nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒11‒02
five papers chosen by
Thanos Verousis

  1. Resiliency: Cross-venue dynamics with Hawkes processes By Pelizzon, Loriana; Sagade, Satchit; Vozian, Katia
  2. The impact of US macroeconomic news on the prices of single stocks on the Vienna Stock Exchange By Gurgul, Henryk; Mitterer, Christoph; Wójtowicz, Tomasz
  3. Adversarial Attacks on Deep Algorithmic Trading Policies By Yaser Faghan; Nancirose Piazza; Vahid Behzadan; Ali Fathi
  4. On the impact of publicly available news and information transfer to financial markets By Metod Jazbec; Barna P\'asztor; Felix Faltings; Nino Antulov-Fantulin; Petter N. Kolm
  5. Exchange rates and the information channel of monetary policy By Holtemöller, Oliver; Kriwoluzky, Alexander; Kwak, Boreum

  1. By: Pelizzon, Loriana; Sagade, Satchit; Vozian, Katia
    Abstract: Market fragmentation and technological advances increasing the speed of trading altered the functioning and stability of global equity limit order markets. Taking market resiliency as an indicator of market quality, we investigate how resilient are trading venues in a high-frequency environment with cross-venue fragmented order flow. Employing a Hawkes process methodology on high-frequency data for FTSE 100 stocks on LSE, a traditional exchange, and on Chi-X, an alternative venue, we find that when liquidity becomes scarce Chi-X is a less resilient venue than LSE with variations existing across stocks and time. In comparison with LSE, Chi-X has more, longer, and severer liquidity shocks. Whereas the vast majority of liquidity droughts on both venues disappear within less than one minute, the recovery is not lasting, as liquidity shocks spiral over the time dimension. Over half of the shocks on both venues are caused by spiralling. Liquidity shocks tend to spiral more on Chi-X than on LSE for large stocks suggesting that the liquidity supply on Chi-X is thinner than on LSE. Finally, a significant amount of liquidity shocks spill over cross-venue providing supporting evidence for the competition for order flow between LSE and Chi-X.
    Keywords: liquidity,resiliency,fragmentation,competition,high-frequency data,Hawkes processes
    JEL: G10 G14
    Date: 2020
  2. By: Gurgul, Henryk; Mitterer, Christoph; Wójtowicz, Tomasz
    Abstract: Recent studies have shown that announcements of US macroeconomic news had significant impact on European stock markets. However, importance of information about the US economy may vary in time. In order to analyze this issue we examine impact of announcements of unexpected US macroeconomic news on the prices of selected stocks listed on the Vienna Stocks Exchange. Based on 5-minute returns of 13 stocks we examine how the strength and the significance of reaction of investors to unexpected macroeconomic news form the US has changed in the recent 15 years. Application of event study methodology allows us precisely describe such reaction in first minutes after news announcements.
    Keywords: event study, macroeconomic announcements, intraday data
    JEL: E44 G14
    Date: 2020–10–04
  3. By: Yaser Faghan; Nancirose Piazza; Vahid Behzadan; Ali Fathi
    Abstract: Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies. However, DRL have been shown to be susceptible to adversarial attacks. It follows that algorithmic trading DRL agents may also be compromised by such adversarial techniques, leading to policy manipulation. In this paper, we develop a threat model for deep trading policies, and propose two attack techniques for manipulating the performance of such policies at test-time. Furthermore, we demonstrate the effectiveness of the proposed attacks against benchmark and real-world DQN trading agents.
    Date: 2020–10
  4. By: Metod Jazbec; Barna P\'asztor; Felix Faltings; Nino Antulov-Fantulin; Petter N. Kolm
    Abstract: We quantify the propagation and absorption of large-scale publicly available news articles from the World Wide Web to financial markets. To extract publicly available information, we use the news archives from the Common Crawl, a nonprofit organization that crawls a large part of the web. We develop a processing pipeline to identify news articles associated with the constituent companies in the S\&P 500 index, an equity market index that measures the stock performance of U.S. companies. Using machine learning techniques, we extract sentiment scores from the Common Crawl News data and employ tools from information theory to quantify the information transfer from public news articles to the U.S. stock market. Furthermore, we analyze and quantify the economic significance of the news-based information with a simple sentiment-based portfolio trading strategy. Our findings provides support for that information in publicly available news on the World Wide Web has a statistically and economically significant impact on events in financial markets.
    Date: 2020–10
  5. By: Holtemöller, Oliver; Kriwoluzky, Alexander; Kwak, Boreum
    Abstract: We disentangle the effects of monetary policy announcements on real economic variables into an interest rate shock component and a central bank information shock component. We identify both components using changes in interest rate futures and in exchange rates around monetary policy announcements. While the volatility of interest rate surprises declines around the Great Recession, the volatility of exchange rate changes increases. Making use of this heteroskedasticity, we estimate that a contractionary interest rate shock appreciates the dollar, increases the excess bond premium, and leads to a decline in prices and output, while a positive information shock appreciates the dollar, decreases prices and the excess bond premium, and increases output.
    Keywords: monetary policy,central bank information shock,identication through heteroskedasticity,high-frequency identication,proxy SVAR
    JEL: C36 E52 E58
    Date: 2020

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