Python for Finance (Paperback)

Yves Hilpisch

Python for Finance (Paperback)

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商品描述

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

商品描述(中文翻譯)

金融業最近以驚人的速度採用Python，一些最大的投資銀行和對沖基金使用它來建立核心交易和風險管理系統。這本實用指南幫助開發人員和量化分析師入門Python，並引導您了解使用Python進行量化金融的最重要方面。

作者Yves Hilpisch通過實際示例展示了如何基於大型、現實案例研究開發基於蒙特卡洛模擬的衍生品和風險分析的完整框架。本書的大部分內容使用互動式的IPython Notebooks，涵蓋的主題包括：

- 基礎知識：Python數據結構、NumPy數組處理、使用pandas進行時間序列分析、使用matplotlib進行可視化、使用PyTables進行高性能I/O操作、處理日期/時間信息以及選擇的最佳實踐方法。
- 金融主題：使用NumPy、SciPy和SymPy的數學技術，如回歸和優化；用於蒙特卡洛模擬、風險價值和信用價值風險計算的隨機過程；用於正態性測試、均值-方差組合優化、主成分分析（PCA）和貝葉斯回歸的統計學。
- 特殊主題：金融算法的高性能Python，如向量化和並行化；將Python與Excel集成；基於Web技術構建金融應用程序。

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