puffinsoft/benchstreet
The benchmark for financial time series forecasting.
This project provides pre-trained models for financial time series forecasting, specifically for predicting S&P 500 daily closing prices over long periods. It helps quantitative analysts and researchers quickly compare different forecasting methods without needing to implement them from scratch. You input historical S&P 500 data, and the project outputs evaluated performance across various model types.
No commits in the last 6 months. Available on PyPI.
Use this if you are a quant or researcher wanting to evaluate the effectiveness of different forecasting models on financial market data, particularly for long-term S&P 500 predictions.
Not ideal if you need an objective, production-ready benchmark for diverse financial instruments or if you are not comfortable working with code examples to adapt models.
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14
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1
Language
Python
License
MIT
Category
Last pushed
Jul 19, 2025
Commits (30d)
0
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