Financial Media

This article investigates the impact that the initial financialization of the Wireless Telegraph & Signal Company (Marconi) had upon its core business model, its relationship with its workers, government, and the bourgeoning investor class (1897–1905). Drawing upon primary sources from the Marconi corporate archives at the University of Oxford, the article investigates how the company used the new financial disclosure requirements of the day to deploy a compelling publicity campaign for wireless communications.

The headlines texts have been deconstructed into different narrative techniques with different rhetorical or ideological purposes. In this chapter, we explore how these techniques are drawn upon in reflecting and discussing the ‘big’ phenomenon of China’s economic globalization, which is a complex and multifaceted process. The chapter also examines how the media determine whether and to what extent a particular frame of the discourse is selected to represent the process of globalization; and how the media make judgments on these discourses to create and articulate a certain ideology (i.e., arguably the neo-liberal discourse). A close investigation of how the sample articles are framed could provide a useful perspective to answer these questions.

PLEASE NOTE: this paper is available for free from the link below. It appears in a brilliant special issue of Ctrl-Z open access journal edited by Robert Briggs
ABSTRACT: Working on the same principles as the phonograph, but reading tremblings of the ground rather than of the air, scratching out in real time invisible actions in visible form, the seismograph betrays its origins in the mechanical era. Today a second, more arithmetic form of data visualisation diagrams a numerical data set such as the one derived from instrument systems in place to monitor the health of the Animas River. A third form, financial visualisation software in commodity markets, not only gives direct accounts of geology (reserves), human interventions in them (extraction) and simulations of their likely use (futures) but actively produce those futures by fixing future trading prices. These three geomedia—vectoral analogues, numerical translations, and direct data—have significantly different means for handling time, with implications for the increasingly punctual subjects they presume, to the extent that it is not at all clear that the subjectivities they address, enable or create are human.

In media and communication studies, only a handful of literatures have grappled the special characteristics of financial media, and its relationship with economic development and social changes. Therefore, the concept of financial media needs to be identified in the contexts of history (1.1.1), media production (1.1.2) and institutionalism (1.1.3). More specifically, the target cases—Economist and Caijing—will be spotted to justify their validity and significance for analyzing the neo-liberal discourses constructed by financial media. To briefly sum up, the first chapter seeks answers to three sets of questions: (1) What is financial media? (2) What are the Economist and Caijing? (3) How are they selected? And why are they comparable?

Compared to other domains of media discourse, economic-financial news contain a considerable amount of speech acts regarding future events, in particular predictions. This can be explained by their specific institutional context, financial markets, where investors constantly seek to single out gain opportunities and to correctly assess their risk. One of the crucial factors making economic-financial predictions worthy of being considered in investment decisions is argumentation, in particular the extent to which the predicted proposition follows from a plausible and acceptable reasoning. Starting from a corpus of 50 articles of the Italian economic-financial press, we consider the inferential dimension of prediction-oriented arguments, focusing on thelocus, i.e. the ontological relation on which the connection between the argument(s) and the predictive conclusion rests. All predictions found in the corpus were manually annotated with the softwareUAM Corpus Tool. For each of them we ...