Abstract
Despite intensive study, a comprehensive understanding of the structure of capital market trading data remains elusive. The one known application of audification to market price data reported in 1990 that it was difficult to interpret the results, probably because the market does not resonate according to acoustic laws. This chapter illustrates some techniques for transforming data so it does resonate; so audification may be used as a means of identifying auto-correlation in trading- and similar-datasets. Some experiments to test the veracity of this process are described in detail, along with the computer code used to produce them. Also reported are some experiments in which the data is sonified using a homomorphic modulation technique . The results obtained indicate that the technique may have a wider application to other similarly structured time-series datasets .
The flexibility of money, as with so many of its qualities, is most clearly and emphatically expressed in the stock exchange, in which the money economy is crystallized as an independent structure just as political organization is crystallized in the state. The fluctuations on exchange prices frequently indicate subjective-psychological motivations, which, in their crudeness and independent movements, are totally out of proportion in relation to objective factors (Simmel 1979, 326).
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Notes
- 1.
The nomenclatures used for various kinds of markets is somewhat convoluted and are often misused. A stock market is for trading equities, namely ownership interests in companies. A financial market is an institutional structure or mechanism for creating or exchanging financial assets, namely those that are real such as land, buildings, equipment, patents. The term capital market is used generally to refer to markets for stocks, bonds, derivatives and other investments and it is this term we adopt here, or the less formal The Market. Both are generic terms signifying all regulated exchanges and their activities.
- 2.
The bottom chart. The top chart is derived from a random-walk model.
- 3.
The term ‘Quant’ is used in the field to identify those who quantitatively analyze capital market data, or use such analysis to construct investment portfolios with a specific risk profile. See Sect. 2.2.
- 4.
Brownian motion is an independent (that is uncorrelated) random walk in which the size and direction of the next (price) move is independent of the previous move(s). A statistical analysis of time series data is concerned with the distribution of values without taking into account their sequence in time.
- 5.
See Chap. 3, Table 3.1 for a description of different ways of acquiring knowledge.
- 6.
It is somewhat ironic that, in an enterprise that relies on ‘clean’ data, financial data often requires considerable ‘washing’ before its sonification can be undertaken. This situation is exacerbated by the trait that, with datasets over a certain size, the use of metadata tagging is uncommon, principally because it significantly increases the overall size of the dataset, even though the omission increases the likelihood of error. In any event, any cleaning has to be undertaken algorithmically and so it is expedient to have the tools for doing so integrated with the sonification software being used.
- 7.
The term ‘volume’ is used throughout to mean ‘trading volume’ not a psychoacoustic parameter.
- 8.
See Chap. 2 for a discussion of common sonification techniques.
- 9.
Market depth is a term used to denote the structure of potential buy and sell orders clustered around the most recently traded price. Traders are able to withdraw or restructure their orders at any time before they are “met” by an order from a trader taking the other side of the trade.
- 10.
Similar to that used by Xenakis for his ST series of compositions (Xenakis 1971, 136–43).
- 11.
The XAO is the broad Australian market indicator, a composite of the 500 largest companies listed on the exchange, weighted by capitalization. Contextual details are available at https://www.asx.com.au/products/indices.htm.
- 12.
- 13.
All Audio Examples referred to can be directly downloaded from the book’s online repository.
- 14.
For a more detailed description of the technique, see Chap. 2, Sect. 2.2.2.3.
- 15.
MacCsound is no longer available. However, it would be possible to write a similar controller in Sonipy—using the minimal Python tkinter module, for example.
- 16.
A well-commented version of the script developed for these experiments, along with the audio examples, is available for download from the book’s online repository.
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Worrall, D. (2019). Audification Experiments: Market Data Correlation. In: Sonification Design. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-030-01497-1_7
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