Quantitative finance
An advanced path through the quant toolkit: probability and time-series statistics, machine learning for markets (including the deep-learning and LSTM approaches ForecastingStocks itself uses), how alpha factors are built and combined, and how to validate a strategy without fooling yourself.
Statistics for quants
The probability and time-series foundations every model rests on.
Machine learning for markets
Supervised, unsupervised and deep learning — what works, what dazzles, and what is dangerous.
Alpha factors and signals
The well-known sources of return and how to turn them into a tradeable signal.
Validation and the backtest trap
How to test a strategy without fooling yourself — the discipline that separates real edges from mirages.
This content is for educational and informational purposes only and is not investment, financial, tax or legal advice. Trading and investing carry risk, including the possible loss of capital. Any performance shown by third-party tools is hypothetical and not a promise of future results. Do your own research and consider professional advice before making any decision.