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1 - 10 of 16
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Evolution and practice: low-latency distributed applications in finance
Brook A. Queue 13(4): 40-53, 2015. Type: Article
Latency is an often-neglected quality when discussing performance. Often, the focus is on bandwidth or throughput; however, a big airplane loaded with disks can provide high bandwidth but terrible latency. Financial data is smaller tha...
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Sep 14 2015 |
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 Python in practice: create better programs using concurrency, libraries, and patterns
Summerfield M., Addison-Wesley Professional, Upper Saddle River, NJ, 2014. 336 pp. Type: Book (978-0-321905-63-5)
Intermediate-level programming language books are often hard to read. Either they work out a simplified example application, which is of little interest when you’re working on something entirely different, or they try to expl...
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Jan 9 2014 |
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Investment strategies optimization based on a SAX-GA methodology
Canelas A., Neves R., Horta N., Springer Publishing Company, Incorporated, 2012. 93 pp. Type: Book (978-3-642331-09-1)
“History repeats itself.” This old saying leads forecasters to analyze past movements to predict the future. If investors can successfully apply this to financial markets, they ought to get rich quickly. However, fi...
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May 30 2013 |
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Numerical Python for scalable architectures
Kristensen M., Vinter B. PGAS 2010 (Proceedings of the 4th Conference on Partitioned Global Address Space Programming Model, New York, NY, Oct 12-15, 2010) 1-9, 2010. Type: Proceedings
Developing numeric computations using a dynamic language such as Python should lead rapidly to production-quality code. Contrast this with prototyping in a specialized environment such as MATLAB, followed by slow recoding in a lower-le...
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Jan 9 2012 |
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Pro DLR in .NET 4
Wu C., Apress, Berkeley, CA, 2010. 328 pp. Type: Book (978-1-430230-66-3)
Dynamic languages, such as Ruby and Python, are addictive; once you feel comfortable using them, it becomes hard to switch back to static languages. For seasoned programmers, code entities in dynamic languages almost resemble living cr...
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Nov 9 2011 |
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Portfolio and investment risk analysis on global grids
Moreno-Vozmediano R., Nadiminti K., Venugopal S., Alonso-Conde A., Gibbins H., Buyya R. Journal of Computer and System Sciences 73(8): 1164-1175, 2007. Type: Article
Calculating the value-at-risk (the expected profit or loss of a portfolio of financial investments) using the Monte Carlo simulation approach requires calculating the future value of each investment under many thousands of random price...
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Feb 21 2008 |
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MPI for Python
Dalcín L., Paz R., Storti M. Journal of Parallel and Distributed Computing 65(9): 1108-1115, 2005. Type: Article
High-performance parallel computing has the reputation of being difficult to program, partly because the programming languages traditionally used are statically typed, compiled languages, such as Fortran, C, and C++. The de facto stand...
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Feb 14 2007 |
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Monte Carlo grid for financial risk management
Tezuka S., Murata H., Tanaka S., Yumae S. Future Generation Computer Systems 21(5): 811-821, 2005. Type: Article
This easy-to-read paper describes a PC-based grid to speed up the Monte Carlo (many randomized simulations) approach to calculating value-at-risk. Value-at-risk is a standard measure in financial risk management, covering both market r...
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Nov 25 2005 |
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Migrating to simpler distributed applications
Kainz J. Object-oriented programming systems, languages, and applications (Companion to the 19th Annual ACM SIGPLAN Conference on Object-oriented Programming Systems, Languages, and Applications, Vancouver, BC, CANADA, Oct 24-28, 2004) 290-293, 2004. Type: Proceedings
Although many institutions over the past few years have enhanced, refined, and redeveloped their original Internet service offerings, one rarely finds actual experience reports of architectural evolutions from a software perspective. S...
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Dec 9 2004 |
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Vocabulary use in XML standards in the financial market domain
Qin J., Taffet M. Knowledge and Information Systems 6(3): 269-289, 2004. Type: Article
Identifying things by naming them is a major task when learning, using, or designing a language. Traditional linguists rarely studied artificial languages, such as computer languages, database schema, or data interchange languages like...
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Oct 27 2004 |
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