Direct Estimation of the Risk Neutral Factor Dynamics of Affine Term Structure Models

Recent events have highlighted the potential importance of nonlinear efiects of flscal variables (notably debt and deflcits) on interest rates: While in times when government solvency is not a concern the standard crowding-out efiects are of moderate magnitude, in times when default risk becomes an issue the interest rate efiects can become very large. This paper provides new evidence on the magnitude of these efiects. For the case when default risk is not a concern, it uses an arbitrage-free term structure model to estimate the dynamic efiects of flscal policy shocks on interest rates along the entire maturity spectrum. For the case when default risk becomes a concern (thereby violating a central assumption of the term structure model), I present evidence based on EMU government bond spread regressions on time-varying efiects of national flscal policies on spreads as well as the time-varying sensitivity of yield spreads to international risk aversion as a function of the state of flscal policy. JEL classiflcation: E6, H6.

Government Bonds and the Term Structure of Interest Rates

The aim of this paper is twofold; first we concentrate on the work of Vasicek (1977) and Cox, Ingersoll and Ross (1985). We examine and test empirically each model and discuss its performance in predicting the term structure of interest rates using a parametric estimating approach GMM (Generalized Moments Method). Second we estimate the term structure of interest rate dynamics using a nonparametric approach ANN (Artificial Neural Network). Two neural network models are performed. The first model uses spreads between interest rates of 10 different maturities as the only explanatory variable of interest rate changes. The second model introduces two factors, spreads and interest rates' levels. Using historical U.S. Treasury bill rates and Treasury bond yields, we compare the ability of each model to predict the term structure of interest rates. Data are daily and cover the period from 3 January 1995 to 29 December 2000. Results suggest that neural network, Vasicek (1977) and Cox, Ingersoll and Ross (1985) models generate different yield curves. Neural network models outperform the parametric standard models. The most successful forecast is obtained with a two factors neural network model.

The term structure of interest rates, i.e., yield curve, has long been of interest to monetary policymakers and their advisers. The transmission of monetary is conventionally viewed as running from shortterm interest rates managed by central banks to longer-term rates that influence aggregate demand. A central bank's leverage over longer-term rates comes from fact that market determines these as average expected level of short rates over relevant horizon (abstracting from a term premium and default risk). Working in other direction, long bond rate contains a premium for expected and, thus, serves as an indicator of credibility of a central bank's commitment to low inflation.1 Different theoretical perspectives support two above-mentioned uses of term structure for monetary policy: John Hicks's (1939) expectations theory of term structure supports first, and Irving Fisher's (1896) decomposition of nominal bond rates into expected and an expected real return supports second.2 The two views are compatible in principle, although reconciling them creates difficulties of interpretation in practice. For example, does a steepening yield curve indicate a loss of confidence in central bank's commitment to low inflation, or does it indicate that markets expect tighter in form of a higher path of short rates pursued by central bank? The yield curve contains information of use to monetary policymakers, but it needs to be interpreted in light of judicious subsidiary identifying conditions, together with other data on economy. Some circumstances lend themselves to clearer interpretations than others, and there are many pitfalls. Whether or not one regards longer-term interest rates as economic indicators or as part of transmission mechanism for policy, or both, term structure plays a potentially important role in policymaking process. In spite of its complexity, term structure cannot be ignored. This article addresses some issues involved in using term structure to conduct monetary policy. I begin by discussing long bond rate as an indicator of expectations. Second, I comment on role that bond rates have played in recent U.S. monetary history. Third, I explain how information in yield curve can be used to overcome what I call policy in pipeline problem. Fourth, I review recent empirical evidence supporting two theoretical views underlying our understanding of term structure. I explain how peso problems associated with inflation scares in bond market may help to account for a serious empirical failure of expectations theory of term structure. I also discuss evidence supporting view that significant movements in long-term interest rates are largely driven by expected inflation. Finally, I point out some pitfalls of using term structure to make tactical decisions. 1. PURSUING LOW INFLATION The Chairman of Federal Reserve Board, Alan Greenspan, supports a longrun goal for price stability such that the expected rate of change of general level of prices ceases to be a factor in individual and business decisionmaking.3 The long bond rate is particularly well suited to help a central bank assess degree to which it has achieved low defined in that way. One could compare behavior of yield on a long-term nominal bond to its behavior in a past period in which was very low and public was reasonably confident that it would stay low. For instance, in United States 30-year nominal bond rate ranged from around 3 percent to a little over 4 percent from mid-1950s until mid-1960s, a period in which averaged around 1 to 2 percent, and presumably, long-term expectations were no more than that.4 One would think that if Federal Reserve (the Fed) were to achieve full credibility for low inflation, long bond rate would once again move down to 3 to 4 percent range. …

Term Structure of Interest Rates. Review of a Theory of the Term Structure of Interest Rates (CIR)

Pricing and Hedging Interest Rate Options: Evidence from Cap-Floor Markets

Significant amount of research has been dedicated to explaining property yields. Long term interest rate is usually identified as one of the key determinants, and property yields are often benchmarked to long term government bonds, which are considered to represent the closest alternative to property investments. However, empirical evidence provides a mixed picture indicating that the link is less than straightforward even when allowing for a time-varying risk premium. We argue that the relationship between interest rates and property yields is not just contemporaneous and expectations about future interest rates need to be accounted for in order to fully understand the link between these variables. Since real estate is illiquid and involves significant transaction cost, investors are effectively locked in for many years once they commit to a project. An interest rate increase during that period would expose them to a valuation risk. Moreover, when benchmarking to liquid bonds, the opportunity cost is not only the interest they can earn today but also the interest they could expect in the near future. Fundamentally, the term structure of interest rates (yield curve) contains information about the expected future interest rate. Therefore, we would expect that a steeper curve should result in higher property yields. We test this hypothesis using prime office yields in the key centres in Europe and Australia and find convincing evidence that the shape of the yield curve indeed affects property yields.

58 - Portfolio management II

A Fresh View on the Ho-Lee Model of the Term Structure from a Stochastic Discounting Perspective

The space of probability distributions on a given sample space possesses natural geometric properties. For example, in the case of a smooth parametric family of probability distributions on the real line, the parameter space has a Riemannian structure induced by the embedding of the family into the Hilbert space of square-integrable functions, and is characterised by the Fisher-Rao metric. In the nonparametric case the relevant geometry is determined by the spherical distance function of Bhattacharyya. In the context of term structure modelling, we show that minus the derivative of the discount function with respect to the maturity date gives rise to a probability density. This follows as a consequence of the positivity of interest rates. Therefore, by mapping the density functions associated with a given family of term structures to Hilbert space, the resulting metrical geometry can be used to analyse the relationship of yield curves to one another. We show that the general arbitrage-free yield curve dynamics can be represented as a process taking values in the convex space of smooth density functions on the positive real line. It follows that the theory of interest rate dynamics can be represented by a class of processes in Hilbert space. We also derive the dynamics for the central moments associated with the distribution determined by the yield curve.

We examine and test the validity of the expectation hypothesis of the term structure (EHTS) of interest rates in Saudi Arabia using the traditional single equation approach, Campbell and Shiller methodology, Error Correction Model, and monthly data over the period June 1983 to December 2014. The results of the single equation approach indicate that the test of validity of the expectation hypothesis cannot be rejected for all maturities. We also find that the validity of the EHTS of interest rates is supported through the stationarity of the term spreads between short- and long-term interest rates. Moreover, the cointegration test reveals the existence of a cointegration relationship between short- and long-term interest with ( 1 − 1 ) $\left(1-1\right)$ cointegrating vector, suggesting the validity EHTS of interest rates. Policy implications based on the empirical results suggest that the transparency of monetary policy in Saudi Arabia and the effective role of the Saudi Arabian Monetary Authority (SAMA) in conducting monetary policy increase the predictive power of market participants of future movements of short-term interest rates.

An Empirical Analysis of Yield Curves Across Euro and Non-Euro Countries Using Interbank Interest Rates

The term structure of interest rates within a production economy: A parametric example

At present, China is in the critical stage of transforming from a quantitative monetary policy to a price-based monetary policy. The implementation of a quantitative-price mixed monetary policy can further improve the effect of monetary policy and interest rate regulation and maintain the stable operation of the macro economy. Based on the current economic situation, this article conducts experiments to prove the relationship between its monetary policy and the term structure of interest rates. To this end, this article first analyzes and compares the final effects of monetary policy on regional economies with the aid of an analysis framework that can simultaneously take into account the individuality of regional economies, the spillover effects between regional economies and the overall nature of monetary policy. Then, this article further combines the current background of interest rate marketization and monetary policy from quantity-oriented price-oriented changes. Focusing on the interest rate channel, it deeply analyzes the regional effects and formation of China's monetary policy under the new situation. First of all, on the basis of combing and summarizing relevant literature, find the expansion space for evaluating the regional effect of China's monetary policy. Experimental research results show that the term structure of interest rates is playing an increasingly important role in monetary policy. Combining the study of the term structure of interest rates with monetary policy and examining the relationship between them can not only promote the role of interest rates in macro-control, but also have important implications for improving the forward-looking and effectiveness of monetary policy.

Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model