Description: Further DetailsTitle: Machine Learning for Algorithmic TradingCondition: NewSubtitle: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd EditionEAN: 9781839217715ISBN: 9781839217715Publisher: Packt Publishing LimitedFormat: PaperbackRelease Date: 07/31/2020Description: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format.Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance.What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.Language: EnglishCountry/Region of Manufacture: GBItem Height: 93mmItem Length: 75mmAuthor: Stefan JansenGenre: Computing & InternetISBN-10: 1839217715Release Year: 2020 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
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Publication Name: Machine Learning for Algorithmic Trading
Title: Machine Learning for Algorithmic Trading
Subtitle: Predictive models to extract signals from market and alternative
EAN: 9781839217715
ISBN: 9781839217715
Release Date: 07/31/2020
Release Year: 2020
Country/Region of Manufacture: GB
Item Height: 93mm
ISBN-10: 1839217715
Edition: 2
Book Title: Machine Learning for Algorithmic Trading : Predictive Models to Extract Signals from Market and Alternative Data for Systematic Trading Strategies with Python, 2nd Edition
Number of Pages: 822 Pages
Language: English
Publisher: Packt Publishing, The Limited
Topic: Machine Theory, Finance / Financial Engineering, Finance / General, Forecasting
Publication Year: 2020
Genre: Computers, Business & Economics
Item Length: 3.6 in
Author: Stefan Jansen
Item Width: 3 in
Format: Trade Paperback
