Financial signal processing

{{More citations needed|date=August 2012}}

Financial signal processing is a branch of signal processing technologies which applies to signals within financial markets. They are often used by quantitative analysts to make best estimation of the movement of financial markets, such as stock prices, options prices, or other types of derivatives.

History

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.{{cite web |url=http://www.fisig.com/fisig_papers/index.htm |title=Connections Between Financial Signal Processing, Entropy, and Superior Investment Returns, James Simon, Jim Simon, Renaissance Technologies |publisher=Fisig.com |date= |accessdate=2013-06-16 |archive-url=https://web.archive.org/web/20130518074712/http://www.fisig.com/fisig_papers/index.htm |archive-date=2013-05-18 |url-status=dead }}

For a long time, financial signal processing technologies have been used by different hedge funds, such as Jim Simons'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. KoenigTütüncü, 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 2015, A.N. Akansu and M.U. Torun published A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading.Akansu, Ali N.; Torun, Mustafa U., A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading, Boston, MA: Academic Press, 2015 {{ISBN|978-0-12-801561-2}} An edited volume with the title Financial Signal Processing and Machine Learning was published the following year.Akansu, Ali N.; Kulkarni, Sanjeev R.; Malioutov, Dmitry M., Eds., Financial Signal Processing and Machine Learning, Hoboken, NJ: Wiley-IEEE Press, 2016 {{ISBN|978-1-118-74567-0}}

The first IEEE International Conference on Acoustics, Speech, and Signal Processing session on Financial Signal Processing was organized at ICASSP 2011 in Prague, Czech Republic.Special Session, Signal Processing Methods for Finance Applications, [https://researchr.org/publication/icassp-2011 Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011], May 22–27, 2011, Prague Congress Center, Prague, Czech Republic. There were two special issues of IEEE Journal of Selected Topics in Signal Processing published on Signal Processing Methods in Finance and Electronic Trading in 2012,{{cite web|url=https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6239656|title=IEEE Xplore: IEEE Journal of Selected Topics in Signal Processing - (Volume 6 Issue 4)|website=IEEE}} and on Financial Signal Processing and Machine Learning for Electronic Trading in 2016{{cite web|url=https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=7542489&punumber=4200690|title=IEEE Xplore: IEEE Journal of Selected Topics in Signal Processing - (Volume 10 Issue 6)|website=IEEE}} in addition to the special section on Signal Processing for Financial Applications in IEEE Signal Processing Magazine appeared in 2011.{{cite web|url=https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=5999554|title=IEEE Xplore: IEEE Signal Processing Magazine - (Volume 28 Issue 5)|website=IEEE}}

Financial signal processing in academia

Recently, a new research group in Imperial College London has been formed which focuses on Financial Signal Processing as part of the Communication and Signal Processing Group of the Electrical and Electronic Engineering department,{{cite web|url=http://www.fsplab.com/|title=Financial Signal Processing Lab|date= |access-date=2014-02-17}} led by Anthony G. Constantinides. In June 2014, the group started a collaboration with the Schroders Multi-Asset Investments and Portfolio Solutions (MAPS) team on multi-asset study.{{cite web|url=http://www.schroders.com/global/media-centre/news-releases?id=Schroders%20and%20experts%20from%20Imperial%20College%20London%20collaborate%20on%20Multi-Asset%20study|title=Schroders Press Release|date= |access-date=2014-07-15}}

Other research groups working on the financial signal processing include the Convex Research Group of Prof. Daniel Palomar{{Cite journal|last1=Feng|first1=Yiyong|last2=Palomar|first2=Daniel P.|date=2016-08-11|title=A Signal Processing Perspective on Financial Engineering|url=https://www.nowpublishers.com/article/Details/SIG-072|journal=Foundations and Trends in Signal Processing|language=English|volume=9|issue=1–2|pages=1–231|doi=10.1561/2000000072|issn=1932-8346|url-access=subscription}} and the Signal Processing and Computational Biology Group led by Prof. Matthew R. McKay at the Hong Kong University of Science and Technology{{cite web|url=https://www.danielppalomar.com/|title=Convex Research Group|date=|access-date=2020-03-12}} and Stanford University Convex Optimization Group led by Prof. Stephen Boyd at the Stanford University.{{cite web|url=https://web.stanford.edu/~boyd/index.html|title=Stanford University Convex Optimization Group|last=|first=|date=|website=|access-date=2020-03-12}} There are also open source libraries available for index tracking and portfolio optimization.{{cite web|url=https://github.com/dppalomar|title=Financial signal processing libraries|last=|first=|date=|website=GitHub|access-date=2020-03-12}}{{Cite web|url=http://cvxportfolio.org/|title=Stanford University Convex Optimization Group|last=|first=|date=|website=GitHub|language=en|access-date=2020-03-12}}

Financial signal processing in industry

  • Vivienne Investissement: multifractality for asset price, covariance estimation for asset allocation;{{Cite web|url=http://www.vivienne-investissement.com/EN/Research.php?p=B|title=VIVIENNE INVESTISSEMENT|website=www.vivienne-investissement.com|access-date=2020-03-12}}
  • NM FinTech;{{Cite web|url=https://nmfin.tech/|title=NM FinTech {{!}} Quantitative Models for Wealth Management|language=en-US|access-date=2020-03-12}}
  • Sanostro: On the back of a lack of market place for signals, Sanostro AG, headquartered in Switzerland, created the first B2B signal market place providing signals on all liquid assets. Sanostro allows signal providers (hedge funds, quant teams of institutional investors, etc.) to provide their signals, standardize them, so that their track record can be audited. The signals themselves can then be re-combined for B2B purposes, like dynamic FX hedging, tactical asset allocation, equity upside capture;{{Cite web|url=https://www.sanostro.com/|title=www.sanostro.com {{!}} Alpha-as-a-Service|language=en-US|access-date=2020-05-04}}
  • SkyBlue FS: Their SkyBlue OpenSignals product offers AI-powered signals and trade setups that can be accessed via API service.{{Cite web |title=SkyBlue FinTech |url=https://skybluecap-sg.com |url-status=live |access-date=7 January 2025 |website=SkyBlue FinTech Solutions}}

See also

References