From making visible to hiding. Visual representations of financial markets as tools of manipulation and active and living agents

Abstract

This article shows that visual representations of financial markets not only make them visible, i.e. present and reveal certain important financial information such as the size and distribution of demand and supply, the quantity, type and intentions of sellers and buyers, trends and patterns in price movements, or the depth, liquidity and sentiment of the market, but also hide what they are supposed to reveal and make visible. What is important, they do this not only because of the ways of their production; not only because of pitfalls and errors inherent in them; not only because of framing processes they are subjected to, but also because of their interactive nature that allows financial agents to manipulate them. This fact, and above all its possibility, carries with itself important consequences for the role that the visual representations play in the functioning of capital markets. Namely, it causes that these representations, regardless of other factors, themselves become a source of uncertainty in these markets. As such, they are therefore not so much neutral and passive representations of financial exchange as rather tools for manipulation on the one hand and active and living agents on the other.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Notes

[1] When choosing these and not other visual representations of financial markets, I chose first and foremost those that I usually used during investing on the mentioned markets. Such a choice, having an individual and subjective character, causes that examples of visual representations used here are not entirely representative of the set of visual representations of financial markets. In other words, they are not the ones that are used by all investors; there are also other visual representations of capital markets utilised by financial agents on the discussed markets. Moreover, there is also one more reason why the selected examples are not representative. Namely, this is because brokers and companies that provide visual instrumentation for financial trading, limit access to them and their use to situations related solely to trading in financial assets. As a result not all forms of visual representations of capital markets could be exploited in this article, but only those without legal problems.

[2] Market depth refers to the overall level and breadth of open orders. Typically, the more buy and sell orders that exist, the greater the depth of the market (https://www.investopedia.com/terms/m/marketdepth.asp).

[3] Market liquidity refers to the extent to which a market, such as a country’s stock market or a city’s real estate market, allows assets to be bought and sold at stable, transparent prices (https://www.investopedia.com/terms/l/liquidity.asp).

[4] Market sentiment refers to the overall attitude of investors towards a particular security or financial market. It is the feeling or tone of a market (https://www.investopedia.com/terms/m/marketsentiment.asp).

[5] The exception may be Beunza and Stark (2004, 392) who emphasise that graphic representations on traders’ screens also obscure.

[6] The first of these three disciplines, i.e. social studies of finance, anthropology of finance, economic and cultural geography, are sometimes referred to as ‘cultural economy of finance’ (see Pryke and Du Gay 2007).

[7] Grounding this research in the author’s own experiences and observations as the so-called individual investor causes that this research mainly concerns those visual representations of financial markets that are available to the ‘mass’ investor. As such, they may differ significantly from those visual representations of capital markets that are available to the ‘institutional’ investor. The one with greater technical and financial capabilities can afford much more advanced forms of these representations (for examples of such more advanced representations see e.g. Pryke 2010).

[8] In detail, this means that gathering research data is based on auto-observation, it also means that materials used during the conducted study are those of author’s own ones and that findings are an effect of careful auto-reflection with a constant comparison of its outcomes with the existing literature.

[9] At the most general level associated with the way visual representations exist, two categories are distinguished, namely internal representations and external representations (Gilbert 2010, 5). On the other hand, when one considers their physical structure, there are eleven of these categories, i.e. graphs, tables, graphical tables, time charts, networks, structure diagrams, process diagrams, maps, cartograms, icons, and pictures (Lohse et al. 1994). To this should be added that each of the categories just mentioned is further divided into other kinds and types, and so e.g. graphs are further divided into rectilinear cartesian coordinate graphs, polar coordinate graphs, bar graphs, line graphs, matrix diagrams, trilinear charts, response surfaces, topographic charts, and conversion scales (Rankin 1990). All this shows that visual representations form a very large and diverse family. Not only are they divided into many categories, but these categories are further divided into other kinds and types, which together gives a large number of forms in which visual representations appear. Of course, not all kinds and types are equally present in the world of electronic financial markets. Based on the research of Ko et al. (2016, 599) on visual analysis approaches for financial data, the most popular ones can be identified. Such representations are primarily graphs and candlestick charts.

[10] The fact that visual representations of financial markets allow us to recognise the eyes and faces of other market participants does not mean, of course, that this recognition cannot be wrong. Indeed, it can be. This is because the market participants can hide their true identity and intentions behind visual representations of capital markets. This possibility is given to them by the interactive nature of the representations in question, thanks to which they can place their orders on the market in various numerical configurations, thus misleading other investors.

[11] ‘Technical analysts’ is one of the groups of economic actors on financial markets. What distinguishes them from other groups, such as ‘arbitrageurs’ or ‘fundamental analysts’ is, first and foremost, that the main tool on which they base their investment choices and decisions is the financial graph which shows the prices of a financial instrument in a historical perspective. In short, they do not need other tools or other information but only the historical prices of financial instruments in the form of a financial chart (for more on ‘technical analysts’ see e.g. Mayall 2006; Roscoe and Howorth 2009).

Additional information

Notes on contributors

Marcin Marian Krawczyk

Marcin Marian Krawczyk is an Assistant Professor at Maria Curie-Sklodowska University in Lublin, Poland. His research focuses primarily on the meaning of the aesthetic in the financial world. He is the author of “Aesthetics and Finance. On the Role and Place of the Aesthetic On the Electronic Financial Markets” (in Polish).