The Impact of Macroeconomic News on Quote Adjustments, Noise, and Informational Volatility

Hautsch, Nikolaus; Hess, Dieter; Veredas, David

doi:10.2139/ssrn.1343297

Cited by 18 publications

(15 citation statements)

References 60 publications

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“…The fact that Bund Futures trading is concentrated on one market platform, might be an obvious reason why HFTs are generally less aggressive than on equity markets and primarily make their profits from market making strategies. 4 Finally, we contribute to the literature on the effects of news arrivals, such as, e.g., Fleming & Remolona (1999), Green (2004), Andersen et al (2003) and Hautsch et al (2011). Our results thus provide novel insights into liquidity dynamics of HFTs and nHFTs around scheduled announcements as well as after distinct events such as the Brexit referendum.…”

Section: Introductionmentioning

confidence: 71%

The Ambivalent Role of High-Frequency Trading in Turbulent Market Periods

Hautsch

Noé²,

Zhang

2017

SSRN Journal

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We show an ambivalent role of high-frequency traders (HFTs) in the Eurex Bund Futures market around high-impact macroeconomic announcements and extreme events. Around macroeconomic announcements, HFTs serve as market makers, post competitive spreads, and earn most of their profits through liquidity supply. Right before an announcement, however, HFTs significantly widen spreads and cause a rapid but short-lived drying-out of liquidity. In turbulent periods, such as after the U.K. Brexit announcement, HFTs shift their focus from market making activities to aggressive (but not necessarily profitable) directional strategies. Then, HFT activity becomes dominant and market quality can degrade.

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Section: Introductionmentioning

confidence: 71%

The Ambivalent Role of High-Frequency Trading in Turbulent Market Periods

Hautsch

Noé²,

Zhang

2017

SSRN Journal

Self Cite

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“…Bernile et al (2015) suggest these findings are consistent with information leakage. 1 Our study differs from Hautsch et al (2011) and Bernile et al (2015) in two important aspects. First, our methodology and an expanded set of announcements allow us to show that pre-announcement informed trading is limited neither to FOMC announcements nor to the last minute before the official release time.…”

Section: Introductionmentioning

confidence: 76%

Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?

Kurov

Sancetta

Strasser

et al. 2018

J. Financ. Quant. Anal.

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We examine stock index futures and Treasury futures around the release time of 30 U.S. macroeconomic announcements. Nine of the 20 announcements that move markets show evidence of substantial informed trading before the official release time. Prices begin to move in the “correct” direction approximately 30 minutes before the release time. The preannouncement price drift accounts on average for approximately 40% of the total price adjustment. This implies that some traders have private information about macroeconomic fundamentals. Preannouncement drift might originate from a combination of information leakage and superior forecasting that incorporates proprietary data.

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“…Brenner et al (2009) find that US macroeconomic information drives the level, volatility, and co-movement of the US stock, Treasury, and corporate bond markets. Hautsch et al (2011) find that the arrival of macroeconomic news has an impact on the bid and ask dynamics of the German Bund futures. Rangel (2011) examines the effect of macroeconomic firm-specific news sentiment on intraday volatility persistence, even after controlling for the potential effects of macroeconomic news.…”

Section: Macroeconomic Newsmentioning

confidence: 87%

Building News Measures from Textual Data and an Application to Volatility Forecasting

Caporin

Poli

2017

Econometrics

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We retrieve news stories and earnings announcements of the S&P 100 constituents from two\ud professional news providers, along with tenmacroeconomic indicators.We also gather data fromGoogle\ud Trends about these firms’ assets as an index of retail investors’ attention. Thus, we create an extensive\ud and innovative database that contains precise information with which to analyze the link between news\ud and asset price dynamics. We detect the sentiment of news stories using a dictionary of sentiment-related\ud words and negations and propose a set of more than five thousand information-based variables that\ud provide natural proxies for the information used by heterogeneousmarket players. We first shed light on\ud the impact of information measures on daily realized volatility and select them by penalized regression.\ud Then,we performa forecasting exercise and showthat themodel augmentedwith news-related variables\ud provides superior forecasts

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The Impact of Macroeconomic News on Quote Adjustments, Noise, and Informational Volatility

Cited by 18 publications

References 60 publications

The Ambivalent Role of High-Frequency Trading in Turbulent Market Periods

The Ambivalent Role of High-Frequency Trading in Turbulent Market Periods

Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?

Building News Measures from Textual Data and an Application to Volatility Forecasting

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