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The design and implementation of visualised agricultural commodity futures techniques analysis software

The design and implementation of visualised agricultural commodity futures techniques analysis... The agricultural commodity futures analysis software in the mainstream market can only contribute to 'qualitative investment', with poor support for 'quantitative trading', in urgent need of improvement. In view of above-mentioned state, the thesis introduces the visualised agricultural commodity futures techniques analysis software based on .NET platform. The software adopts the WPF framework in VS2015 for development, IronPython for drawing graphics and Windows file system for data storage. The software has such functions as visualised data graphics display, data updating and classification retrieval. Such features of the software as lightweight, the ability to collect a large number of historical data, offline use and the ability to build mathematical models can not only meet the needs of ordinary users, but also bring good news to the professional analysts. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Systemic Studies Inderscience Publishers

The design and implementation of visualised agricultural commodity futures techniques analysis software

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1751-0589
eISSN
1751-0597
DOI
10.1504/IJASS.2017.089940
Publisher site
See Article on Publisher Site

Abstract

The agricultural commodity futures analysis software in the mainstream market can only contribute to 'qualitative investment', with poor support for 'quantitative trading', in urgent need of improvement. In view of above-mentioned state, the thesis introduces the visualised agricultural commodity futures techniques analysis software based on .NET platform. The software adopts the WPF framework in VS2015 for development, IronPython for drawing graphics and Windows file system for data storage. The software has such functions as visualised data graphics display, data updating and classification retrieval. Such features of the software as lightweight, the ability to collect a large number of historical data, offline use and the ability to build mathematical models can not only meet the needs of ordinary users, but also bring good news to the professional analysts.

Journal

International Journal of Applied Systemic StudiesInderscience Publishers

Published: Jan 1, 2017

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