affine term structure
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Author(s):  
Riccardo Brignone ◽  
Christoph Gerhart ◽  
Eva Lütkebohmert

AbstractWe propose an affine term structure model that allows for tenor-dependence of yield curves and thus for different risk categories in interbank rates, an important feature of post-crisis interest rate markets. The model has a Nelson–Siegel factor loading structure and thus economically well interpretable parameters. We show that the model is tractable in terms of estimation and provides good in-sample fit and out-of-sample forecasting performance. The proposed model is arbitrage-free across maturities and tenors, and thus perfectly suited for risk management and pricing purposes. We apply our framework to the pricing of caplets in order to illustrate its practical applicability and its suitability for stress testing.


2021 ◽  
Author(s):  
Scott Joslin ◽  
Anh Le

Within the affine framework, many have observed a tension between matching conditional first and second moments in dynamic term structure models (DTSMs). Although the existence of this tension is generally accepted, less understood is the mechanism that underlies it. We show that no arbitrage along with the rich information in the cross section of yields has strong implications for both the dynamics of volatility and the forecasts of yields. We show that this link implied by the absence of arbitrage—and not the factor structure per se—underlies the tension between first and second moments found in the literature. Adding to recent research that has suggested that no-arbitrage restrictions are nearly irrelevant in Gaussian DTSMs, our results show that no-arbitrage restrictions are potentially relevant when there is stochastic volatility. This paper was accepted by Gustavo Manso, finance.


2020 ◽  
Author(s):  
Hitesh Doshi ◽  
Kris Jacobs ◽  
Rui Liu

The existing literature finds that information not captured by traditional term structure factors helps predict excess bond returns. When estimating no-arbitrage affine term structure models, aligning in-sample and out-of-sample objective functions results in term structure factors that capture information that remains hidden from existing approaches. Specifically, the estimates of the third term structure factor radically differ and are related to the fourth principal component, which helps forecast bond returns. The new objective function leads to substantial improvements in forecasting performance. It also results in higher model term premiums and lower expected future short rates. This paper was accepted by David Simchi-Levi, finance.


2020 ◽  
Vol 110 ◽  
pp. 535-540
Author(s):  
Erin L. Wolcott

Foreign governments went from owning a tenth of publicly available US Treasury notes and bonds in 1985 to over half in 2008. Recently, foreign governments have reduced their positions. I find foreign official purchases have depressed medium-term yields, despite conventional wisdom pointing toward the long end of the yield curve. To examine effects over the entire yield curve, I embed a structural vector autoregression of macroeconomic variables into an affine term structure model. With segments of the yield curve increasingly determined by international financial markets, it may be more difficult for the Federal Reserve to implement its interest rate policy.


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