Python for Finance Analyze Big Financial Data

Download Now

Python for Finance: Analyze Big Financial Data by
English | December 10, 2014 | ISBN: 1491945281 | ASIN: B00QUBHNBW | 596 Pages | EPUB/MOBI/AZW3/PDF (Converted) | 35 MB

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 matDescriptionlib, 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.

Direct Download

Tags: Financial, Analyze, Finance, Python

Python for Finance Analyze Big Financial Data from rapidshare mediafire megaupload hotfile, Python for Finance Analyze Big Financial Data via torrent or emule, full free Python for Finance Analyze Big Financial Data, Python for Finance Analyze Big Financial Data rar zip password or anything related.


Add Comments:
Enter Code: *