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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. Noise has two broad implications. *It allows speculative trading to occur (see below). *It is indicative of market inefficiency. == 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 gain. 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. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Noise (economic)」の詳細全文を読む スポンサード リンク
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