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README.md
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@@ -35,6 +35,7 @@ We are pleased to introduce **FinText-TSFM**, a comprehensive suite of **time se
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- U.S.: Covers U.S. market-wide excess returns from 2000 to 2023, with one pre-trained model per year.
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- Global: Covers 89 global markets excess returns from 2000 to 2023, with one pre-trained model per year.
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- Augmented: It extend global data with augmented factors from 2000 to 2023, with one pre-trained model per year.
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- **Performance Insights:**
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Our findings show that **off-the-shelf TSFMs** underperform in zero-shot forecasting, while **finance-pretrained models** achieve large gains in both predictive accuracy and portfolio performance.
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- U.S.: Covers U.S. market-wide excess returns from 2000 to 2023, with one pre-trained model per year.
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- Global: Covers 89 global markets excess returns from 2000 to 2023, with one pre-trained model per year.
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- Augmented: It extend global data with augmented factors from 2000 to 2023, with one pre-trained model per year.
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- The remaining TSFMs are available for download via the [**FinText.ai Portal**](https://fintext.ai).
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- **Performance Insights:**
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Our findings show that **off-the-shelf TSFMs** underperform in zero-shot forecasting, while **finance-pretrained models** achieve large gains in both predictive accuracy and portfolio performance.
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