Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

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.     

Public information arrival and volatility persistence in financial markets

This paper explores the relationship between daily market volatility and the arrival of public information in four different financial markets. Public information is measured as the daily number of economic news headlines, divided in six categories of news. Statistical analysis of the news data suggests the presence of particular seasonality effects, as well as a strong degree of autocorrelation. Over the period 1994–1998, significant effects of specific news categories on the volatility of US stocks, treasury bills, bonds and dollar were detected. However, the effects – in size and duration – vary by news category and by financial market. It is demonstrated that most of the volatility persistence, as observed by GARCH models, tends to disappear when news is included in the conditional variance equation.     

When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions

We examine high-frequency market reactions to an intraday stock-specific news flow. Using unique pre-processed data from an automated news analytics tool based on linguistic pattern recognition we exploit information on the indicated relevance, novelty and direction of company-specific news. Employing a high-frequency VAR model based on 20 s data of a cross-section of stocks traded at the London Stock Exchange we find distinct responses in returns, volatility, trading volumes and bid-ask spreads due to news arrivals. We show that a classification of news according to indicated relevance is crucial to filter out noise and to identify significant effects. Moreover, sentiment indicators have predictability for future price trends though the profitability of news-implied trading is deteriorated by increased bid-ask spreads.     

Time and dynamic volume–volatility relation

This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive (VAR) model is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid–ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.     

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.     

Trading Patterns and Prices in the Interbank Foreign Exchange Market

The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.     

Market conditions,default risk and credit spreads

This study empirically examines the impact of the interaction between market and default risk on corporate credit spreads. Using credit default swap (CDS) spreads, we find that average credit spreads decrease in GDP growth rate, but increase in GDP growth volatility and jump risk in the equity market. At the market level, investor sentiment is the most important determinant of credit spreads. At the firm level, credit spreads generally rise with cash flow volatility and beta, with the effect of cash flow beta varying with market conditions. We identify implied volatility as the most significant determinant of default risk among firm-level characteristics. Overall, a major portion of individual credit spreads is accounted for by firm-level determinants of default risk, while macroeconomic variables are directly responsible for a lesser portion.     

The impact of salient political and economic news on the trading activity

This paper investigates the impact of salient political and economic news on the intraday trading activity, namely, the stock return volatility, the stock price volatility, the number of shares traded, and the trading frequency. Using transactions data on 33 constituent stocks of the Hang Seng Index in the Stock Exchange of Hong Kong (SEHK), we find that political news has a distinct impact on market activity when compared with economic news. We argue that the observed phenomenon is related to the precision of signals associated with these two types of news and investors' perceptual biases.     

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.     

The effect of option transaction costs on informed trading in the options market around earnings announcements

We investigate the effect of option market transaction costs (a form of market imperfection) on the ability of option implied volatility-based measures to predict future stock returns and volatility around quarterly earnings announcements. We find that the predictability is significantly stronger for firms with lower option relative bid-ask spreads. The effect is more pronounced around positive rather than negative earnings news. We find no significant effect of option transaction costs around randomly chosen dates when there is no clustering of major information events. Trading strategies based on option market predictors and transaction costs earn monthly abnormal returns of 1.39% to 1.91%.     

Impact of macroeconomic news on metal futures

This paper uses intra-day data for the period 2002 through 2008 to examine the intensity, direction, and speed of impact of US macroeconomic news announcements on the return, volatility and trading volume of three important commodities - gold, silver and copper futures. We find that the response of metal futures to economic news surprises is both swift and significant, with the 8:30 am set of announcements - in particular, nonfarm payrolls and durable goods orders - having the largest impact. Furthermore, announcements that reflect an unexpected improvement in the economy tend to have a negative impact on gold and silver prices; however, they tend to have a positive effect on copper prices. In comparison, realized volatility and volume for all three metals are positively influenced by economic news. Finally, there is evidence that several news announcements exert an asymmetric impact on market activity variables.     

Volatility spreads and earnings announcement returns

Prior research documents that volatility spreads predict stock returns. If the trading activity of informed investors is an important driver of volatility spreads, then the predictability of stock returns should be more pronounced during major information events. This paper investigates whether the predictability of equity returns by volatility spreads is stronger during earnings announcements. Volatility spreads are measured by the implied volatility differences between pairs of strike price and expiration date matched put and call options and capture price pressures in the option market. During a two-day earnings announcement window, the abnormal returns to the quintile that includes stocks with relatively expensive call options is more than 1.5% greater than the abnormal returns to the quintile that includes stocks with relatively expensive put options. This result is robust after measuring volatility spreads in alternative ways and controlling for firm characteristics and lagged equity returns. The degree of announcement return predictability is stronger when volatility spreads are measured using more liquid options, the information environment is more asymmetric, and stock liquidity is low.     

THE EFFECTS OF DECIMALIZATION ON RETURN VOLATILITY COMPONENTS,SERIAL CORRELATION,AND TRADING COSTS

We examine the composition of return volatility, serial correlation, and trading costs before and after decimalization on the New York Stock Exchange. We decompose the variance of price changes into components associated with public news, rounding errors, and market‐making frictions. We find that when stocks move from a fractional to a decimal trading system, the variance components due to market‐making frictions and rounding errors decline significantly, whereas the component due to public news remains unchanged. The serial correlation of price changes weakens substantially after decimalization. The uninformed component of bid‐ask spreads decreases significantly whereas the informed component has no significant change.     

It is not only what you say,but how you say it: ESG,corporate news,and the impact on CDS spreads

We assess the influence of corporate news on costs of financing for a sample of large European and U.S. firms from 2006 to 2016. Focusing on environmental, social, and governance (ESG) news items, we take into account volume (number of news items), tonality (positive, neutral, negative), and source (financial or mass media). We find that (1) the volume of ESG-related news is significantly associated with credit default swap (CDS) spreads and therefore matters for companies' refinancing costs; (2) news with positive (negative) tonality is associated with lower (higher) CDS spreads by about 4% (6%); (3) tonality matters even more for ESG-related news. These results hold for different subsamples and alternate specifications, and are relatively insensitive to omitted variables.     

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.     

Volatility changes in European currency exchange rates due to EMS announcements

This study examines the effects of announcements concerning European Monetary Union on the exchange rate volatilities of several European currencies. It is expected that when good news is portrayed in regard to a single currency this will be considered bad news, thus eliciting a negative reaction, for the German mark. Conversely, good news for a single currency should also be good news for weaker currencies, such as the Portuguese escudo, the Italian lira, the Greek drachma, and the Spanish peseta. In terms of volatility, a reaction to good news should be a reduction in volatility, as bad news should cause an increase in volatility. In total there are 22 announcements examined from January 1986 through September 1997. The German mark is observed to experience greater increases in volatility than decreases, as does the Italian lira. Portugal and Greece appear to react more strongly to positive news in that the decreases in volatility are on average greater than the increases.     

The role of private information in return volatility,bid–ask spreads and price levels in the foreign exchange market

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.     

Currency bid-ask spread dynamics and the Asian crisis: Evidence across currency regimes

Using a sample of 21 emerging and developed country currencies, we evaluate the impact of the Asian crisis on bid-ask spreads. While the crisis had widespread and uniform volatility effects, the spread effects were not uniform across emerging and developed country currencies. For Asian emerging markets, spreads widened and spread volatility increased significantly during the crisis, while developed markets spreads narrowed and spread volatility decreased significantly. We investigate the impact of more flexible and less flexible exchange rate regimes on bid-ask spreads using panel data. In general, countries with tightly-managed regimes have significantly lower spreads than countries with more freely-floating regimes, while controlling for the influence of other factors such as volatility. Asian developing market spreads are higher than spreads of the other countries, again, after controlling for the influence of other factors.     

Macroeconomic news and treasury futures return volatility: Do treasury auctions matter?

Various macroeconomic announcements are known to influence asset price volatility. In addition to non-farm payrolls, we highlight the importance of Treasury auctions – a news event that has grown in importance due to ongoing Federal deficits. The occurrence of an auction, which increases supply in the underlying cash market, pushes futures prices lower and volatility higher. Conversely, a higher bid-to-cover ratio, indicates greater demand for Treasury securities, increases Treasury futures prices and lowers volatility. The response is consistent with market participants using futures to manage inventory risk. The results are consistent across a set of volatility estimates, and in an alternate conditional volatility framework.