Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis
📰 ArXiv cs.AI
Learn how to forecast yield curves using machine learning and econometrics, and compare their performance on U.S. Treasury yield curve data
Action Steps
- Collect daily U.S. Treasury yield curve data over a long period, such as 47 years, to train and test forecasting models
- Apply econometrics/time-series analysis methods, such as ARIMA and VAR, to forecast yield curves
- Implement classical machine learning methods, including linear regression and random forests, to predict yield curves
- Use deep learning techniques, such as LSTM and CNN, to forecast yield curves and compare their performance with other methods
- Evaluate and compare the forecasting performance of different models using metrics such as mean squared error and mean absolute error
Who Needs to Know This
Quantitative analysts and researchers in finance can benefit from this study to improve their yield curve forecasting models, while data scientists can apply the comparative analysis to other time-series forecasting problems
Key Insight
💡 Machine learning and econometrics can be used to forecast yield curves, but their performance varies depending on the method and data used
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💡 Forecast yield curves with machine learning and econometrics! 📊 Compare performance on U.S. Treasury yield curve data 📈
Key Takeaways
Learn how to forecast yield curves using machine learning and econometrics, and compare their performance on U.S. Treasury yield curve data
Full Article
Title: Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis
Abstract:
arXiv:2605.09842v1 Announce Type: new Abstract: While machine learning has revolutionized many fields such as natural language processing (NLP) and computer vision, its impact on time-series forecasting is still widely disputed, especially in the finance domain. This paper compares forecasting performance on U.S. Treasury yield curve data across econometrics/time-series analysis, classical machine learning, and deep learning methods, using daily data over 47 years. The Treasury yield curve is im
Abstract:
arXiv:2605.09842v1 Announce Type: new Abstract: While machine learning has revolutionized many fields such as natural language processing (NLP) and computer vision, its impact on time-series forecasting is still widely disputed, especially in the finance domain. This paper compares forecasting performance on U.S. Treasury yield curve data across econometrics/time-series analysis, classical machine learning, and deep learning methods, using daily data over 47 years. The Treasury yield curve is im
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