Artificial Intelligence in Finance: A Python-Based Guide

Hilpisch, Yves

Artificial Intelligence in Finance: A Python-Based Guide

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商品描述

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading.

Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book.

In five parts, this guide helps you:

  • Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI)
  • Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice
  • Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets
  • Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies
  • Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

商品描述(中文翻譯)

AI和機器學習的廣泛應用正在革命化當今許多行業。一旦這些技術與歷史和實時金融數據的程序可用性相結合，金融行業也將從根本上發生變化。通過這本實用書，您將學習如何使用AI和機器學習在金融市場中發現統計效率低下的地方，並通過算法交易來利用它們。

作者Yves Hilpisch向金融和數據科學的從業人員、學生和學者展示了將機器學習和深度學習算法應用於金融的實用方法。通過大量獨立的Python示例，您將能夠複製書中呈現的所有結果和圖表。

在這本指南的五個部分中，您將學到以下內容：

- 學習AI的核心概念和算法，包括通往人工通用智能（AGI）和超級智能（SI）的最新突破
- 理解數據驅動的金融、AI和機器學習對金融理論和實踐的持久影響
- 應用神經網絡和強化學習來發現金融市場中的統計效率低下
- 通過回測和算法交易（交易策略的自動執行）識別和利用經濟效率低下的地方
- 理解AI將如何影響金融行業的競爭動態，以及金融奇點的潛在出現可能帶來的影響

作者簡介

Dr. Yves J. Hilpisch is founder and managing partner of The Python Quants (http: //tpq.io), a group that focuses on the use of open source technologies for financial data science, algorithmic trading and computational finance. He is the author of the books Python for Finance (O'Reilly, 2014), Derivatives Analytics with Python (Wiley, 2015) and Listed Volatility and Variance Derivatives (Wiley, 2017). Yves lectures on computational finance at the CQF Program (http: //cqf.com), on data science at htw saar University of Applied Sciences (http: //htwsaar.de), and is the director for the online training program leading to the first Python for Finance University Certificate (awarded by htw saar).

作者簡介(中文翻譯)

Dr. Yves J. Hilpisch是The Python Quants（http://tpq.io）的創始人和經營合夥人，該團隊專注於使用開源技術進行金融數據科學、算法交易和計算金融。他是《Python for Finance》（O'Reilly，2014）、《Derivatives Analytics with Python》（Wiley，2015）和《Listed Volatility and Variance Derivatives》（Wiley，2017）等書的作者。Yves在CQF Program（http://cqf.com）上講授計算金融課程，在htw saar應用科學大學（http://htwsaar.de）上講授數據科學課程，並擔任首個Python for Finance大學證書的線上培訓計劃主任（由htw saar頒發）。

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