Unified Model Arbitrage-Free Term Structure of Flow Risks

2021 ◽  
pp. 1-26
Author(s):  
Thomas S. Y. Ho ◽  
Sang Bin Lee
2018 ◽  
Author(s):  
Maxim Ulrich ◽  
Stephan Florig ◽  
Christian Wuchte
Keyword(s):  

2021 ◽  
pp. 01-38
Author(s):  
Jens H. E. Christensen ◽  
◽  
Mark M. Spiegel ◽  

Japanese realized and expected inflation has been below the Bank of Japan’s two percent target for many years. We use the exogenous COVID-19 pandemic shock to examine the efficacy of monetary and fiscal policy responses for elevating inflation expectations from an arbitrage-free term structure model of nominal and real yields. We find that monetary and fiscal policy announcements during this period failed to lift inflation expectations, which instead declined notably and are projected to only slowly revert back to levels far below the announced target. Hence, our results illustrate the challenges faced in raising well-anchored low inflation expectations.


Author(s):  
Francis X. Diebold ◽  
Glenn D. Rudebusch

This chapter discusses a new class of affine arbitrage-free models that overcome the problems with empirical implementation of the canonical affine arbitrage-free model. This new class is based on the dynamic Nelson–Siegel model (DNS) and retains its empirical tractability. Thus, from one perspective, the chapter takes the theoretically rigorous but empirically problematic affine arbitrage-free model and makes it empirically tractable by incorporating DNS elements. From an alternative perspective, it takes the DNS model and makes it theoretically more satisfactory. DNS is simple and stable to estimate, and it is quite flexible and fits both the cross section and time series of yields remarkably well. However, DNS fails on an important theoretical dimension: It does not impose the restrictions necessary to eliminate opportunities for riskless arbitrage. The lack of freedom from arbitrage motivated Diebold et al. (2005) and Christensen et al. (2011) to introduce the class of arbitrage-free Nelson–Siegel (AFNS) yield curve models, which are affine arbitrage-free term structure models that nevertheless maintain the DNS factor-loading structure.


2007 ◽  
Vol 42 (3) ◽  
pp. 595-620 ◽  
Author(s):  
Heber Farnsworth ◽  
Tao Li

AbstractThere is a large and growing literature on how to model the dynamics of the default-free term structure to fit the observed historical data. Much less is known about how best to model the dynamics of defaultable yield curves. This paper develops a class of defaultable term structure models that is tractable enough to be empirically implemented and flexible enough to capture some important behaviors of the credit spreads in the data. We compare two non-nested models within this class using a Bayesian estimation technique, which helps to solve the problem of latent state variables. The Bayesian approach also enables us to test the two non-nested models on the basis of the Bayes factor. The results strongly suggest that models with constant transition probabilities will not be able to fit the observed dynamics of inter-rating spreads.


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