In neoclassical models, prices are determined by objective fundamentals and rational market actors supplied with accurate market information will drive prices to their correct equilibrium point in line with those fundamentals. The preceding discussion of communicative/ informational reflexivity in financial markets underlines why this account is not sustainable. Implicit/ performative reflexivity means that the concepts, models and schemata used by investors to understand market phenomena shape their trading activity and thus help constitute the object of their own codifications. Thus price movements can be driven by investor responses to price movements, especially in securities where ‘momentum’ or ‘noise’ traders try to predict fluctuations based on investor psychology.
The search of a trading edge in a environment where virtually all the core market information is symmetrically distributed in real-time motivates the identification of new models/ frames to take advantage of other information. Investors must work out what factors are currently shaping the trading decisions of other market actors. This may give rise to herding behaviour, either through trading on price momentum or through following consensus opinion, analyst recommendations, or just the latest rumour circulating online. There are certainly empirical examples that suggest the objectivity of financial news may sometimes be irrelevant if investors can anticipate that the aggregate trading patterns will still move prices in response to it. For example, a report in Business Week (24 April, 2000) identified a concern about increasing investor reliance on often inaccurate or misleading information distributed via the internet from dubious sources. In one case, a Californian tree pruner was prosecuted by the SEC for distributing dubious stock recommendations under the name ‘Independent Financial Reports’. His advice was picked up by a on-line subscription financial news service, Business Wire, and was even cited on Bloomberg. If market analyses from amateurs or vested interests are as potentially influential as professional experts, then it seems curious that investment institutions pay significant sums for analyst reports. Henwood duly offers an explanation:
‘Why would people pay $100,000 a year for such bad journalism?…Because it moves markets when it spreads beyond the circle of subscribers; if you hear it first, you can make money on it whether it's true or not.’ (1998 p.104). In other words, the truth value of financial information may
depend not on correspondence with any objective economic conditions, but on investors’ inter- subjective confidence that other actors will take notice of the information and act upon it as if it were true.
Despite the evidence that financial media can trigger price movements, these are not simple causal effects, and involve quite complex institutional and cognitive processes (see Sant & Zaman, 1996; Vickers & Weiss, 2000; Busse & Green 2002; Davis, 2005, 2006a; Frieder & Zittrain, 2006). Information is interpreted in the context of prevailing market expectations of future price movements which feed back into current valuations and form the basis of current market prices. As well-known financial speculator, George Soros (1994, p.29) observes, ‘Nowhere is the role of expectations
more clearly visible than in financial markets. Buy and sell decisions are based on expectations about future prices, and future prices, in turn, are contingent on present buy and sell decisions.’
Kurtz (2000) and Golding (2003) likewise note the importance of expectations shaping the market response to news. Although analyst predictions are publicly reported in the financial media unofficial ‘whisper numbers’ also circulate through the market grapevine and provide institutional traders with an indication of the price/earning estimates set the institutional thresholds around which prices will
actually move108: This raises an important issue about the interplay between public news media and private channels. Given that the significance of financial media reports depends on their interpretation in respect to prevailing expectations, and that the institutional biases of public analyst statements are well recognised by institutional investors, then explaining financial market behaviour needs to explore the other financial networks/channels/information sources through which those expectations are formed. Even if financial news media can trigger trading, other media/sources may play a more fundamental role in helping institutional investors develop an informed view of other market actors positions and predispositions.
Financial markets are evidently sensitive to signals about financial epiphenomena that their own processes endogenously generate. However, not all these signals will be communicated through news media. As Wark (1994) suggests, the emergence of a media-saturated space of economic flows means it has become problematic to discern what is information and what is noise. It might be contended that this depends less on the external reference to market conditions and more on the variables currently being incorporated into trading models/ schemata. Contingent or game reflexivity suggests that any number of currently-peripheral variables can become salient to investment decisions at different times. Rumours about the activities of other investment institutions and predictions of market commentators in the media are all routinely monitored and analysed for their implications. Analysts specialising in various markets are employed to collate, filter, condense, prioritise and interpret all this contingent information into a form readily intelligible to investors. The relevance and significance of different types of information may vary depending on the type of institution and market sector.
The implication here is that the trading schemata of investors evolves and that a variety of variables could become price-sensitive if they become incorporated into those schemata (see Clark et al., 2005; Knorr-Cetina, 2005). As Beunza & Stark (2003, 2004) point out, despite the quantity of information available through various financial media, its symmetrical distribution across the market means that any trading advantage must come from identifying, prioritising and interpreting the information that is most likely to move the market; ‘the challenge for traders is not to be faster,
higher, stronger- as if the problem of the volume of data could be solved by gathering yet more- but in selecting what counts and making sense of the selection’ (2004, p.369). Arnoldi (2006) concurs,
pointing out that in information-saturated trading rooms, ‘What is lacking is indeed, not information,
what is lacking is a frame by which some information can be singled out as discrete and tangible information, leaving the rest behind as mere background and noise’ (p.390). In other words, despite
(or perhaps because of) the real-time information flows on the trading screens, traders need meta-
information to tell them what kind of data needs to be monitored in order to anticipate price
movements. This would indicate that trading frames evolve and that their validity depends on their correspondence with the prevailing intersubjective codifications demarcating which variables are currently salient. As George Soros (1994) acknowledges, the evidence that investors respond to perceptions/expectations of other investors’ aggregate market behaviour means that the neoclassical assumption that financial market prices have a natural equilibrium based on objective fundamentals cannot be sustained; ‘Instead of a determinate result, we have an interplay in which
both the situation and the participants’ views are dependent variables so that an initial change precipitates further changes both in the situation and in the participants’ views. I call this interaction “reflexivity”.’ (1994, p.42 109).
108 As Kurtz remarks: ‘Everything revolved around expectations; the good news was already built into the stock
price. Analysts always set the next target, and there was intense pressure to ‘make the number’, regardless of how high the bar had been raised. If the company fell short, Wall Street devalued the stock.’ (2000, p.70). And furthermore; ‘The brokerage houses would buy up a company’s stock, publish lowball estimates for the next quarterly earnings and everyone would act pleasantly surprised when the company ‘beat the Street’ by a penny or two, looking for all the world like it was on a roll. And the media played along with the game, relentlessly reporting the artificially low estimates and then breathlessly touting the better-than-expected results.’ (2000, p.227-228).
109
More specifically, Soros argues that the financial markets exhibit a reflexive process whereby prices are determined by two factors, ‘prevailing bias’ and ‘underlying trend’ (1994, p.50). The former refers to observable patterns of aggregate market perceptions manifested in the common reference point of shifting prices. The latter refers, rather nebulously, to unobserved/ subliminal factors which shape market actors’ perceptions of market events. Both are, in turn, shaped by price movements, and Soros uses these concepts to develop a
Soros goes on to explain that:
‘Stock market valuations have a direct way of influencing underlying values: through the issue and repurchase of shares and options and through corporate transactions of all kinds- mergers, acquisitions, going public, going private, and so on. There are also more subtle ways in which stock prices may influence the standing of a company: credit rating, consumer acceptance, management credibility, etc. […] I contend that market valuations are always distorted; moreover- and this is the crucial departure from equilibrium theory- the distortions can affect underlying values. Stock prices are not merely passive reflections; they are active ingredients in a process in which both stock prices and the fortunes of companies whose stock are traded are determined.’ (1994, p.48-49).
The relationship between the producers/ distributors of economic information and those who use it to make trading/ investment decisions is a complex one, often involving contradictory imperatives. For both analysts and traders, markets are embodied and mediated through a variety of channels and electronic screen displays (see Knorr Cetina & Bruegger, 2001, 2002a). These may include, in varying priority, public news from mass media, financial wire-services and real-time market updates, reports from specialist market analysts (especially ratings agencies), advice and tips from colleagues and insider sources, and, of course, the monitoring of other investors' market activity (Henwood, 1998; Rothkopf, 1999). Smart (1999) points out that a key role of financial analysts is to render market data intelligible by articulating narratives that are meaningful in terms of their institution’s operational schemata, thereby providing a frame to help orientate trading decisions. These translations of data into meaningful discourses is extends beyond passive de-coding. There is an active, performative aspect through which the codifications become intersubjective. This is significant not only within the institution but also on a broader market level when analysts comment publicly in the media. Even if analysts’ opinions are not accepted uncritically, they may act as primary definers in imposing a frame of reference around which the perceptions of other market actors will tend to crystallise. The role of analysts extends beyond basic buy/hold/sell recommendations. Media coverage is often desired by analysts because of the visibility and credibility this confers upon their account or ‘story’ of how and why market events occurred. Particularly where markets conditions are complex or uncertain, analyst frames may be contested. Having the market pay attention to an institution’s preferred frame/story can therefore be an important factor in ensuring the aggregate reaction is not unfavourable to its interests.
Beunza & Stark’s (2003, 2004, 2005a, 2005b) detailed analyses of social relations and technologies deployed in financial institutions emphasise the trading-floor as the principal node of financial agency. Although exchanges remain an important point of interaction and reference point in terms of prices and indexes it is through the agency manifested on the actual trading-floor that the trajectory of global capital flows are largely determined, particularly since electronic brokerage systems largely replaced pit trading and reterritorialised investment through interlinked but spatially remote terminals (see also Knorr Cetina & Bruegger, 2002a, 2002b). Of particular interest to Beunza and Stark is the way in which traders across different financial sub-markets (bonds, stocks, currencies etc.) engage with each other in ‘heterarchical’ formations to share knowledge and actively construct the models and schemata and decision-making frames that will confer a trading advantage (see also Knorr-Cetina & Bruegger’s [2002] conception of financial ‘conversations’). Beunza & Stark (2004, 2005a) point out that calculative frame-making is key role of analysts in investment institutions. This is particularly important where securities need to be valued in volatile market contexts where ambiguity/ uncertainty is high, because the calculative frames shape what kinds of information are coded as significant and what data is excluded as noise (see Tversky &