Artificial Intelligence for Trading
WorldQuant via Udacity Nanodegree
Overview
In this program, you’ll analyze real data and build financial models for trading. Whether you want to pursue a new job in finance, launch yourself on the path to a quant trading career, or master the latest AI applications in quantitative finance, this program offers you the opportunity to master valuable data and AI skills.
Complete real-world projects designed by industry experts, covering topics from asset management to trading signal generation. Master AI algorithms for trading, and build your career-ready portfolio.
Syllabus
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Basic Quantitative Trading
Learn about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.
Trading with momentum -
Advanced Quantitative Trading
Learn the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.
Breakout Strategy -
Stocks, Indices, and ETFs
Learn about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs.
Smart Beta and Portfolio Optimization -
Factor Investing and Alpha Research
Learn about alpha and risk factors, and construct a portfolio with advanced optimization techniques.
Alpha Research and Factor Modeling -
Sentiment Analysis with Natural Language Processing
Learn the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.
Sentiment Analysis using NLP -
Advanced Natural Language Processing with Deep Learning
Learn to apply deep learning in quantitative analysis and use recurrent neural networks and long short-term memory to generate trading signals.
Deep Neural Network with News Data -
Combining Multiple Signals
Learn advanced techniques to select and combine the factors you’ve generated from both traditional and alternative data.
Combine Signals for Enhanced Alpha -
Simulating Trades with Historical Data
Learn to refine trading signals by running rigorous back tests. Track your P&L while your algorithm buys and sells.
Backtesting
Taught by
Cindy Lin, Arpan Chakraborty, Elizabeth Otto Hamel, Eddy Shyu, Brok Bucholtz, Parnian Barekatain, Juan Delgado, Luis Serrano, Cezanne Camacho, Mat Leonard, Eduardo P., Hsin-Wen C., Frank Salvador Y., Sridhar S., Jonnie W. and André V.
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