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Financial signal processing : ウィキペディア英語版 | Financial signal processing
Financial signal processing is a branch of signal processing technologies which applies to financial signals. They are often used by quantitative investors to make best estimation of the movement of equity prices, such as stock prices, options prices, or other types of derivatives. == History == The early history of financial signal processing can be traced back to Isaac Newton. Newton lost money in the famous South Sea Company investment bubble. The modern start of financial signal processing is often credited to Claude Shannon. Shannon was the inventor of modern communication theory. He discovered the capacity of a communication channel by analyzing entropy of information. For a long time, financial signal processing technologies have been used by different hedge funds, such as Jim Simon's Renaissance Technologies. However, hedge funds usually do not reveal their trade secrets. Some early research results in this area are summarized by R.H. Tütüncü and M. Koenig〔Tütüncü, Reha H. and Koenig, Mark, "Robust asset allocation", Annals of Operations Research, vol. 132, pp. 157–187, 2004〕 and by T.M. Cover, J.A. Thomas.〔Cover, Thomas M. and Thomas, Joy A., Elements of Information Theory, 2nd Edition, Wiley, 2006〕 In 2011, IEEE Signal Processing Society called for a Special Issue on Signal Processing Methods in Finance and Electronic Trading.〔http://www.signalprocessingsociety.org/uploads/special_issues_deadlines/sp_finance.pdf〕 A.N. Akansu and M.U. Torun have published the book in financial signal processing entitled ''A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading.''〔Akansu, Ali N.; Torun, Mustafa U. (2015), A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading, Boston, MA: Academic Press, ISBN 978-0-12-801561-2〕
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