Computational finance
نویسندگان
چکیده
Large-scale computing technology has been central to this growth in two ways. First, the markets could not operate without the transaction-processing systems that handle the placing, execution, and settlement of trades. Second, as the markets have grown, new branches of finance have emerged, particularly in the last 20 years, to leverage the volume and liquidity of products and securities sold. These new approaches depend on the availability of sophisticated analysis and computing resources to design and model—preferably in near real time—products and markets. This emerging discipline, which integrates mathematics, economics, and large-scale numeric computation, has come to be known as computational finance. Practitioners of computational finance must deal with computational issues familiar to many CiSE readers. Financial data sets are large, often noisy, and might be incomplete. Valuation models require careful design of numerical algorithms and code implementation. Also, for many products, extensive simulation might be the only practicable pricing method. Added to these issues are various requirements probably more visible in this business setting. Risk management, especially at the corporate level, requires combining forecasts across dozens of products, markets, and future scenarios. Then there is time-to-market. Nowadays, new financial products rapidly become commodities with narrow margins, or, if the market moves, they can lose profitability overnight.
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Edward Tsang has a first degree in Business Administration (Major in Finance) and a PhD in Computer Science. He has broad interest in applied artificial intelligence, in particularly computational finance, heuristic search, constraint satisfaction and scheduling. He is currently a professor in computer science at the University of Essex where he leads the Computational Finance Group and Constra...
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عنوان ژورنال:
- Computing in Science and Engineering
دوره 1 شماره
صفحات -
تاریخ انتشار 1999