Model Archive

All 10 model reviews organized by category.

A summary of a published model or paper. Not a recommendation to use it for trading, and not financial, investment, legal or tax advice. Summaries can be inaccurate or out of date and are provided "as is". Check the model's license before commercial use. Terms & Disclaimer

Forecasting

Temporal Fusion Transformer for Interpretable Multi-horizon Forecasting

Attention-based architecture for multi-horizon time series forecasting with interpretable outputs.

Sep 2021

N-BEATS: Neural Basis Expansion Analysis for Time Series

Deep neural architecture specifically designed for univariate time series forecasting with backward and forward residual links.

Jun 2020

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Efficient transformer architecture using ProbSparse self-attention for long-sequence time series forecasting with O(L log L) complexity.

Mar 2021

TimesFM: A Decoder-Only Foundation Model for Time-Series Forecasting

Google Research pretrained decoder-only time-series foundation model (TimesFM) for zero-shot forecasting; ICML 2024 paper. Version 3.0 adds multivariate and covariate support. (Paper with Apache-2.0 code; v1.0–2.5 weights are Apache-2.0, v3.0 weights are non-commercial, non-production)

Feb 2024

Chronos / Chronos-2 (Amazon Science)

Pretrained time-series forecasting models. Chronos-2 (120M params) supports zero-shot univariate, multivariate, and covariate forecasting. Family spans 8M to 710M parameters. (Paper with Apache-2.0 code)

Mar 2024

Derivatives

Deep Hedging: Hedging Derivatives with Reinforcement Learning

Deep reinforcement learning framework for hedging derivatives under realistic market frictions including transaction costs, market impact, and risk limits.

Dec 2019

General

Advances in Financial Machine Learning (Book)

Marcos López de Prado's foundational book on financial ML techniques. Published by Wiley. Paid resource.

Jan 2018

NLP

FinGPT: Open-Source Financial LLMs

Open-source large language model framework for financial NLP using data-centric approach with automatic data curation and low-rank adaptation (LoRA) for efficient fine-tuning.

Jun 2023

Factor Investing

Empirical Asset Pricing via Machine Learning

Comparative analysis of machine learning methods for measuring equity risk premiums (expected stock returns), using 94 stock characteristics, their interactions with eight aggregate time-series variables, and 74 industry dummies.

May 2020

Risk Management

Tail-GAN: Learning to Simulate Tail Risk Scenarios

GAN-based approach for generating high-dimensional multi-asset price scenarios that preserve the tail risk (Value-at-Risk and Expected Shortfall) of a set of trading strategies, for estimating portfolio loss distributions.

Apr 2026