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@@ -42,7 +42,7 @@ We are pleased to introduce **FinText-TSFM**, a comprehensive suite of **time se
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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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  - **Evaluation Scope:**
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- Models are benchmarked across **U.S. and seven international markets**, using rolling windows of **5, 21, 252, and 512 days**, with over **18 million out-of-sample forecasts** spanning **22 years (2001–2023)** of daily excell returns, evaluated at both the **statistical** and **economic performance** levels.
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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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  - **Evaluation Scope:**
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+ Models are benchmarked across **U.S. and seven international markets**, using rolling windows of **5, 21, 252, and 512 days**, with over **18 million out-of-sample forecasts** spanning **22 years (2001–2023)** of daily excess returns, evaluated at both the **statistical** and **economic performance** levels.
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