First to “Read” the News: News Analytics and Algorithmic Trading

Beschwitz, Bastian von; Keim, Donald B.; Massa, Massimo

doi:10.1093/rapstu/raz007

Cited by 29 publications

(8 citation statements)

References 46 publications

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“…In addition, high-frequency traders (HFTs) can become informed by paying to observe the (autocorrelated) retail order flow and, in turn, can increase adverse selection for other (uninformed) market makers. Also, along the lines of the evidence provided by von Beschwitz et al (2020), news analytics of media coverage ignite algorithmic trading, and although they tend to speed up stock price and trading volume in response to articles, they also reduce liquidity.…”

Section: B Attention-driven Retail Tradingmentioning

confidence: 99%

Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown

Ozik¹,

Sadka

Shen³

2021

J. Financ. Quant. Anal.

136

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This article studies the impact of retail investors on stock liquidity during the COVID-19 pandemic lockdown in spring 2020. Retail trading exhibits a sharp increase, especially among stocks with high COVID-19–related media coverage. Retail trading attenuated the rise in illiquidity by roughly 40% but less so for high-media-attention stocks. Causality is addressed using the staggered implementation of the stay-at-home advisory across U.S. states. The results highlight that ample free time and access to financial markets facilitated by fintech innovations to trading platforms are significant determinants of retail-investor stock market participation.

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Section: B Attention-driven Retail Tradingmentioning

confidence: 99%

Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown

Ozik¹,

Sadka

Shen³

2021

J. Financ. Quant. Anal.

136

View full text Add to dashboard Cite

show abstract

“…The effect could be caused by HFTs reacting faster to a signal non-HFTs also observe (Von Beschwitz, Keim, andMassa 2015, Chordia, Green, andKottimukkalur 2018). But the most probable signals they would both utilize in close succession do not fully explain the results (e.g., past returns, news articles, analyst forecasts and recommendations, management guidance, and form 8-K filings).…”

mentioning

confidence: 92%

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Hirschey

2021

Management Science

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This study provides evidence that high-frequency traders (HFTs) identify patterns in past trades and orders that allow them to anticipate and trade ahead of other investors’ order flow. Specifically, HFTs’ aggressive purchases and sales lead those of other investors, and this effect is stronger at times when it is more difficult for non-HFTs to disguise their order flow. Consistent with some HFTs being more skilled or more focused on anticipatory strategies, I show that trades from a subset of HFTs consistently predict non-HFT order flow the best. The results are not explained by HFTs reacting faster to news or past returns, by contrarian or trend-chasing behavior by non-HFTs, or by trader misclassification. These findings support the existence of an anticipatory trading channel through which HFTs increase non-HFT trading costs. This paper was accepted by Karl Diether, finance.

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“…The use of computers and intelligence in processing data from sources derived from information such as social media and news has increased in recent years and has become a viable trading strategy to use .The earlier studies conducted by Smales (2014) which aims to determine the market reaction of stocks to stock-specific news shows that the number of available news items reveals different responses to market activity, volatility, bid-ask spreads, and return; The relevance of news items is very important when identifying significant effects; and reactions to volatility, market activity, and spreads are most affected by negative news. von Beschwitz et al (2018) adds that the news release algorithm by computer can speed up the response of trading volume and stock prices. News analysis using computer algorithms can increase market efficiency because temporary price distortions due to inaccurate news analysis can be corrected quickly.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of News Related to Covid-19 on Stock Market Returns in Five Major ASEAN Countries

Rahadian

Nurfitriani

2022

jeb

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The sudden tightening of global finances, unprecedented and dominating news of how negative COVID-19 is has affected the global monetary, and how pessimistic the public sentiment towards the COVID-19 virus pandemic is itself has caused uncertainty in the stock market. The purpose of this study is to analyze the relationship between COVID-19-related news and stock market returns. RavenPack Coronavirus Media Monitor was used to explain important news issues related to COVID-19 with news indices such as panic, media hype, fake news, country sentiment, infodemic, and media coverage. With the quantile regression analysis technique, the results of the study were divided into three research periods. For the research period of January 2020 to March 2020, it was found that the variables that affect stock market returns are media hype, fake news, country sentiment and infodemic index; for the research period of April 2020 to December 2020, it was found that the variables that affect stock market returns are panic, fake news and country sentiment index; while for the period January 2020 to December 2020 the variables that affect stock market returns are panic, fake news, country sentiment and infodemic index.

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First to “Read” the News: News Analytics and Algorithmic Trading

Cited by 29 publications

References 46 publications

Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown

Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown

Do High-Frequency Traders Anticipate Buying and Selling Pressure?

Impact of News Related to Covid-19 on Stock Market Returns in Five Major ASEAN Countries

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