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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.

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.

This study employs a multivariate GARCH model to investigate the relative sensitivities of the first and the second moment of bank stock return distribution to the short‐term and long‐term interest rates and their respective volatilities. Three portfolios are formed representing the money center banks, large banks, and small banks, respectively. Estimation and testing of hypotheses are carried out for each of the three portfolios separately. The sample includes daily data over the 1988‐2000 period. Several hypotheses are tested within the multivariate GARCH specification. These include the hypotheses of: (i) insensitivity of bank stock return to the changes in the short‐term and long‐term interest rates, (ii) insensitivity of bank stock returns to the changes in the volatilities of short‐term and long‐term interest rates, and (iii) insensitivity of bank stock return volatility to the changes in the short‐term and long‐term interest rate volatilities. The findings indicate that short‐term and long‐term interest rates and their volatilities do exert significant and differential impacts on the return generation process of the three bank portfolios. The magnitudes and the direction of the effect are model‐specific namely that they depend on whether the short‐term or the long‐term interest rate level is included in the mean return equation. These findings have implications on bank hedging strategies against the interest rate risk, regulatory decisions concerning risk‐based capital requirement, and investor’s choice of a portfolio mix.

This paper aims to examine the Treasury bond yields response to monetary policy shocks in Tunisia under a heterogeneous economic environment.

Using a traditional fixed coefficient model, the impact of monetary policy changes on the term structure of interest rates for the whole period from January 2006 to December 2016 is estimated first. Then the stability of this relationship by distinguishing two sub-periods around the revolution of January 2011 is studies. To investigate how the relationship between the monetary policy and the Treasury yield curve evolves over time, a time-varying parameter model is estimated.

The results show that the impact of monetary policy is more pronounced at the short end of the yield curve relative to the longer end. Furthermore, this impact declines significantly across all maturities following the revolution and exhibits wide time variation. This evidence supports the negative influence of high levels of uncertainty on monetary policy effectiveness and highlights the desirability of more active monetary policy, especially in turbulent environment.

The impact of uncertainty on the effectiveness of monetary policy shocks needs to be explored further in future research to understand the structural sources of uncertainty and their dynamic interactions with monetary policy and risk aversion in asset markets.

A more active role of the central bank to influence the yield curve mainly through Treasury bond purchases covering medium and long maturities may be warranted. Communication also needs to be reinforced to ensure predictability of the monetary policy stance.

This paper extends the empirical literature on the pass-through of monetary policy to interest rates for an emerging country in context of transition by estimating a state-space model to test the time-varying behavior and examine the influence of increased economic uncertainty on monetary policy effectiveness.

Existing research has theoretically modeled conditional correlations between the long-term interest rates as a function of macroeconomic variable. In line with it, the purpose of this paper is to explore whether conditional correlations can be a new signal to predict recessions. Furthermore, this paper also tries to investigate among the four factors – the time difference of the beginning and the end of recessions, financial integration (FI), and trade integration (TI) – which factors drive the direction of change in conditional correlations. Finally, this paper is to explain the implication for Korea trade.

This study uses a probit regression model for 33 country during the period from 1972 to 2015. To measure the time-varying interest rates conditional correlations, a VAR(1)-DBEKK-GARCH(1,1) model is adopted due to its statistical advantages. Furthermore, the authors also construct the four measures – time difference of the beginning of recessions (BEG), time difference of the end of recessions (END), FI, and TI. The authors first study the predictive power of correlations in both in and out-samples test, and study which factors determine the different behavior of interest rate co-movements using the four measures.

The empirical results show that the conditional correlations between the long-term interest rates of the USA and individual countries contain information about recessions a few quarters ahead which term spreads of neither individual countries nor the USA conveyed in. However, there is a heterogeneity of the significance and direction of interest rate correlations. A further research reveals that especially the heterogeneous degree of TI leads to the different overlapped recession period of individual countries with the USA, resulting in heterogeneous behavior of interest rates among countries.

As a limitation of this paper, the forecasting power of interest rate correlations is not always significant in all countries. Despite this, the study has a profound implication that for those countries where the US accounts for the high proportion of trade, increase in conditional correlations can be a signal for future recessions. Especially, given a considerable portion of trade in GDP and the more sensitive trade activity of Korea to a contagious recession than a domestic recession, the conditional correlation measure is particularly useful for Korean policy makers.

Although many papers model interest rate co-movement as a function of macroeconomic condition, this paper provides the first evidence to show interest rate co-movement precede the macro shocks empirically. Furthermore, this paper determines the precise channel through which TI affects the time-varying behavior of interest rate co-movements before recessions.