You're reading from Machine Learning for Algorithmic Trading - Second Edition

Product typeBook

Published inJul 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781839217715

Edition2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Author (1)

Stefan Jansen

Index

Symbols

1/N portfolio 132

(first), high, low, and closing (last) price and volume (OHLCV) 35

LSTM architecture 599, 600

Accession Number (adsh) 55

AdaBoost algorithm 367

advantages 369

disadvantages 369

used, for predicting monthly price moves 369, 371

AdaGrad 528

adaptive boosting 366, 367

adaptive learning rates

about 527

AdaGrad 528

adaptive moment derivation (Adam) 528

RMSProp 528

adaptive moment derivation (Adam) 528

agglomerative clustering 435

aggressive strategies 4

Akaike information criterion (AIC) 183

AlexNet 564

AlexNet performance

comparing 566, 567

algorithm

finding, for task 149

Algorithm API 243

algorithmic trading libraries

Alpha Trading Labs

Interactive Brokers

pybacktest

Python Algorithmic Trading Library (PyAlgoTrade)

QuantConnect

Trading with Python

ultrafinance

WorldQuant

AlgoSeek 41

AlgoSeek intraday...

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Author (1)

Stefan Jansen

Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions for a broad range of business problems. Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank. He holds Master's degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin, and a CFA Charter. He has worked in six languages across Europe, Asia, and the Americas and taught data science at Datacamp and General Assembly.
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