Noise (economic)

Last updated March 09, 2024

Economic noise, or simply noise, describes a theory of pricing developed by Fischer Black. Black describes noise as the opposite of information: hype, inaccurate ideas, and inaccurate data. His theory states that noise is everywhere in the economy and we can rarely tell the difference between it and information.

Loudon and Della Bitta (1988) refer to noise as “a type of disruption in the communication process” and go further stating that "each state of the communication process is susceptible to (this) message distortion." (As cited in Wu & Newell, 2003). Therefore, we can say that noise is a disruption within the communication process and can be found in all forms within the communication process.

Some examples of noise could be distortion of a television advertisement or interference of a radio broadcast. This therefore would mean that your reception of the information could be misunderstood as your reception of the information has been interfered with, meaning you may not receive the message in the way the sender is implying. Another, and probably more likely, example of noise is whilst an ad break is occurring on television, the reception of the ad has been interrupted by your mobile phone, meaning you do not fully and clearly receive and decode the information the advertisement is trying to deliver.^[1]

What also must be considered when looking at the idea of noise is the understanding that the more the sender and receiver have in common, the less likely it will be for noise to have an effect on the encoding of the message. For example, if the receiver did not understand a symbol or the symbol had a different meaning to the receiver then it did to the sender, this would mean the receiver could encode the message in a different way to how the sender had intended.^[1]

Types of noise

Environmental or External Noise consists of environmental distractions, typically via sound or vision, present while information is being communicated.^[2] An example of this is using a mobile phone whilst watching a television advertisement, as the mobile is within the external environment and could have an impact, as a distraction, on how the receiver decodes the message.

Clutter is another type of noise. Russel and Lane (1996) define clutter as “"non-program material carried during or between shows including commercials, public service announcements, and program promotional spots”^[2] (as cited in Wu & Newell, 2003). Therefore, if the television advertisement had been shown after a public service announcement, the receiver could be distracted, thinking about what was discussed within the announcement, as opposed to being fully focused on the television advertisement.

Internal Noise is the third type of noise to be considered. MacInnis and Jaworski (1989, as cited in Wu & Newell, 2003) and MacInnis, et al. (1991 also cited in Wu & Newell, 2003) imply that the decoding of a message within an advertisement could be affected by the internal noise of the receiver. Internal noise being thoughts and concerns. The relationship between internal noise and the decoding of messages as a receiver does not yet have evidence through market research.^[2] (As cited in Wu & Newell, 2003). Continuing on from this, it is clear that if the audience of an advertisement was focused on a thought or concern in their mind, they would not decode the message within the advertisement in the same way.

Finance

People trade speculatively because they disagree about the future, making different predictions about the fate of companies and commodity prices, among other economic variables. These disagreements stem from the fact that everyone interprets information or data differently and subjectively. But because of the complex nature of the world's markets, not all market data is "information." Much of the daily price fluctuation is due to random change rather than meaningful trends, creating the problem of discerning real information from noise. This problem is what drives trading in a market; if everyone knew all things, then no speculative trades would occur because it is a zero-sum game. In real life, however, trades occur as a kind of bet on what is noise and what is information; generally the more skillful, and technologically advanced, "gambler" wins.

This trade takes place between what Black calls information traders and noise traders , where the former operates based on accurate information and the latter trades based on noise. Unfortunately, there is no way of precisely parsing the noise and information from a data stream or signal, so the so-called noise traders tend to think that they, in fact, trade on information that others in the market simply reject as noise. Thus, methods of parsing noise and information from a signal are becoming increasingly important in the market-place, especially as strategies used by high-tech alternative investment firms, such as some hedge funds.

Business cycles

A particular type of trader Black makes special mention of is the entrepreneur. Like the above-mentioned traders, entrepreneurs have theories about what will happen and what is happening. In this case, though, they have theories as to what people want. When they are correct, there is a little boom; "I make what you want, you make what I want, we trade and we are happy."

But the world has noise and entrepreneurs make mistakes. They make things others don't want. Thus, they don't work as hard, money is wasted and the economy is harmed. When this happens on a massive scale, there is a bust.

Critics argue that this disobeys the law of large numbers; with so many entrepreneurs trying, the aggregate success rate will be constant. (This assumes that producers are more or less independent; critics say they are, proponents say they're more interconnected.)

Econometrics

Black argues that econometrics is filled with it in the forms of unobservables and mis-measurement. No matter how many variables one puts into a model, there are always more to add but can't (ones you can't observe) and the ones you have will always have error. This is how noise manifests in econometrics (as well as poor interpretation of regressions, such as assuming correlation means causation).

Related Research Articles

In information theory and coding theory with applications in computer science and telecommunication, error detection and correction (EDAC) or error control are techniques that enable reliable delivery of digital data over unreliable communication channels. Many communication channels are subject to channel noise, and thus errors may be introduced during transmission from the source to a receiver. Error detection techniques allow detecting such errors, while error correction enables reconstruction of the original data in many cases.

A communication channel refers either to a physical transmission medium such as a wire, or to a logical connection over a multiplexed medium such as a radio channel in telecommunications and computer networking. A channel is used for information transfer of, for example, a digital bit stream, from one or several senders to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.

Within the realm of communication studies, organizational communication is a field of study surrounding all areas of communication and information flow that contribute to the functioning of an organization. Organizational communication is constantly evolving and as a result, the scope of organizations included in this field of research have also shifted over time. Now both traditionally profitable companies, as well as NGO's and non-profit organizations, are points of interest for scholars focused on the field of organizational communication. Organizations are formed and sustained through continuous communication between members of the organization and both internal and external sub-groups who possess shared objectives for the organization. The flow of communication encompasses internal and external stakeholders and can be formal or informal.

<span class="mw-page-title-main">Coding theory</span> Study of the properties of codes and their fitness

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The Financial Information eXchange (FIX) protocol is an electronic communications protocol initiated in 1992 for international real-time exchange of information related to securities transactions and markets. With trillions of dollars traded annually on the NASDAQ alone, financial service entities are employing direct market access (DMA) to increase their speed to financial markets. Managing the delivery of trading applications and keeping latency low increasingly requires an understanding of the FIX protocol.

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Decoding, in semiotics, is the process of interpreting a message sent by an addresser (sender) to an addressee (receiver). The complementary process – creating a message for transmission to an addressee – is called encoding.

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To disseminate, in the field of communication, is to broadcast a message to the public without direct feedback from the audience.

<span class="mw-page-title-main">Active audience theory</span>

Active Audience Theory argues that media audiences do not just receive information passively but are actively involved, often unconsciously, in making sense of the message within their personal and social contexts. Decoding of a media message may therefore be influenced by such things as family background, beliefs, values, culture, interests, education and experiences. Decoding of a message means how well a person is able to effectively receive and understand a message. Active Audience Theory is particularly associated with mass-media usage and is a branch of Stuart Hall's Encoding and Decoding Model.

Models of communication are simplified representations of the process of communication. Most models try to describe both verbal and non-verbal communication and often understand it as an exchange of messages. Their function is to give a compact overview of the complex process of communication. This helps researchers formulate hypotheses, apply communication-related concepts to real-world cases, and test predictions. Despite their usefulness, many models are criticized based on the claim that they are too simple because they leave out essential aspects. The components and their interactions are usually presented in the form of a diagram. Some basic components and interactions reappear in many of the models. They include the idea that a sender encodes information in the form of a message and sends it to a receiver through a channel. The receiver needs to decode the message to understand the initial idea and provides some form of feedback. In both cases, noise may interfere and distort the message.

Aberrant decoding or aberrant reading is a concept used in fields such as communication and media studies, semiotics, and journalism about how messages can be interpreted differently from what was intended by their sender. The concept was proposed by Umberto Eco in an article published first in 1965 in Italian and in 1972 in English.

Lasswell's model of communication is one of the first and most influential models of communication. It was initially published by Harold Lasswell in 1948 and analyzes communication in terms of five basic questions: "Who?", "Says What?", "In What Channel?", "To Whom?", and "With What Effect?". These questions pick out the five fundamental components of the communicative process: the sender, the message, the channel, the receiver, and the effect. Some theorists have raised doubts that the widely used characterization as a model of communication is correct and refer to it instead as "Lasswell's formula", "Lasswell's definition", or "Lasswell's construct". In the beginning, it was conceived specifically for the analysis of mass communication like radio, television, and newspapers. However, it has been applied to various other fields and many theorists understand it as a general model of communication.

The source–message–channel–receiver model is a linear transmission model of communication. It is also referred to as the sender–message–channel–receiver model, the SMCR model, and Berlo's model. It was first published by David Berlo in his 1960 book The Process of Communication. It contains a detailed discussion of the four main components of communication: source, message, channel, and receiver. Source and receiver are usually distinct persons but can also be groups and, in some cases, the same entity acts both as source and receiver. Berlo discusses both verbal and non-verbal communication and sees all forms of communication as attempts by the source to influence the behavior of the receiver. The source tries to achieve this by formulating a communicative intention and encoding it in the form of a message. The message is sent to the receiver using a channel and has to be decoded so they can understand it and react to it. The efficiency or fidelity of communication is defined by the degree to which the reaction of the receiver matches the purpose motivating the source.

Schramm's model of communication is an early and influential model of communication. It was first published by Wilbur Schramm in 1954 and includes innovations over previous models, such as the inclusion of a feedback loop and the discussion of the role of fields of experience. For Schramm, communication is about sharing information or having a common attitude towards signs. His model is based on three basic components: a source, a destination, and a message. The process starts with an idea in the mind of the source. This idea is then encoded into a message using signs and sent to the destination. The destination needs to decode and interpret the signs to reconstruct the original idea. In response, they formulate their own message, encode it, and send it back as a form of feedback. Feedback is a key part of many forms of communication. It can be used to mitigate processes that may undermine successful communication, such as external noise or errors in the phases of encoding and decoding.

References

1 2 Belch, G.E. (2012). Advertising: An Integrated Marketing Communication Perspective (2nd ed. ). North Ryde, NSW: McGraw Hill Australia Pty Limited.
1 2 3 Wu, Bob T.; Newell, Stephen J. (2003-04-01). "The Impact of Noise on Recall of Advertisements". Journal of Marketing Theory and Practice. 11 (2): 56–65. doi:10.1080/10696679.2003.11658496. ISSN 1069-6679. S2CID 168279217.

Noise . Fischer Black. Journal of Finance, 1986.
How Noise Matters to Finance. N. Adriana Knouf. University of Minnesota Press, 2016.

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[:0-1] 1 2 Belch, G.E. (2012). Advertising: An Integrated Marketing Communication Perspective (2nd ed. ). North Ryde, NSW: McGraw Hill Australia Pty Limited.

[:1-2] 1 2 3 Wu, Bob T.; Newell, Stephen J. (2003-04-01). "The Impact of Noise on Recall of Advertisements". Journal of Marketing Theory and Practice. 11 (2): 56–65. doi:10.1080/10696679.2003.11658496. ISSN 1069-6679. S2CID 168279217.

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