Short-term Interest Rate Volatility Research Articles

Volatility patterns of short-term interest rate futures

A general question in finance is whether the volatility of the price of futures contracts follows any particular trend over the contract’s life. In this study, we contribute to the debate by empirically analyzing the trend of the term structure of the volatility of short-term interest rates (STIR) futures prices. Using data on the Eurodollar, Euribor, and Short-Sterling futures contracts for the period between 2000 and 2018, we model the volatility of each individual contract considering time to expiration and trading activities. Furthermore, we investigate whether these trends change according to overall economic conditions. We find that STIR futures behave differently than futures on other underlying assets and that, most of the time, STIR futures price volatility declines as the contract approaches expiration. Moreover, the relation between volatility and time to maturity depends on market conditions and trading activities, and it is non-linearly related to the observation period.

Time Series Dynamics of Short Term Interest Rates in Turkey

Interest rate functions as the cornerstone for the heavy majority of the financial models. The high volatility in interest rates in the financial crisis of 2008/09 and resulting increased uncertainty led many researchers to focus on modeling the dynamics of changes in short term interest rates. This study aims to analyze the volatility of short-term interest rate in Turkey in terms of overnight repo rate and to forecast this rate for the next six months by modelling this volatility. For this purpose, the ARCH family models like ARCH, GARCH and EGARCH were preferred to use since they are the most common methods in the literature. Using the weekly frequency data for the period of January 2002 - January 2021, the model that best describes the stochastic volatility in the data was found to be the GARCH (1.1) model. As a result of the fact that the in-sample estimates were found sufficient, the interest rate estimates for the next 6 months were realized.

Alternative characterization of volatility of short-term interest rate

Most reported stochastic volatility (SV) model for interest rates only deals with an AR specification for the latent factor process. We show in this paper the technical details for specifying the SV model for interest rates that includes an ARMA structure, a jump component and additional exogenous variables for the latent factor process. We demonstrate the efficacy of this approach with an application to the US short-term interest rate data. We find that the elasticity parameter of the variance is closer to 0.5, i.e., similar to that of the Cox–Ingersoll–Ross (1985) model of interest rates. This is quite a contrast to the finding Chan et al. [Chan, KC, GA Karolyi, F Longstaff and A Sanders (1992). The volatility of short-term interest rates: An empirical comparison of alternative models of term structure of interest rates, Journal of Finance, 47, 1209–1227]. who found the elasticity to be close to 1.5.

The Term Structure of Short-Term Interest Rate Futures Volatility

A general question in finance is whether the volatility of futures contracts price follows any particular trend over the contract’s life. In this study, we contribute to the debate by analyzing the term structure of the volatility of short-term interest rates (STIR) futures prices to empirically assess whether a particular trend consistently prevails or if there is no trend at all. Using data on the Eurodollar, Euribor, and Short-Sterling futures contracts for the period between 2000 and 2018, we model the volatility of each individual contract considering time to expiration, financial markets conditions, and trading activity. Furthermore, our dataset arrangement allows us to investigate whether these trends change according to overall economic conditions. The results show that STIR futures behave differently than futures on other underlying assets and that, most of the time, STIR futures price volatility declines as the contract approaches expiration. However, the relation between volatility and time to maturity depends on market conditions and trading activity, and the relation appears to be non-linear.

Modelling and forecasting short-term interest rate volatility: A semiparametric approach

This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rates. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, level effect and serial dependence in the conditional variance. Moreover, the semiparametric approach yields robust volatility estimates even if the short rate drift function and the underlying innovation distribution are misspecified. Empirical investigation with the U.S. three-month Treasury bill rates suggests that the semiparametric procedure produces superior in-sample and out-of-sample forecast of short rate changes volatility compared with the widely used single-factor diffusion models. This forecast improvement has implications for pricing interest rate derivatives.

The Optimal Width of the Central Bank Standing Facilities Corridor and Banks' Day - to - Day Liquidity Management

Containing short-term volatility of the overnight interest rate is normally considered the main objective of central bank standing facilities. This paper develops a simple stochastic model to show how the width of the central bank standing facilities corridor affects banks’ day-to-day liquidity management and the volatility of the overnight rate. It is shown that the wider the corridor, the greater the interbank turnover, the leaner the central bank’s balance sheet (i.e. the lower the average recourse to standing facilities) and the greater short-term interest rate volatility. The obtained relationships are matched with central bank preferences to obtain an optimal corridor width. The model is tested against euro area and Hungarian daily data encompassing the financial crisis that began in 2007.

Modelling and Forecasting Short-Term Interest Rate Volatility: A Semiparametric Approach

This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rate. This method is compared in its ability to capture the dynamics of short rate volatility to a class of one-factor diffusion models where the conditional variance is serially correlated and levels dependent. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, levels effect and serial dependence in the conditional variance. The empirical evidence based on U.S. three-month Treasury bill rates further indicates that the semiparametric procedure is better than the widely used single-factor diffusion models in forecasting the future volatility of interest rate changes. The improvement in modelling short rate volatility using the new procedure has implications for pricing interest rate derivatives.

Are levels effects important in out-of-sample performance of short rate models?

This paper derives short-term interest rate volatility forecasts from various interest rate models. While models that specify both GARCH and levels effects are superior in their forecasts accuracy, they systematically under predict interest rate volatility more frequently than simple short rate models.

THE INFLUENCE OF THE INSTRUMENTS OF MONETARY POLICY OF THE NATIONAL BANK OF POLAND ON THE LEVEL AND VARIABILITY OF SHORT-TERM RATES OF INTEREST

The National Bank of Poland influences on interbank market throughout three instruments: reserve requirements, standing facilities and open market operations. This article describes the impact of these tools on short-term interest rates on the interbank market. Nowadays limiting volatility of short-term interest rates on the interbank market is the most important function of reserve requirements. They help to stabilise the overnight rate because the requirements are lagged and averaged. Standing facilities are safety valves for banking system. Banks can use credit facility when they urgently need liquidity or deposit facility when they have surpluses. Simultaneously, standing facilities indicate corridor of market rates volatility. These standing facilities’ features allow them to limit overnight rate volatility – as well as reserve requirements do. Open market operations are the principal instrument for maintaining short-term interest rates at a level consistent with established inflation target being implemented. Minimal interest rate for main operation - issuing 7-day NBP money bills - is announced by the Monetary Policy Council. One-week interest rate on the interbank market fluctuates around this official interest rate.

Testing the stabilization hypothesis in the UK short-term interest rates: Evidence from a GARCH-X model

The objective of this paper is to examine the validity of one of the recurring arguments made against futures markets that they give rise to price instability. The paper concentrates on the impact of futures trading on the spot market volatility of short-term interest rates. The analytical framework employed is based on a new statistical approach aiming to reconcile the traditional models of short-term interest rates and the conditional volatility processes. More specifically, this class of models aims to capture the dynamics of short-term interest rate volatility by allowing volatility to depend on both scale effects and information shocks. Using a GARCH-X and asymmetric GARCH-X model four main conclusions emerge from the present study. First, the empirical results suggest that there is an indisputable change in the nature of volatility with evidence of mean reversion after the onset of futures trading. Second, the information flow into the market has improved as a result of futures trading. Third, a stabilization effect has been detected running from the futures market to the cash market by lowering volatility levels and decreasing the risk in the spot market. Finally, trying to capture the leverage effect the findings suggest that positive shocks have a greater impact on volatility than negative shocks.

Are there nonlinearities in short-term interest rates?

The present paper investigates the characteristics of short-term interest rates in several countries. We examine the importance of nonlinearities in the mean reversion and volatility of short-term interest rates. We examine various models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate.We find that different markets require different models. In particular, we find evidence of nonlinear mean reversion in some of the countries that we examine, linear mean reversion in others and no mean reversion in some countries. For all countries we examine, there is strong evidence of the need for the volatility of interest rate changes to be highly sensitive to the level of the short-term interest rate. Out-of-sample forecasting performance of one-factor short rate models is poor, stemming from the inability of the models to accommodate jumps and discontinuities in the time series data.

Determinants of Treasury-LIBOR Swap Spreads

Using data from the Treasury versus London Interbank Offer Swap Rates (LIBOR) for October 1987 to June 1998, this paper examines the determinants of swap spreads in the Treasury-LIBOR interest rate swap market. This study hypothesizes Treasury-LIBOR swap spreads as a function of the Treasury rate of comparable maturity, the slope of the yield curve, the volatility of short-term interest rates, a proxy for default risk, and liquidity in the swap market. The study finds that, in the long-run, swap spreads are negatively related to the yield curve slope and liquidity in the swap market. We also find that swap spreads are positively related to the short-term interest rate volatility. In the short-run, swap market's response to higher default risk seems to be higher spread between the bid and offer rates.

Volatility transmission between stock and bond markets

A two-factor no-arbitrage model is used to provide a theoretical link between stock and bond market volatility. While this model suggests that short-term interest rate volatility may, at least in part, drive both stock and bond market volatility, the empirical evidence suggests that past bond market volatility affects both markets and feeds back into short-term yield volatility. The empirical modelling goes on to examine the (time-varying) correlation structure between volatility in the stock and bond markets and finds that the sign of this correlation has reversed over the last 20 years. This has important implications far portfolio selection in financial markets.

Regime-switching stochastic volatility and short-term interest rates

Abstract In this paper, we introduce regime switching in a two-factor stochastic volatility (SV) model to explain the behavior of short-term interest rates. We model the volatility of short-term interest rates as a stochastic volatility process whose mean is subject to shifts in regime. We estimate the regime-switching stochastic volatility (RSV) model using a Gibbs Sampling-based Markov Chain Monte Carlo algorithm. In-sample results strongly favor the RSV model in comparison to the single-state SV model and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family of models. Out-of-sample results are mixed and, overall, provide weak support for the RSV model.

Money market operations and short-term interest rate volatility in the United Kingdom

This study examines whether in the United Kingdom the choice of the operational framework for monetary policy has been systematically related to patterns in money market rates. It first focuses on the Bank of England's policy target, the two-week repo rate. The tests indicate that tighter spreads between the two-week market rate and the official repo rate result in lower money market volatility at the very short end of the money market curve. The effects at the longer end are much weaker. But no evidence is found of transmission of two-week volatility along the money market curve. In contrast to many other central banks, the Bank of England does not employ an operating target for the overnight rate. No evidence is found that allowing greater variation in overnight rates undermines efforts of the central bank to keep market interest rates in alignment with its monetary policy target. The results further indicate that volatility of rates at the very short end of the UK money market yield curve has declined ...

Money Market Operations and Volatility of UK Money Market Rates

The Bank of England implements UK monetary policy by influencing short-term interest rates in its money market operations. The way in which the Bank operates in the market has changed significantly over time, but the aim throughout has been to ensure that the behaviour of short-term interest rates is consistent with monetary policy decisions, whether made by the Chancellor of the Exchequer or, since 1997, by the Bank's own Monetary Policy Committee. Operational choices by the central bank, together with developments in the markets themselves, are likely to have affected the volatility of short-term interest rates. This article outlines various measures of volatility in sterling money markets.

How is the Debt Managed? Learning from Fiscal Stabilizations

This paper provides evidence on the behavior of public debt managers during fiscal stabilizations. Such episodes provide valuable information on the way debt instruments are chosen because they allow to overcome the problem that policymakers' expectations of interest rates are generally not observable. We find that governments increase the share of fixed-rate long-term debt denominated in the domestic currency the higher is the conditional volatility of short-term interest rates, the lower are long-term interest rates, and the stronger is the fall in long-term rates that follows the announcement of the stabilization program. By contrast, conventional measures of the relative cost of issuing long-term debt, such as the long-short interest-rate spread, are not significant. This evidence suggests that debt managers tend to prefer long to short maturity debt because they are concerned about the risk of refinancing at higher than expected interest rates. However, when long-term rates are high relative to their expectations, they issue short maturity debt to minimize borrowing costs.

How is the Debt Managed? Learning from Fiscal Stabilizations

This paper examines public debt management during episodes of fiscal stabilization when long–term interest rates are generally higher than governments’ expectations of future rates. We find that governments increase the share of fixed–rate long–term debt denominated in the domestic currency, the higher is the conditional volatility of short–term interest rates, the lower are long–term interest rates, and the stronger is the fall in long–term rates that follows the announcement of the stabilization program. This evidence suggests that governments tend to prefer long to short maturity debt because they are concerned about refinancing risk. However, when long–term rates are high relative to their expectations, they issue short maturity debt to minimize borrowing costs. JEL classification: E63; H63

An empirical comparison of continuous time models of the short term interest rate

This article tests the performance of a wide variety of well‐known continuous time models—with particular emphasis on the Black, Derman, and Toy (1990; henceforth BDT) term structure model—in capturing the stochastic behavior of the short term interest rate volatility. Many popular interest rate models are nested within a more flexible time‐varying BDT framework that allows us to compare the models and find the proper specification of the dynamics of short rates. The empirical results indicate that the equilibrium models that do not allow the drift and diffusion parameters to vary over time and parameterize the volatility only as a function of interest rate levels overemphasize the sensitivity of volatility to the level of interest rate and fail to model adequately the serial correlation in conditional variances. On the other hand, the GARCH‐based arbitrage‐free models with time‐dependent parameters in the drift and diffusion functions define the volatility only as a function of unexpected information shocks and fail to capture adequately the relationship between interest rate levels and volatility. This study shows that the most successful models in capturing the dynamics of short term interest rates are those that introduce time‐dependent parameters to the short rate process and define the conditional volatility as a function of both the interest rate levels and the last period's unexpected news. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 777–797, 1999

Managing the Public Debt in Fiscal Stabilizations: The Evidence

This paper provides evidence on the behavior of public debt managers during fiscal stabilizations in OECD countries over the last two decades. We find that debt maturity tends to lengthen the more credible is the program, the lower is the long-term interest rate and the higher is the volatility of short-term interest rates. We show that this debt issuing strategy is consistent with optimal debt management if information between the government and private investors is asymmetric, as is usually the case at the outset of a stabilization attempt when private investors may lack full confidence in the announced budget cuts.