as “"non-program material carried during or between shows including commercials, public service announcements, and program promotional spots” (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. (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