Public information releases, private information arrival and volatility in the foreign exchange market

This paper estimates the impact of market activity and news on the volatility of returns in the exchange market for Japanese Yen and US dollars. We examine the effects of news on volatility before, during and after news arrival, using three categories of news. Market activity is proxied by quote arrival, separated into a predictable seasonal component and an unexpected component. Results indicate that both components of market activity, as well as news releases, affect volatility levels. We conclude that both private information and news effects are important determinants of exchange rate volatility. Our finding that unexpected quote arrival positively impacts foreign exchange rate volatility is consistent with the interpretation that unexpected quote arrival serves as a measure of informed trading. Corroborating this interpretation is regression analysis, which indicates that spreads increase in the surprise component of the quote arrival rate, but not in the expected component. The estimated impact of a unit increase in unexpected quote arrival and the range of values observed for this variable imply an important volatility conditioning role for informed trading.     

Volatility spillovers and the effect of news announcements

We examine the effect of US and European news announcements on the spillover of volatility across US and European stock markets. Using synchronously observed international implied volatility indices at a daily frequency, we find significant spillovers of implied volatility between US and European markets as well as within European markets. We observe a stark contrast in the effect of scheduled versus unscheduled news releases. Scheduled (unscheduled) news releases resolve (create) information uncertainty, leading to a decrease (increase) in implied volatility. Nevertheless, news announcements do not fully explain the volatility spillovers, although they do affect the magnitude of volatility spillovers. Our results are robust to extreme market events such as the recent financial crisis and provide evidence of volatility contagion across markets.     

The Impact of Public Information on the Stock Market

We study the relation between the number of news announcements reported daily by Dow Jones & Company and aggregate measures of securities market activity including trading volume and market returns. We find that the number of Dow Jones announcements and market activity are directly related and that the results are robust to the addition of factors previously found to influence financial markets such as day-of-the-week dummy variables, news importance as proxied by large New York Times headlines and major macroeconomic announcements, and noninformation sources of market activity as measured by dividend capture and triple witching trading. However, the observed relation between news and market activity is not particularly strong and the patterns in news announcements do not explain the day-of-the-week seasonalities in market activity. Our analysis of the Dow Jones database confirms the difficulty of linking volume and volatility to observed measures of information.     

Non-scheduled news arrival and high-frequency stock market dynamics: Evidence from the Australian Securities Exchange

An increasing number of market participants utilise news analytics software to comprehend the large amounts of unstructured data flowing through news-wires. Utilising original data from one such tool – Ravenpack – I examine the market reaction of leading Australian stocks to stock-specific news flow over an extended period. Unconditional analysis of key variables around 484,440 news items reveals distinct responses in market activity, volatility, bid-ask spreads and returns. The study confirms previous literature such that indicated relevance of news items is critical when identifying significant effects. In addition, the reaction of market activity, volatility and spreads is greatest for negative news. The findings are confirmed when controlling for market dynamics and cross-dependencies between variables in a high-frequency VAR model.     

基于不同分布假设下波动模型估计效果比较——以上海股票市场为例

本文基于不同分布假设,即正态分布、Student-t分布以及EGB2分布,使用2005年1月4日至2011年6月30日上证综指日收益率数据对GARCH模型和GJR GARCH模型估计效果进行实证比较。实证结果显示：（1）基于非对称EGB2分布的GJR GARCH模型更适合中国证券市场;（2）中国股票市场存在波动不对称性,且好消息引发的波动大于坏消息引发的波动,这可能与中国股票市场特有的市场结构和交易制度有关;（3）波动的不对称特性可能部分来自于对分布偏度特性考虑的欠缺,验证了合理的分布假设在波动行为分析过程中的重要性。     

Macroeconomic news announcements and the role of expectations: evidence for US bond,stock and foreign exchange markets

We investigate the impact of scheduled government announcements relating to six different macroeconomic variables on the risk and return of three major US financial markets. Our results suggest that these markets do not respond in any meaningful way, to the act of releasing information by the government. Rather, it is the ‘news’ content of these announcements which cause the market to react. For the three markets tested, unexpected balance of trade news was found to have the greatest impact on the mean return in the foreign exchange market. In the bond market, news related to the internal economy was found to be important. For the US stock market, consumer and producer price information was found to be important. Finally, financial market volatility was found to have increased in response to some classes of announcement and fallen for others. In part, this result can be explained by differential ‘policy feedback’ effects.     

Forecasting Financial Market Volatility Using a Dynamic Topic Model

This study employs big data and text data mining techniques to forecast financial market volatility. We incorporate financial information from online news sources into time series volatility models. We categorize a topic for each news article using time stamps and analyze the chronological evolution of the topic in the set of articles using a dynamic topic model. After calculating a topic score, we develop time series models that incorporate the score to estimate and forecast realized volatility. The results of our empirical analysis suggest that the proposed models can contribute to improving forecasting accuracy.     

Comparative analysis on the effects of the Asian and global financial crises on precious metal markets

The global financial crisis has vigorously struck major financial markets around the world, in particular in the developed economies since they have suffered the most. However, some commodity markets, and in particular the precious metal markets, seem to be unscathed by this financial downturn. This paper investigates therefore the nature of volatility spillovers between precious metal returns over fifteen years (1995-2010 period) with the attention being focused on these markets’ behavior during the Asian and the global financial crises. Daily closing values for precious metals are analyzed. In particular, the variables under study are the US$/Troy ounce for gold, the London Free Market Platinum price in US$/Troy ounce, the London Free Market Palladium price in US$/Troy once, and the Zurich silver price in US$/kg. The main sample is divided into a number of sub periods, prior to, during and after the Asian crisis. The aim of this division is to provide a wide and deep analysis of the behavior of precious metal markets during this financial event and of how these markets have reacted during times of market instability. In addition, this paper also looks at the effects of the global financial crisis from August 2007 to November 2010 using GARCH and EGARCH modeling. The main results show that there is clear evidence of volatility persistence between precious metal returns, a characteristic that is shared with financial market behavior as it has been demonstrated extensively by the existing literature in the area. In terms of volatility spillover effects, the main findings evidence volatility spillovers running in a bidirectional way during the periods; markets are not affected by the crises, with the exception of gold, that tends to generate effects in all other metal markets. However, there is little evidence in the case of the other precious metals generating any kind of influence on the gold market. On the other hand, there is little evidence of spillover effects during the two crisis episodes. Finally, the results from asymmetric spillover effects show that negative news/information have a stronger impact in these markets than positive news, again a characteristic that has been also exhibited by financial markets.     

Information arrivals and intraday exchange rate volatility

This paper investigates the link between information arrivals and intraday DEM/$ volatility. Information arrivals are measured by the numbers of news items that appeared in the Reuters News Service. We separate news stories into different categories and find that total headline news counts, US and German macroeconomic news and German Bundesbank monetary policy news all have a significant impact on intraday DEM/$ volatility. The larger quantitative effects of the German Bundesbank monetary policy news and US macroeconomic news at 15-min intervals are consistent with the findings of a two-stage adjustment process of public information arrivals [Fleming and Remolona, J. Finance (1999) 1901]. Our results suggest that the persistent of intraday exchange rate volatility set off by public information is extended by traders’ private information about 15 min later. The conclusions are obtained from ARCH models that incorporate intraday seasonal volatility terms.     

Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany

The occurrence and the transmission of large shocks in international equity markets is of essential interest to the study of market integration and financial crises. To this aim, implied market volatility allows to monitor ex ante risk expectations in different markets. We investigate the behavior of implied market volatility indices for the U.S. and Germany under a straightforward mean reversion model that allows for Poisson jumps. Our empirical findings for daily data in the period 1992 to 2002 provide evidence of significant positive jumps, i.e. situations of market stress with positive unexpected changes in ex ante risk assessments. Jump events are mostly country-specific with some evidence of volatility spillover. Analysis of public information around jump dates indicates two basic categories of events. First, crisis events occurring under spillover shocks. Second, information release events which include three subcategories, namely—worries about as well as actual—unexpected releases concerning U.S. monetary policy, macroeconomic data and corporate profits. Additionally, foreign exchange market movements may cause volatility shocks.     

Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis

We study the simultaneity impact of the European Central Bank news on the daily realized volatility transmission mechanism (spillovers) among various US spot and futures markets. To this end, we apply a bias-corrected vector autoregressive model via Wild bootstrap simulation. We use minute-by-minute intraday data to construct daily realized volatility. We consider 429 news form the ECB as important events employing two major classifications, namely, a country classification with the highest total number of days related ECB news and a type of ECB news classification. We find that investors in futures markets react more vigorously and mainly for the ECB news that is associated with the group of EMU member states applied structural reforms. Yet, more importantly, we show that the US stock markets response heterogeneously to the ECB news, as we find key disagreements in the reactions both across the US markets and the types of ECB news studied. Such evidence is consistent with the explanation of the differential interpretation of information among market participants. From a practical point of view, we suggest that investors in the US spot market can effectively use two or more futures contracts to minimize their exposure to volatility risk associated with that news.     

Multifrequency news and stock returns

Equity prices are driven by shocks with persistence levels ranging from intraday horizons to several decades. To accommodate this diversity, we introduce a parsimonious equilibrium model with regime shifts of heterogeneous durations in fundamentals, and estimate specifications with up to 256 states on daily aggregate returns. The multifrequency equilibrium has higher likelihood than the Campbell and Hentschel [1992. No news is good news: an asymmetric model of changing volatility in stock returns. Journal of Financial Economics 31, 281–318] specification, while producing volatility feedback 10 to 40 times larger. Furthermore, Bayesian learning about volatility generates a novel trade-off between skewness and kurtosis as information quality varies, complementing the uncertainty channel [e.g., Veronesi, 1999. Stock market overreaction to bad news in good times: a rational expectations equilibrium model. Review of Financial Studies 12, 975–1007]. Economies with intermediate information best match daily returns.     

Volatility Spillovers of Stock Markets between China and the Countries along the Belt and Road

ABSTRACT

This article intensively studies the stock market volatility spillover effects between China and the countries along the Belt and Road (B&R) based on the covered selection of Morgan Stanley Capital International Inc (MSCI) index by using multiplicative error model to measure stock market volatility with daily price range. The results show that during the whole sample period, there are bilateral linkages of volatility between the stock markets of China and all of B&R countries. Most of B&R and China’s markets are sensitive to positive news but the asymmetry is trivial. Financial crisis intensified the volatility spillover effects across countries while the markets’ volatilities tend to be influenced by the negative shocks from foreign markets. The B&R markets as risk absorbers exhibit significant sensitivities to the negative news from Chinese market during the crisis period.     

The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect

In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic. We use hourly data for cryptocurrencies and daily data for the news indicator, thus, the GARCH MIDAS framework which allows for mixed data frequencies is adopted. We validate the presupposition that fear-induced news triggered by the COVID-19 pandemic increases the return volatilities of the cryptocurrencies compared with the period before the pandemic. We also establish that the predictive model that incorporates the news effects forecasts the return volatility better than the benchmark (historical average)model.     

News-based sentiment and bitcoin volatility

In this work, I studied whether news media sentiments have an impact on Bitcoin volatility. In doing so, I applied three different range-based volatility estimates along with two different sentiments, namely psychological sentiments and financial sentiments, incorporating four various sentiment dictionaries. By analyzing 17,490 news coverages by 91 major English-language newspapers listed in the LexisNexis database from around the globe from January 2012 until August 2021, I found news media sentiments to play a significant role in Bitcoin volatility. Following the heterogeneous autoregressive model for realized volatility (HAR-RV)—which uses the heterogeneous market idea to create a simple additive volatility model at different scales to learn which factor is influencing the time series—along with news sentiments as explanatory variables, showed a better fit and higher forecasting accuracy. Furthermore, I also found that psychological sentiments have medium-term and financial sentiments have long-term effects on Bitcoin volatility. Moreover, the National Research Council Emotion Lexicon showed the main emotional drivers of Bitcoin volatility to be anticipation and trust.     

Macroeconomic announcements and asymmetric volatility in bond returns

This study analyses the impact of macroeconomic news announcements on the conditional volatility of bond returns. Using daily returns on the 1, 3, 5 and 10 year US Treasury bonds, we find that announcement shocks have a strong impact on the dynamics of bond market volatility. Our results provide empirical evidence that the bond market incorporates the implications of macroeconomic announcement news faster than other information. Moreover, after distinguishing between types of macroeconomic announcements, releases of the employment situation and producer price index are especially influential at the intermediate and long end of the yield curve, while monetary policy seem to affect short-term bond volatility.     

Macro news and bond yield spreads in the euro area

This paper analyses the effects of newspaper coverage of macro news on the spread between the yield on the 10-year German Bund and on sovereign bonds in eight countries belonging to the euro area (Belgium, France, Greece, Ireland, Italy, the Netherlands, Portugal and Spain) using daily data for the period 1999–2014. The econometric analysis is based on the estimation of a VAR-GARCH model. The results can be summarized as follows. Negative news have significant positive effects on yield spreads in all GIIPS (Greece, Ireland, Italy, Portugal and Spain) countries but Italy before September 2008; markets respond more to negative news, and their reaction has increased during the recent financial crisis. News volatility has a significant impact on yield spread volatility, the effects being more pronounced in the case of negative news and bigger in the most recent crisis period, especially in the GIIPS countries. Further, the conditional correlations between yield spreads and negative news increase in absolute value during the financial crisis (especially in the GIIPS countries), indicating a higher sensitivity of the former to the latter.     

引入国债期货合约能否发挥现货市场稳定效应?——基于中国金融周期的研究视角

我国国债期货市场能否发挥稳定现货市场功能,金融周期风险是否会改变国债期货市场对现货市场波动的影响,是投资者实施风险管理和监管部门构建市场稳定机制的重要依据。本文通过信息传递机制和交易者行为两个维度探析国债期货市场发挥稳定功能的微观机理,分析金融周期风险对衍生工具稳定功能的影响,解析引入国债期货合约能否缓解金融周期波动对国债市场冲击,同时关注我国国债期货交易机制改进与现券波动关系。研究发现:(1)我国国债期货市场已实现抑制现货市场波动的功能,金融周期风险会引发现货价格波动,国债期货市场能够降低金融周期的波动冲击;(2)改善现货市场深度和套保交易是国债期货市场发挥稳定功能的微观路径,国债期货市场增进国债预期交易量流动性、减弱非预期交易量干扰,金融周期低波动区间套保交易稳定作用受到抑制;(3)国债期货投机交易和波动溢出效应助长现货市场波动,正负期现基差对国债波动影响具有非对称特征。     

Exchange rate volatility response to macroeconomic news during the global financial crisis

We investigate the volatility reaction to macroeconomic news in major currency markets during the recent global financial crisis. We first present an alternative method for determining the changes in economic states by endogenously estimating crisis thresholds. Second, we assess which macroeconomic indicator gave the earliest warning signal for the upcoming contraction. Third, we investigate whether there is a systematic change in the volatility reaction of exchange rates to news during the crisis period. We find that the estimated logistic transition function based on the housing starts data exhibits the earliest warning signal compared to other indicators. Our results suggest that although volatility response to most news indicators is larger in expansion, currency market reaction to new home sales and Fed funds rate news is larger in the crisis period. We attribute this finding to the context-specific relevance of the housing and credit sectors in the evolution of the global financial crisis.     

中国股票市场波动性研究：模型选择及实证

以日收盘数据计算出的市场日收益率作为研究的基础数据,利用准极大似然估计方法QML估计三种ARCH类模型(GARCH、T-GARCH和E-GARCH)对中国股市波动性与稳定性的运行效果进行了实证研究的结果,得出EGARCH(1,1)模型是最优的拟合模型。运用最优模型实证发现中国股市不仅波动性很大,而且波动是不对称的。