microstructure for the MMI, NYSE, and S&P 500 stock index futures markets, with special emphasis on the effects of opening and closing of trading and expiration of contracts on price movements and trading activities. The results of the examination show that although the opening of the (MMI) futures market is associated with higher volatility, it is when the spot market opens that volatility reaches its highest level. Similarly, the closing of the futures markets, though more volatile, is not as volatile as the closing of the spot markets. Trading patterns, on the other hand, are distinct from volatility. For MMI, trading declines consistently after the close of the spot market. In contrast, the NYSE and S&P 500 continue to trade and reach a peak at the close of the futures markets. Expiration effects are evidenced by the increase in volatility and trading near the closing of the MMI and the spillover to the NYSE and S&P 500. In sharp contrast, the expirations of the NYSE and S&P 500 are only assooiated with decrease in trading, suggesting that efforts to dampen volatility by changing expiration days from Friday to Thursday and shifting settlement price from Friday close to Friday open, have been successful.     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

Non-trading,market making,and estimates of stock price volatility

We examine the effects of market making and intermittent trading on estimates of stock price volatility. When observed price changes are correctly tied to a stock's true price dynamics, it is found that non-trading per se causes a loss of efficiency but no bias in traditional volatility estimates. Non-trading induces substancial inefficiency in the extreme value estimator of volatility which it biases downward. Market making's effects add to the non-trading induced inefficiency in the traditional estimator, while information trading causes a downward bias, and liquidity trading a potentially removable upward bias, in that estimator.