Public Information Arrival: Price Discovery and Liquidity in Electronic Limit Order Markets

Riordan, Ryan; Storkenmaier, Andreas; Wagener, Martin; Zhang, S. Sarah

doi:10.2139/ssrn.1620425

Cited by 38 publications

(46 citation statements)

References 33 publications

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“…The Thomson Reuters sentiment dataset has also been used by Riordan, Storkenmaier, Wagener, and Zhang (2013), Leinweber andSisk (2011), Uhl, Pedersen, andMalitius (2015), and Healy and Lo (2011), among others.…”

Section: Resultsmentioning

confidence: 99%

News vs. Sentiment: Predicting Stock Returns from News Stories

Heston

Sinha

2017

Financial Analysts Journal

173

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Section: Resultsmentioning

confidence: 99%

News vs. Sentiment: Predicting Stock Returns from News Stories

Heston

Sinha

2017

Financial Analysts Journal

173

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“…For example, Kalev, Liu, Pham and Jarnecic (2004) study the intraday return volatility around firm-specific announcements; Tetlock (2010) and Riordan, Storkenmaier, Wagener and Zhang (2012) examine the information asymmetry metrics around media news days. 8 Previous literature has shown that information asymmetry impedes investment and increases the cost of capital (e.g., Diamond and Verrecchia, 1991;Easley and O'Hara, 2004).…”

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confidence: 99%

The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading

Sankaraguruswamy

Shen

Yamada

2013

Journal of Banking & Finance

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In general, Elsevier is permissive with respect to authors and electronic preprints. If an electronic preprint of an article is placed on a public server prior to its submission to an Elsevier journal or where a paper was originally authored as a thesis or dissertation, this is not generally viewed by Elsevier as "prior publication" and therefore Elsevier will not require authors to remove electronic preprints of an article from public servers should the article be accepted for publication in an Elsevier journal.However, please note that Cell Press and The Lancet have different preprint policies and will not consider articles that have already been posted publicly for publication. This is a rule agreed upon by The International Committee of Medical Journal Editors. Information on Cell Press policy on preprints is available, as is The Lancet preprint policy. Permitted scholarly postingVoluntary posting by an author on open websites operated by the author or the author's institution for scholarly purposes, as determined by the author, or (in connection with preprints) on preprint servers. Abstract This paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist [2007, Review of Accounting Studies 12, 443-477], we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of news releases in leveling the playing field of investors but also the role of uninformed investors in reducing trading cost due to information asymmetry. AbstractThis paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist [2007, Review of Accounting Studies 12, 443-477], we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of ne...

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“…This is a topical aspect of big data analysis in financial econometrics, and efforts to improve the understanding of liquidity evolution and co-evolution in the asset cross-section have recently been a focal issue of studies in equities, [HS01,KLVD12,RSWSZ13,SDS13], commodities and futures [FMZ14,MNV13] and foreign exchange and bond markets [HJS14].…”

Section: Introductionmentioning

confidence: 99%

Liquidity commonality does not imply liquidity resilience commonality: a functional characterisation for ultra-high frequency cross-sectional LOB data

Panayi

Peters

Kosmidis³

2015

Quantitative Finance

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We present a large-scale study of commonality in liquidity and resilience across assets in an ultra high-frequency (millisecond-timestamped) Limit Order Book (LOB) dataset from a pan-European electronic equity trading facility. We first show that extant work in quantifying liquidity commonality through the degree of explanatory power of the dominant modes of variation of liquidity (extracted through Principal Component Analysis) fails to account for heavy tailed features in the data, thus producing potentially misleading results. We employ Independent Component Analysis, which both decorrelates the liquidity measures in the asset cross-section, but also reduces higher-order statistical dependencies.To measure commonality in liquidity resilience, we utilise a novel characterisation proposed by [PPDZ14] for the time required for return to a threshold liquidity level. This reflects a dimension of liquidity that is not captured by the majority of liquidity measures and has important ramifications for understanding supply and demand pressures for market makers in electronic exchanges, as well as regulators and HFTs. When the metric is mapped out across a range of thresholds, it produces the daily Liquidity Resilience Profile (LRP) for a given asset. This daily summary of liquidity resilience behaviour from the vast LOB dataset is then amenable to a functional data representation. This enables the comparison of liquidity resilience in the asset crosssection via functional linear sub-space decompositions and functional regression. The functional regression results presented here suggest that market factors for liquidity resilience (as extracted through functional principal components analysis) can explain between 10 and 40% of the variation in liquidity resilience at low liquidity thresholds, but are less explanatory at more extreme levels, where individual asset factors take effect.

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Public Information Arrival: Price Discovery and Liquidity in Electronic Limit Order Markets

Cited by 38 publications

References 33 publications

News vs. Sentiment: Predicting Stock Returns from News Stories

News vs. Sentiment: Predicting Stock Returns from News Stories

The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading

Liquidity commonality does not imply liquidity resilience commonality: a functional characterisation for ultra-high frequency cross-sectional LOB data

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