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    News media and the stock market: Assessing mutual relationships An interdisciplinary multi-method study of financial journalism, news media, emotions, market events and the stock market Strauß, N.

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    Citation for published version (APA): Strauß, N. (2018). News media and the stock market: Assessing mutual relationships: An interdisciplinary multi- method study of financial journalism, news media, emotions, market events and the stock market.

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    Download date: 19 Oct 2020

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  • 121

    Chapter 7

    Financial Networks: Describing Network and Stock Price Dynamics During Quarterly Earnings Announcements

    This study is in preparation for submission to Internet Research. An earlier version of this study was presented at Etmaal van de Communicatiewetenschap in Tilburg, February 2017.

  • 142 Chapter 7

    Abstract

    Focusing on quarterly earnings (QE) announcements of companies listed on the Dow Jones Industrial Average (DJI) index in summer 2016, this study investigates financial networks on Twitter. Network analyses imply that the core of the financial network is mainly constituted of established news media, journalists and professional investors. However, independent and anonymous voices in the financial markets also seem to have access. Furthermore, analyses suggest that attention paid toward reporting companies on Twitter might lead to a downward trend of their stock prices, while reversed effects appear to be mixed. Eventually, a qualitative analysis of secondary data implies that expectations on the market about the QE and the actual reporting and presentation of the numbers by the company and the financial media afterwards might impact the stock market reactions of the reporting company to various extents.

    Introduction

    Financial networks are often considered to be an exclusive, highly educated and elitist group of people. This applies particularly when scholars refer to the closed and self-referential networks in financial centers such as Wall Street in New York, The City in London, or Frankfurt in Germany (Ho, 2009; Norfield, 2016). Ethnographical studies have provided useful insights about the culture of those financial market centers, working cultures among bankers and investors as well as the nature of national and transnational financial networks (e.g., Ho, 2009). However, new technologies such as online trading platforms, online media and social media have altered financial networks and the way market actors communicate with each other (Davis, 2005). Not only has the speed of trading increased tremendously in the past years (Lewis, 2014), the momentum of information distribution has also accelerated rapidly (e.g., Hope, 2006) and moved more and more online.

    Hence, for this paper we assume that this high-speed information and market environment has partly transferred the interaction among financial actors from the traditional physical trading floor (e.g., Zaloom, 2006) to the online sphere, making the actors more intertwined with each other. Yet so far very little is known about how these financial networks are constituted online, their characteristics, and how their communication affects the stock market. Therefore, this study presents a first attempt to examine how financial networks are constituted on social media (i.e., Twitter) regarding specific events, namely the releases of quarterly earnings (QE) announcements of the 30 companies listed on the Dow Jones Industrial Average (DJI). To do so, this study relies on a multi-method approach, combining network analyses with time series analyses (i.e., vector autoregression). Furthermore, to make sense of the findings from the quantitative analyses, secondary data (press releases, online news media reports) were consulted and interpreted in light of the QE of the DJI stocks. In this vein, this study does not only contribute to social network research focusing on online media, but it also provides informative insights for scholars and practitioners interested in financial communication.

    Theoretical Background

    Financial Networks Economic sociologists have considered financial markets nested in social networks and social relations (e.g., Granovetter, 1985; White, 2002). Up to the late 1990s, trading mainly took place on noisy trading floors where traders were physically present in pits and where they closely watched each other’s risk-taking behavior (e.g., Chicago Board of Trading: Zaloom, 2006). During this time, networks between institutional traders and investors were crucial for information exchange and for staying up to date on current market developments by personally interacting with each other (Knorr Cetina & Preda, 2007). With the rise of new technologies, electronic trading systems and real-time data vendors, trading floors have yet transformed from the social performativity of markets into impersonal, silent and mainly electronically based trading floors.

    While the financial information and data exchange has not disappeared therewith—in contrast, it has tremendously increased with the emergence of algorithm trading and big data processing—personal networks among financial market actors have partly transferred to the online sphere, be it through financial data vendors (e.g., chats within Bloomberg or Reuters terminals) or social networks (e.g., Twitter; cf. Yang, Mo, & Liu, 2015). Yet, the difficulty of defining the financial market as an object of analysis due to its fluidity and dispersion becomes apparent when trying to define financial networks. For example, traders might

  • 143 Financial Networks: Describing Network and Stock Price Dynamics During Quarterly Earnings Announcements

    Abstract

    Focusing on quarterly earnings (QE) announcements of companies listed on the Dow Jones Industrial Average (DJI) index in summer 2016, this study investigates financial networks on Twitter. Network analyses imply that the core of the financial network is mainly constituted of established news media, journalists and professional investors. However, independent and anonymous voices in the financial markets also seem to have access. Furthermore, analyses suggest that attention paid toward reporting companies on Twitter might lead to a downward trend of their stock prices, while reversed effects appear to be mixed. Eventually, a qualitative analysis of secondary data implies that expectations on the market about the QE and the actual reporting and presentation of the numbers by the company and the financial media afterwards might impact the stock market reactions of the reporting company to various extents.

    Introduction

    Financial networks are often considered to be an exclusive, highly educated and elitist group of people. This applies particularly when scholars refer to the closed and self-referential networks in financial centers such as Wall Street in New York, The City in London, or Frankfurt in Germany (Ho, 2009; Norfield, 2016). Ethnographical studies have provided useful insights about the culture of those financial market centers, working cultures among bankers and investors as well as the nature of national and transnational financial networks (e.g., Ho, 2009). However, new technologies such as online trading platforms, online media and social media have altered financial networks and the way market actors communicate with each other (Davis, 2005). Not only has the speed of trading increased tremendously in the past years (Lewis, 2014), the momentum of information distribution has also accelerated rapidly (e.g., Hope, 2006) and moved more and more online.

    Hence, for this paper we assume that this high-speed information and market environment has partly transferred the interaction among financial actors from the traditional physical trading floor (e.g., Zaloom, 2006) to the online sphere, making the actors more intertwined with each other. Yet so far very little is known about how these financial networks are constituted online, their characteristics, and how their communication affects the stock market. Therefore, this study presents a first attempt to examine how financial networks are constituted on social media (i.e., Twitter) regarding specific events, namely the releases of quarterly earnings (QE) announcements of the 30 companies listed on the Dow Jones Industrial Average (DJI). To do so, this study relies on a multi-method approach