Forecasting interest rates with shifting endpoints
研究了在收益率曲线因子围绕缓慢时变均值（移动端点）的假设下预测利率期限结构，发现相比平稳和随机游走基准，该方法显著提升了样本外预测精度，尤其对长期利率和长期预测改进最大。
SUMMARY We consider forecasting the term structure of interest rates with the assumption that factors driving the yield curve are stationary around a slowly time‐varying mean or ‘shifting endpoint’. The shifting endpoints are captured using either (i) time series methods (exponential smoothing) or (ii) long‐range survey forecasts of either interest rates or inflation and output growth, or (iii) exponentially smoothed realizations of these macro variables. Allowing for shifting endpoints in yield curve factors provides substantial and significant gains in out‐of‐sample predictive accuracy, relative to stationary and random walk benchmarks. Forecast improvements are largest for long‐maturity interest rates and for long‐horizon forecasts. Copyright © 2013 John Wiley & Sons, Ltd.