Trading Decoded - Artificial Intelligence Applications In Finance: Machine Learning for Algorithmic / Quantitative trading
Trading Decoded - Artificial Intelligence Applications In Finance: Machine Learning for Algorithmic / Quantitative trading

How to Download Trading Decoded - Artificial Intelligence Applications In Finance: Machine Learning for Algorithmic / Quantitative trading MOBI

If you are on Amazon mobile app and want to buy Kindle version, checkout the Amazon website to get the Kindle option.Editorial Reviews"I can highly recommend this book to everyone who wants to start developing ML and AI models to apply on financial assets" -Jerome Cohen, Managing Member, Viseroij Capital Management"Trading decoded fills an important void in the trading and system development literature" - Michael Annerl, Managing Partner, Viseroij Capital Management"The book will be a true treasure for all the readers" - Ajay Agarwal, Director, EIS Global Pte LtdFrom AuthorsWe share their trials, tribulations, and learnings on how to apply Artificial Intelligence to High-Frequency Trading, day trading, and long term investment management. We have spent the last several years researching and applying these techniques, made several mistakes, and learned from them. We do hope the readers would enjoy the narration.We have covered most AI algorithms and explained each concept with case studies relevant to finance. Traders and investment management professionals looking to learn about AI should find this book quite useful. AI experts who want to see how their expertise can be applied to finance should find this book useful too. Beginners in both fields should be able to learn a fair bit from it as well, which may require repeat reading. Experts in AI and in investment management would easily reaffirm their expertise. Python code is provided for certain concepts to illustrate the usage of Machine Learning or Deep Learning libraries.

  • Released: November 16, 2020
  • Author: Avirath Kakkar,Arvin Sahni,Rajalingappaa Shanmugamani
  • Rating: 4,3
  • Publisher: Ebook DIgital Agency
  • Total Page: 1005 pages
  • File Size: 3670 KB

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