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.     

A statistical comparison of the short-term interest rate models for Japan,U.S., and Germany

We propose a simple and practical model selection method for continuous time models. We apply the method to several continuous time short-term interest rate models using discrete time series data of Japan, U.S. and Germany. All the models can be easily estimated from discrete observations, and their performances can be evaluated in a uniform statistical framework. The models that allow dependence of volatility on the level of interest rates tend to perform well empirically. The degree of volatility dependence on the interest rate levels seems to be different across the countries. For the German data, we observe that a model with nonlinear drift performs better than the best linear drift model.     

Regime shifts in interest rate volatility

I find evidence of regime shifts in interest rate volatility using short-rate data from the U.S., the U.K., Japan, and Canada. The regime shifts, if unaccounted for, could lead to spurious volatility persistence when the volatility processes are estimated with the stochastic volatility (SVOL) model. In contrast, the apparent persistence in volatility drops sharply in three out of the four countries when I estimate the volatility processes with the regime-switching stochastic volatility (RSSV) model. I also contribute to the literature by showing how to account for correlation in the regime-switching stochastic volatility model, which is important for modeling asymmetric volatility.     

Beta Regimes for the Yield Curve

We propose an affine term structure model which accommodatesnonlinearities in the drift and volatility function of the short-terminterest rate. Such nonlinearities are a consequence of discretebeta-distributed regime shifts constructed on multiple thresholds.We derive iterative closed-form formula for the whole yieldcurve dynamics that can be estimated using a linearized Kalmanfilter. Fitting the model on US data, we collect empirical evidenceof its potential in estimating conditional volatility and correlationacross yields.     

What drives U.S. financial sector volatility? A Bayesian model averaging perspective

We investigate the driving forces behind the quarterly stock price volatility of firms in the U.S. financial sector over the period from 1990 to 2017. The driving forces represent a set of 28 economic indicators that are routinely used to detect financial instability and crises and correspond to the development of the financial, monetary, real, trade and fiscal sector as well as to the development of the bond and equity markets. The dimensionality and model choice uncertainty are addressed using Bayesian model averaging, which led to the identification of only seven variables that tend to systematically drive the stock price volatility of financial firms in the U.S.: housing prices, short-term interest rates, net national savings, default yield spread, and three credit market variables. We also confirm that our results are not an artefact of volatility associated with market downturns (for negative semi-volatility), as the results are similar even when market volatility is associated with market upsurge (positive semi-volatility). Given the identified drivers, our results provide supporting empirical evidence that dampening credit cycles might lead to decreased volatility in the financial sector.     

The reaction of the Australian financial markets to the interest rate news from the Reserve Bank of Australia and the U.S. Fed

This paper provides comprehensive evidence on the impacts of the Reserve Bank of Australia's (RBA) and the U.S. Fed's target interest rate announcement news on the Australian financial markets over the period 1998–2006. The RBA's news had a significant impact on the first moments of market returns/changes in line with a priori expectations, and the conditional volatility in most of the markets was significantly higher following the news. Asymmetric news effect is also observed for the Australian interest rates where markets tended to respond more strongly to unexpected rate rises than rate falls. While the U.S. Fed's news influenced only the USD/AUD exchange rate, the Australian market volatility was significantly lower in all market segments following the Fed's news.     

Short-run money demand

The conventional wisdom holds that the short-run demand for money is unstable. This paper challenges the conventional view by finding a stable demand for M1 in U.S. data from 1959 through 1993. The approach follows previous work in interpreting long-run money demand as a cointegrating relation, and it uses Goldfeld's partial-adjustment model to interpret short-run dynamics. The key innovation is the choice of the interest rate in the money demand function. Most previous work uses a short-term market rate, but this paper uses the average return on “near monies”—the savings accounts and money market mutual funds that are close substitutes for M1. This choice helps rationalize the behavior of money demand; in particular, the increase in the volatility of velocity after 1980 is explained by increased volatility in the returns on near monies.     

Asymmetric Mean Reversion in European Interest Rates: A Two-factor Model

Abstract

This paper tests for asymmetric mean reversion in European short-term interest rates using a combination of the interest rate models introduced by Longstaff and Schwartz (Longstaff, F.A., Schwarts, E.S. (1992) Interest rate volatility and the ferm structure: A two factor general equilibrium model, Journal of Finance, 48, pp. 1259–1282.) and Bali (Bali, T. (2000) Testing the empirical performance of stochastic volatility models of the short-term interest rates, Journal of Financial and Quantitative Analysis, 35, pp. 191–215.). Using weekly rates for France, Germany and the United Kingdom, it is found that short-term rates follow in all instances asymmetric mean reverting processes. Specifically, interest rates exhibit non-stationary behavior following rate increases, but they are strongly mean reverting following rate decreases. The mean reverting component is statistically and economically stronger thus offsetting non-stationarity. Volatility depends on past innovations past volatility and the level of interest rates. With respect to past innovations volatility is asymmetric rising more in response to positive innovations. This is exactly opposite to the asymmetry found in stock returns.     

Likelihood-based specification analysis of continuous-time models of the short-term interest rate

An extensive collection of continuous-time models of the short-term interest rate is evaluated over data sets that have appeared previously in the literature. The analysis, which uses the simulated maximum likelihood procedure proposed by Durham and Gallant (2002), provides new insights regarding several previously unresolved questions. For single factor models, I find that the volatility, not the drift, is the critical component in model specification. Allowing for additional flexibility beyond a constant term in the drift provides negligible benefit. While constant drift would appear to imply that the short rate is nonstationary, in fact, stationarity is volatility-induced. The simple constant elasticity of volatility model fits weekly observations of the three-month Treasury bill rate remarkably well but is easily rejected when compared with more flexible volatility specifications over daily data. The methodology of Durham and Gallant can also be used to estimate stochastic volatility models. While adding the latent volatility component provides a large improvement in the likelihood for the physical process, it does little to improve bond-pricing performance.     

Fundamental Properties of Bond Prices in Models of the Short-Term Rate

This article develops restrictions that arbitrage-constrainedbond prices impose on the short-term rate process in order tobe consistent with given dynamic properties of the term structureof interest rates. The central focus is the relationship betweenbond prices and the short-term rate volatility. In both scalarand multidimensional diffusion settings, typical relationshipsbetween bond prices and volatility are generated by joint restrictionson the risk-neutralized drift functions of the state variablesand convexity of bond prices with respect to the short-termrate. The theory is illustrated by several examples and is partiallyextended to accommodate the occurrence of jumps and default.     

The Stochastic Volatility of Short-Term Interest Rates: Some International Evidence

This paper estimates a stochastic volatility model of short-term riskless interest rate dynamics. Estimated interest rate dynamics are broadly similar across a number of countries and reliable evidence of stochastic volatility is found throughout. In contrast to stock returns, interest rate volatility exhibits faster mean-reverting behavior and innovations in interest rate volatility are negligibly correlated with innovations in interest rates. The less persistent behavior of interest rate volatility reflects the fact that interest rate dynamics are impacted by transient economic shocks such as central bank announcements and other macroeconomic news.     

The spillover effects of target interest rate news from the U.S. Fed and the European Central Bank on the Asia-Pacific stock markets

This paper provides comprehensive evidence on the spillover effects of the U.S. Fed's and the European Central Bank (ECB)’s target interest rate news on the market returns and return volatilities of 12 stock markets in the Asia-Pacific over the period 1999–2006. The news spillover effects on the returns are generally consistent with the literature where a majority of stock markets shows significant negative returns in response to unexpected rate rises. While the results of the speed of adjustment for the Fed's news are mixed across the markets, the ECB news was absorbed slowly, in general. The return volatilities were higher in response to the interest rate news from both sources. In addition, both the Fed and the ECB news elicited tardy or persisting volatility responses. These findings have important implications for all levels of market participants in the Asia-Pacific stock markets.     

Interest Rate Volatility and the Term Structure: A Two-Factor General Equilibrium Model

We develop a two-factor general equilibrium model of the term structure. The factors are the short-term interest rate and the volatility of the short-term interest rate. We derive closed-form expressions for discount bonds and study the properties of the term structure implied by the model. The dependence of yields on volatility allows the model to capture many observed properties of the term structure. We also derive closed-form expressions for discount bond options. We use Hansen's generalized method of moments framework to test the cross-sectional restrictions imposed by the model. The tests support the two-factor model.     

Modeling volatility and changes in the swap spread

We investigate the determinants of changes in U.S. interest rate swap spreads using a model that explicitly allows for volatility interactions between swaps of different terms to maturity. Changes in the swap spread are found to be positively related to interest rate volatility, to changes in the default risk premium in the corporate bond market, and to changes in the liquidity premium for government securities. Swap spread changes are negatively related to changes in the level of interest rates and changes in the slope of the term structure. We also find that there is a strong and significant volatility interaction among spreads for swaps of different maturities and that the process for the conditional variance of the spread is highly persistent across all maturities.     

Words matter: Market responses to changes in U.S. and Chinese trade-related internet search frequency under different U.S. administrations

This paper employs internet search frequency data as a proxy for investor interest in innovations in stock market volatility surrounding the U.S./China trade relationship. The study documents a positive correlation between U.S. and China trade-related investor attention and market-wide share-price volatility in both nations—especially during the Trump administration. In addition, the study confirms previously established volatility spillover effects between U.S. and Chinese markets, which, again, are strongest during the Trump presidency. Overall, the results of the study support the validity of using publicly-available internet search data as a proxy for investor attention.     

Identifying volatility risk premia from fixed income Asian options

Fixed income options are frequently adopted by companies to hedge interest rate risk. Their payoff dependence on the cumulative short-term rate makes them particularly informative about interest rate volatility risk. Based on a joint dataset of bonds and Asian interest rate options, we study the interrelations between bond and volatility risk premia in a major emerging fixed income market. We propose a dynamic term structure model that generates an incomplete market compatible with a preliminary empirical analysis of the dataset. Approximation formulas for at-the-money Asian option prices avoid the use of computationally intensive Fourier transform methods, allowing for an efficient implementation of the model. The model generates a bond risk premium strongly correlated with a widely accepted emerging market benchmark index (EMBI-Global), and a negative volatility risk premium, consistent with the use of Asian options as insurance in this market.     

美联储政策变化、国际资本流动与宏观经济波动

本文构建包含国际投资者、外资企业和银行流动性冲击的DSGE模型来探究美联储货币政策变动和政策不确定性对我国宏观经济的影响和作用机制。研究发现:(1) 美联储加息会导致我国产出、投资和通货膨胀的下降、汇率贬值、国际资本外流和银行系统流动性紧张。随着金融摩擦程度的增加和银行杠杆率的上升,美联储加息对我国产出、投资和资产价格的负面影响会进一步增强。(2) 美联储货币政策不确定性的增加会直接导致外资企业的投资、劳动需求和产出的下降,并对我国总产出、总投资和资产价格产生明显的负向外溢效应,进一步加剧我国宏观经济的波动。(3)为应对美联储的利率变动,适当限制国际资本流动能有效稳定我国经济波动和改善社会福利,而实施固定汇率和央行盯住美国利率的政策会加大宏观经济的波动,并导致社会福利下降。     

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.     

Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany

The occurrence and the transmission of large shocks in international equity markets is of essential interest to the study of market integration and financial crises. To this aim, implied market volatility allows to monitor ex ante risk expectations in different markets. We investigate the behavior of implied market volatility indices for the U.S. and Germany under a straightforward mean reversion model that allows for Poisson jumps. Our empirical findings for daily data in the period 1992 to 2002 provide evidence of significant positive jumps, i.e. situations of market stress with positive unexpected changes in ex ante risk assessments. Jump events are mostly country-specific with some evidence of volatility spillover. Analysis of public information around jump dates indicates two basic categories of events. First, crisis events occurring under spillover shocks. Second, information release events which include three subcategories, namely—worries about as well as actual—unexpected releases concerning U.S. monetary policy, macroeconomic data and corporate profits. Additionally, foreign exchange market movements may cause volatility shocks.     

Modeling interest rate volatility: A Realized GARCH approach

We propose using a Realized GARCH (RGARCH) model to estimate the daily volatility of the short-term interest rate in the euro–yen market. The model better fits the data and provides more accurate volatility forecasts by extracting additional information from realized measures. In addition, we propose using the ARMA–Realized GARCH (ARMA–RGARCH) model to capture the volatility clustering and the mean reversion effects of interest rate behavior. We find the ARMA–RGARCH model fits the data better than the simple RGARCH model does, but it does not provide superior volatility forecasts.