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Long-term interest rates of small open economies (SOE) correlate strongly with the USA long-term rate. Can central banks in those countries decouple from the United States? An estimated Dynamic Stochastic General Equilibrium (DSGE) model for the UK (vis-á-vis the USA) establishes three structural empirical results: (1) Comovement arises due to nominal fluctuations, not through real rates or term premia; (2) the cause of comovement is the central bank of the SOE accommodating foreign inflation trends, rather than systematically curbing them; and (3) SOE may find themselves much more affected by changes in USA inflation trends than the United States itself. All three results are shown to be intuitive and backed by off-model evidence.

This paper investigates the relationship between government borrowing and long‐term interest rates utilizing a loanable funds framework to describe the interest rate determination process. Three measures of government borrowing are examined. The results indicate that there is not a significant relationship between government borrowing and long‐term interest rates.

Vector‐autoregression (VAR), integration, and cointegration models are used to investigate the causal relations, dynamic interaction, and a common trend between interest rates and inflation in nine countries in the Pacific‐Basin. This paper finds that for all countries, short‐ and long‐term interest rates and the spread between the long‐term interest rates and inflation are non‐stationary I (1) processes. The nominal interest rates and inflation are not co‐integrated. In addition to this study’s inability to find a unidirectional causality between inflation and interest rates, when the VAR model is used, it also fails to find a consistent positive response either of inflation to shocks in interest rates or of interest rates to shocks in inflation in most of the countries studied. The VAR model results are consistent with the cointegration tests’ results, that is, nominal interest rates are poor predictors for future inflation in the Pacific‐Basin countries.

The purpose of this paper is to analyze different behaviors between long-term options’ implied volatilities and realized volatilities.

This paper uses a widely adopted short interest rate model that describes a stochastic process of the short interest rate to capture interest rate risk. Price a long-term option by a system of two stochastic processes to capture both underlying asset and interest rate volatilities. Model capital charges according to the Basel III regulatory specified approach. S&P 500 index and relevant data are used to illustrate how the proposed model works. Coup with the low interest rate scenario by first choosing an optimal time segment obtained by a multiple change-point detection method, and then using the data from the chosen time segment to estimate the CIR model parameters, and finally obtaining the final option price by incorporating the capital charge costs.

Monotonic increase in long-term option implied volatility can be explained mainly by interest rate risk, and the level of implied volatility can be explained by various valuation adjustments, particularly risk capital costs, which differ from existing published literatures that typically explained the differences in behaviors of long-term implied volatilities by the volatility of volatility or risk premium. The empirical results well explain long-term volatility behaviors.

The authors only consider the market risk capital in this paper for demonstration purpose. Dealers may price the long-term options with the credit risk. It appears that other than the market risks such as underlying asset volatility and interest rate volatility, the market risk capital is a main nonmarket risk factor that significantly affects the long-term option prices.

Analysis helps readers and/or users of long-term options to understand why long-term option implied equity volatilities are much higher than observed. The framework offered in the paper provides some guidance if one would like to check if a long-term option is priced reasonable.

It is the first time to analyze mathematically long-term options’ volatility behavior in comparison with historically observed volatility.

This study attempts to determine whether the level and volatility of interest rates affect the equity returns of commercial banks. Short‐term, intermediate‐term, and long‐term interest rates are used. Volatility is defined as the conditional variance of respective interest rates and is generated by using the ARCH estimation procedure. Two sets of models are estimated. The basic models attempt to determine the effect of contemporaneous and lagged interest rate volatility on bank equity returns, while the extended models incorporate additional contemporaneous macroeconomic variables. Contemporaneous interest rate volatility has little explanatory power, while lagged volatilities do possess some explanatory power, with the lag length varying depending on the interest rate series used and the time period examined. The results from the extended model suggest that the long‐term interest rate affects bank equity returns more adversely than the short‐term or the intermediate‐term interest rates. The findings establish the relevance of incorporating macroeconomic variables and their volatilities in models determining bank equity returns.

This chapter conducts an event study of 30 quantitative easing (QE) announcements made by 21 central banks on daily government bond yields and bilateral US dollar exchange rates in March and April 2020, in the midst of the global financial turmoil triggered by the COVID-19 outbreak. The chapter also investigates the transmission of innovations to long-term interest rates in a standard GVAR model estimated with quarterly pre-COVID-19 data. The authors find that QE has not lost effectiveness in advanced economies and that its international transmission is consistent with the working of long-run uncovered interest rate parity and a large dollar shortage shock during the COVID-19 period. In emerging markets, the QE impact on bond yields is much stronger and its transmission to exchange rates is qualitatively different than in advanced economies. The GVAR evidence that the authors report illustrates the Fed’s pivotal role in the global transmission of long-term interest rate shocks, but also the ample scope for country-specific interventions to affect local financial market conditions, even after controlling for common factors and spillovers from other countries. The GVAR evidence also shows that QE interventions can have sizable real effects on output driven by a very persistent impact on long-term interest rates.

The possibility that government borrowing may crowd out private borrowing has been widely discussed in the popular press and extensively analyzed by researchers. The Clinton Administration's “Operation Twist,” resulting in increased reliance on short‐term securities to fund the Federal deficit, highlights the impact of the maturity structure of Treasury debt issues on interest rates. This paper examines the relationship between changes in the maturity distribution of Treasury issues and Moody's twenty year AA municipal bond yield. Briefly, I find changes in the maturity structure of outstanding Treasury securities Granger‐cause changes in the Moody's twenty‐year AA municipal bond yield. The results suggest that changes in the maturity structure of Treasury borrowing will impact the interest expense of municipal debt issues and therefore the rate of return earned by holders of municipal securities.

Analyses the empirical relation between the one‐month interest rate, the long‐term interest rate and the motgage rate in The Netherlands. To study the dynamic interactions between these variables, vector autoregressive techniques are used. Concentrates on the question of whether the mortgage rate dynamics can correctly be described by a one‐factor interest rate model. One‐factor interest rate models allow mathematical derivations of deterministic equations to price interest rate derivatives. Finds, however, that a single factor does not correctly describe the interest rate term structure. Hence, to model the mortgage rate dynamics accurately more factors should be included.

Economic fundamentals—such as economic growth, inflationary expectations, and monetary policy—cannot explain the worldwide rise in long‐term interest rates during 1994. The present paper investigates the extent to which the rise in rates was consistent with economic theory and domestic policies. It finds that it is necessary to introduce institutional factors to account for the widespread nature of the rise and the extent of the rise as well as, for some countries, the fact that long rates rose at all.