Econ Papers Daily / 期刊论文
长期收益率有助于估计短期风险溢价吗？
Do long-term yields help to estimate short-term risk premia?
摘要
We identify a new and important property of affine term structure models: at long maturities, the slope of the term structure of risk premia becomes “almost observable”. Exploiting this property by fitting models to long-maturity data dramatically improves the precision of estimates of risk premia and expected short rates across the term structure. In a Monte Carlo experiment we show that using rates with maturities up to 25 years, rather than 10 years as is standard in the literature, reduces the standard deviation of estimation errors in risk premia, expected short rates and term premia by over 70%. Applying this approach to US Treasury data, we find that variation in expected short rates accounts for a much larger share of variation in yields (and variation in term premia a correspondingly smaller fraction) than in the widely used estimates reported by the Federal Reserve. Accounting for time-variation in yield volatility is key to successful extraction of the risk premium information in long rates. Our approach therefore departs from much of the empirical literature in two important respects: it incorporates long-maturity yields and allows for time-varying yield volatility, whereas most existing studies ignore long-term yields and rely on constant volatility models.
中文摘要
我们发现仿射期限结构模型的一个新的重要性质：在长到期期限上，风险溢价期限结构的斜率变得“几乎可观测”。利用这一性质，将模型拟合到长到期数据，可以显著提高对整个期限结构上风险溢价和预期短期利率估计的精度。在一项蒙特卡洛实验中，我们表明，使用到期期限最长可达25年的利率，而非文献中标准的10年利率，可将风险溢价、预期短期利率和期限溢价中估计误差的标准差降低超过70%。将这一方法应用于美国国债数据，我们发现，与美联储报告的广泛使用的估计相比，预期短期利率的变动在收益率变动中所占的份额要大得多（相应地，期限溢价变动所占的份额要小得多）。考虑收益率波动率的时间变化是成功提取长利率中风险溢价信息的关键。因此，我们的方法在两个重要方面不同于许多实证文献：它纳入长到期收益率，并允许收益率波动率随时间变化，而大多数现有研究忽略长期收益率并依赖恒定波动率模型。