Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Buy

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

  • Implement machine learning algorithms to build, train, and validate algorithmic models
  • Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions
  • Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics

Book Description

The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies.

This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies.

Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym.

What you will learn

  • Implement machine learning techniques to solve investment and trading problems
  • Leverage market, fundamental, and alternative data to research alpha factors
  • Design and fine-tune supervised, unsupervised, and reinforcement learning models
  • Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn
  • Integrate machine learning models into a live trading strategy on Quantopian
  • Evaluate strategies using reliable backtesting methodologies for time series
  • Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow
  • Work with reinforcement learning for trading strategies in the OpenAI Gym

Who this book is for

Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Table of Contents

  1. Machine Learning for Trading
  2. Market and Fundamental Data
  3. Alternative Data for Finance
  4. Alpha Factor Research
  5. Strategy Evaluation
  6. The Machine Learning Process
  7. Linear Models
  8. Time Series Models
  9. Bayesian Machine Learning
  10. Decision Trees and Random Forests
  11. Gradient Boosting Machines
  12. Unsupervised Learning
  13. Working with Text Data
  14. Topic Modeling
  15. Word Embeddings
  16. Next Steps
(HTML tags aren't allowed.)

Pro Puppet
Pro Puppet

The lives of system administrators and operations staff often revolve around a series of repetitive tasks: configuring hosts, creating users, and managing applications, daemons, and services. Often these tasks are repeated many times in the life cycle of one host, from building to decommissioning, and as new configuration is added or...

Combustion Processes in Propulsion: Control, Noise, and Pulse Detonation
Combustion Processes in Propulsion: Control, Noise, and Pulse Detonation
"This collection represents the current state-of-the-art in combustion research for air-breathing chemical propulsion. Nearly an equal mix of computational and experimental results are presented from the major players in Pulse Detonation Engines research, providing the reader with a thorough overview of the contemporary technical issues...
Criminal Poisoning: Investigational Guide for Law Enforcement, Toxicologists, Forensic Scientists, and Attorneys (Forensic Science and Medicine)
Criminal Poisoning: Investigational Guide for Law Enforcement, Toxicologists, Forensic Scientists, and Attorneys (Forensic Science and Medicine)

In this revised and expanded edition, leading forensic scientist John Trestrail offers a pioneering survey of all that is known about the use of poison as a weapon in murder. Topics range from the use of poisons in history and literature to convicting the poisoner in court, and include a review of the different types of poisons, techniques...


Beginning the Linux Command Line
Beginning the Linux Command Line

This is Linux for those of us who don’t mind typing. All Linux users and administrators tend to like the flexibility and speed of Linux administration from the command line in byte–sized chunks, instead of fairly standard graphical user interfaces. Beginning the Linux Command Line is verified against all of the most...

Immigrant, Inc.: Why Immigrant Entrepreneurs Are Driving the New Economy
Immigrant, Inc.: Why Immigrant Entrepreneurs Are Driving the New Economy

A provocative look at the remarkable contributions of high-skill immigrant entrepreneurs in America

Both a revelation and a call-to-action, Immigrant, Inc. explores the uncommon skill and drive of America's new immigrants and their knack for innovation and entrepreneurship. From the techies who created icons of...

ANSI Common LISP
ANSI Common LISP
Combines an introduction to Lisp programming and a convenient, up-to-date reference manual for ANSI Common Lisp. Professional programmers will appreciate its thorough, practical approach. Paper. DLC: COMMON LISP (Computer program language)

Teaching users new and more powerful ways of thinking about programs, this
...
©2019 LearnIT (support@pdfchm.net) - Privacy Policy