Computational finance

Computational finance or financial engineering is a cross-disciplinary field which relies on mathematical finance, numerical methods and computer simulations to make trading, hedging and investment decisions, as well as facilitating the risk management of those decisions. Utilising various methods, practitioners of computational finance aim to precisely determine the financial risk that certain financial instruments create.

Contents

History

Generally, individuals who fill positions in computational finance are known as “quants”, referring to the quantitative skills necessary to perform the job. Specifically, knowledge of the C++ programming language, as well as of the mathematical subfields of: stochastic calculus, multivariate calculus, linear algebra, differential equations, probability theory and statistical inference are often entry level requisites for such a position. C++ has become the dominant language for two main reasons: the computationally intensive nature of many algorithms, and the focus on libraries rather than applications.

Computational finance was traditionally populated by Ph.Ds in finance, physics and mathematics who moved into the field from more pure, academic backgrounds (either directly from graduate school, or after teaching or research). However, as the actual use of computers has become essential to rapidly carrying out computational finance decisions, a background in computer programming has become useful, and hence many computer programmers enter the field either from Ph.D. programs or from other fields of software engineering. Practitioners of computational finance have come from the fields of signal processing and computational fluid dynamics.

Masters level degree holders are also increasingly making their presence felt as more terminal programs become available at the leading schools. Today, all full service institutional finance firms employ computational finance professionals in their banking and finance operations (as opposed to being ancillary information technology specialists), while there are many other boutique firms ranging from 20 or fewer employees to several thousand that specialize in quantitative trading alone. JPMorgan Chase & Co. was one of the first firms to create a large derivatives business and employ computational finance (including through the formation of RiskMetrics), while D. E. Shaw & Co. is probably the oldest and largest quant fund (Citadel Investment Group is a major rival).

Areas of application

Areas where computational finance techniques are employed include:

Major contributors

Some major contributors to computational finance include:


See also

External links


v • d • e
General areas of finance
v • d • e
Major fields of Technology
Applied science
Information
Industry
Military
Domestic
Engineering
Health and safety
Transport

Wikipedia content modification information:

  • This page was last modified on 4 December 2008, at 14:03.

Wikipedia Authorship and Review

Wikipedia content provided here is not reviewed directly by PediaView.com. Wikipedia content is authored by an open community of volunteers and is not produced by or in any way affiliated with PediaView.com.

Wikipedia Usage Guidelines

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article on "Computational finance".

The URL for this specific entry is:

All Wikipedia text is available under the terms of the GNU Free Documentation License. (See Copyrights for details). Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc.