Articles liés à Python for Finance
Synopsis
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance.
Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include:
- Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices
- Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression
- Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Yves Hilpisch has 10 years of experience with Python, particularly in the finance space. He founded Visixion - an independent, privately-owned analytics software provider and financial engineering boutique. He works as Managing Director Europe for Continuum Analytics, and lectures on Mathematical Finance at Saarland University in Germany.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Python for Finance: Analyze Big Financial Data
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O'Reilly Media, 2015
ISBN 10 : 1491945281
ISBN 13 : 9781491945285
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Python for Finance
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ISBN 13 : 9781491945285
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ISBN 13 : 9781491945285
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