Nominal interest rate policy rules and the feasibility of real interest rate control

In this paper the author builds a financial market model to demonstrate that policy aimed at reducing the variance in nominal interest rates reduces the information content of these variables. This has the undesirable effect of destabilizing real interest rates. The researcher demonstrates that nominal interest rate policy rules stabilize the component of the variance in the ex ante real interest rate attributable to the variance in the nominal rate. The variability of the expected inflation rate can, however, be increased by such policy rules, making the net effect of a nominal interest rate policy on the variance in the real interest rate ambiguous.     

International linkages between short-term real interest rates

Whereas previous studies have focused on the causal relation between nominal interest rates, this paper examines causal relationships between real rates for the United States and six other countries. Based on evidence from our full sample we find that U.S. and foreign interest rates are not highly informative for one another. This would suggest that even if the United States is regarded as a large player in international financial markets this does not necessarily translate into the transmission of U.S. real interest rates to other countries. However, an examination of various sub-periods of our sample reveals that this conclusion may be sensitive to the U.S. monetary policy regime. We also report results for linkages between European countries which indicate that Germany provides some information on real interest rates in France and the United Kingdom, but not in Italy. An analysis of various sub-periods for the European countries show that the result for France is not robust, with German rates having an impact only in the first period through March 1983. This latter evidence does not provide strong support for the hypothesis that Germany's monetary policy plays a dominant role in the European Monetary System. In general, we would argue that domestic factors play a prominent role in determining real interest rates, quite independently from the influence of interest rates from abroad.     

Technological change and the U.S. real interest rate

Economic theory predicts that the rate of technological growth exerts a positive influence on the real rate of interest. To test this hypothesis, I examine the relationship between the inflation-adjusted yield of the 90-day Treasury-Bill and two measures of innovation: the rate of growth of the stock of patents per worker and R&D spending relative to GDP. As theory predicts, from 1963 to 2008 the rate of interest responds positively to an increase in either measure. The point-estimates imply an elasticity of intertemporal substitution between one and two. The findings suggest that a change in the stance of monetary policy and a wave of innovation both contributed to the rise of real interest rates in the 1980s.     

The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting

Does the use of information on the past history of the nominal interest rates and inflation entail improvement in forecasts of the ex ante real interest rate over its forecasts obtained from using just the past history of the realized real interest rates? To answer this question we set up a univariate unobserved components model for the realized real interest rates and a bivariate model for the nominal rate and inflation which imposes cointegration restrictions between them. The two models are estimated under normality with the Kalman filter. It is found that the error-correction model provides more accurate one-period ahead forecasts of the real rate within the estimation sample whereas the unobserved components model yields forecasts with smaller forecast variances. In the post-sample period, the forecasts from the bivariate model are not only more accurate but also have tighter confidence bounds than the forecasts from the unobserved components model.     

A note on identification of multivariate time-series models

We analyze some of the difficulties of identifying multivariate time-series models with feedback, when carried through the two-stage procedure as in Haugh-Box (1977). We find that if the procedure is simplified, as in Jenkins (1979), the identified model can be seriously misspecified. When the procedure is applied correctly, it becomes extremely complicated, as in Granger-Newbold (1977). In such cases, there is a serious risk of overparametrization. The complication is mostly caused by the underlying structure of the multivariate model for the univariate innovations which can be considerably more complicated than the multivariate time-series model of interest.     

A multivariate GARCH in mean approach to testing uncovered interest parity: evidence from Asia-Pacific foreign exchange markets

The existence of time-varying risk premia in deviations from uncovered interest parity (UIP) is investigated based on a conditional capital asset pricing model (CAPM) using data from four Asia-Pacific foreign exchange markets. A parsimonious multivariate generalized autoregressive conditional heteroskedasticity in mean (GARCH-M) parameterization is employed to model the conditional covariance matrix of excess returns. The empirical results indicate that when each currency is estimated separately with an univariate GARCH-M parameterization, no evidence of time-varying risk premia is found except Malaysian ringgit. However, when all currencies are estimated simultaneously with the multivariate GARCH-M parameterization, strong evidence of time-varying risk premia is detected. As a result, the evidence supports the idea that deviations from UIP are due to a risk premium and not to irrationality among market participants. In addition, the empirical evidence found in this study points out that simply modeling the conditional second moments is not sufficient enough to explain the dynamics of the risk premia. A time-varying price of risk is still needed in addition to the conditional volatility. Finally, significant asymmetric world market volatility shocks are found in Asia-Pacific foreign exchange markets.     

Inflation and interest rate derivatives for FX risk management: Implications for exporting firms under real wealth

Firms that export goods face risks such as product price, cost, and exchange rate risks. Price and cost risks can substantially reduce the FX hedging performance in real wealth. We thus investigate hedging strategies that are intended to improve the performance of the FX hedge in real terms using inflation and interest rate derivatives. The impact of these additional instruments is not clear and has only been briefly analyzed in the hedging literature so far. For this purpose, we derive variance-minimizing hedge positions of an exporting firm. A cointegrated VAR and bootstrap methods are used to evaluate the efficiencies of several hedging strategies. While inflation derivatives work better in the short run, interest rate derivatives perform better over longer hedge horizons.     

Switching interest rate sensitivity regimes of U.S. Corporates

We study interest rate sensitivities of U.S. investment grade BBB-rated and high yield corporate bonds over the period of 2001–2016. Our methodology assesses the capital gains of corporate bond portfolios and risk-free government bond portfolios, using average coupon and blended yield indices for the U.S. market. For both, U.S. BBB and high yield corporate bonds, we evidence the switching, from positive to negative interest rate sensitivity, occurring over the transition from the normal economic conditions to the periods of economic distress and vice-versa. The proposed theoretical explanation of such binary behavior posits an interrelation between interest rate and creditworthiness of issuers, which varies according to the phases of the business cycle. This research advances an economic understanding of interest rate risk management and sheds light on how financial institutions may develop strategies that hedge against downside risk.     

Nonparametric efficiency analysis: A multivariate conditional quantile approach

This paper focuses on nonparametric efficiency analysis based on robust estimation of partial frontiers in a complete multivariate setup (multiple inputs and multiple outputs). It introduces α-quantile efficiency scores. A nonparametric estimator is proposed achieving strong consistency and asymptotic normality. Then if α increases to one as a function of the sample size we recover the properties of the FDH estimator. But our estimator is more robust to the perturbations in data, since it attains a finite gross-error sensitivity. Environmental variables can be introduced to evaluate efficiencies and a consistent estimator is proposed. Numerical examples illustrate the usefulness of the approach.     

A real options approach to valuing and negotiating licensing agreements

We apply real options modeling to a common pharmaceutical industry licensing arrangement to take into account various uncertainties and the flexibility value. The managerial flexibility is limited to the project abandonment option. We extend previous work by incorporating the phases required to bring the project from patent approval to market. We also incorporate a deterministic variable into the cash flow process that provides a realistic product lifecycle. We focus on the allocation of project value between licensor and licensee, i.e., the so-called “profit split” ratio (PSR) because it is commonly used in practice to negotiate terms. We find: (1) Ignoring the managerial flexibility in valuation may cause the licensee to either forego an acceptable deal or enter into an inferior deal. (2) The magnitude of project profitability as well as cost and sales uncertainty affects the licensor's bargaining power over compensation for granting abandonment flexibility to the licensee. (3) Managers must exercise care when estimating sales volatility because the flexibility value is more sensitive to sales volatility than it is to cost volatility. (4) Failure to incorporate the product lifecycle will produce suboptimal capital investment decisions.     

A non-linear model of the real US/UK exchange rate

This paper provides a framework for building and estimating non-linear real exchange rate models. The approach derives the stationary distribution from a continuous time error correction model and estimates this by MLE methods. The derived distribution exhibits a wide variety of distributional shapes including multimodality. The main result is that swings in the US/UK rate over the period 1973:3 to 1990:5 can be attributed to the distribution becoming bimodal with the rate switching between equilibria. By capturing these changes in the distribution, the non-linear model yields improvements over the random walk, the speculative efficiency model, and Hamilton's stochastic segmented trends model.     

Utility maximization in a stochastic affine interest rate and CIR risk premium framework: a BSDE approach

Decisions in Economics and Finance - This paper investigates optimal investment problems in the presence of stochastic interest rates and stochastic volatility under the expected utility...     

Measuring the natural rate of interest: A note on transitory shocks

We present evidence that the natural rate of interest is buffeted by both permanent and transitory shocks. We establish this result by estimating a benchmark model with Bayesian methods and loose priors on the unobserved drivers of the natural rate. When subject to transitory shocks, the median estimate for the US economy is more procyclical, displays a less marked secular decline, and is therefore higher following the Great Recession than most estimates in the literature.     

New evidence on the impact of financial leverage on beta risk: A time-series approach

The traditional estimation of a project’s cost of capital often requires leverage adjustments to beta. Several researchers have empirically investigated the relationship between the debt/equity ratio (D/E) and beta implied by such leverage adjustments. Typically, this has involved cross-sectional analysis of a sample of U.S. firms in selected industry classifications. The major contribution of the current study is to extend this evidence by investigating the relationship between financial leverage and beta using a time-series approach. This has several advantages over the cross-sectional approach. Our results reveal that while the estimated unlevered beta produced by the time-series approach is quite close to the theoretically implied unlevered beta, the mean difference between the two measures across our sample of 348 U.S. stocks is highly significant. The analysis also reveals that 30–40% of our full sample rejects a theoretical D/E restriction on the time-series model. Moreover, the results suggest that the restriction is much more likely to be rejected for stocks with high debt/equity ratios, which in general have low unlevered betas. Further, there is a considerable cross-sectional variation in the proportion of these rejections across industry groupings. Accordingly, these results suggest that due care needs to be applied when taking the traditional view of delevering beta risk.     

A Model Confidence Set approach to the combination of multivariate volatility forecasts

In predicting conditional covariance matrices of financial portfolios, practitioners are required to choose among several alternative options, facing a number of different sources of uncertainty. A first source is related to the frequency at which prices are observed, either daily or intradaily. Using prices sampled at higher frequency inevitably poses additional sources of uncertainty related to the selection of the optimal intradaily sampling frequency and to the construction of the best realized estimator. Likewise, the choices of model structure and estimation method also have a critical role. In order to alleviate the impact of these sources of uncertainty, we propose a forecast combination strategy based on the Model Confidence Set [MCS] to adaptively identify the set of most accurate predictors. The combined predictor is shown to achieve superior performance with respect to the whole model universe plus three additional competitors, independently of the MCS or portfolio settings.     

Monotonicity preserving regression techniques for interest rate term structure estimation: A note

Alternative methodologies are compared for measuring the term structure of interest rates via monotone approximations to the discount function. Some empirical comparisons using coupon bond data show that a simple linear methodology based on rational tension spline parametrizations turns out to yield the most efficient compromise between the conflicting goals of goodness of fit and smoothuess of the interpolaut Work supported by M.U.R.S.T. funds.     

Forecasts of US short-term interest rates: A flexible forecast combination approach

This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that, accounting for both regimes in interest rate dynamics, and combining forecasts from different models, helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long forecasting horizons.     

A survey on time-varying parameter Taylor rule: A model modified with interest rate pass-through

Today, the prime aim of central banking is to achieve price stability and, to a lesser extent, output stability. To this end, central banks use various monetary policy rules. This paper intends to provide a broad survey of the literature on Taylor-type monetary policy rules with a time-varying parameter (TVP) specification. To include the TVP feature, some modification is made in the monetary transmission mechanism of Taylor-type monetary policy models to account for the changing risk preference of individuals. In line with this approach, we introduce an interest rate pass-through specification of the monetary transmission process in a general equilibrium model to account for the varying perceptions of risk by individuals. We include an application for Turkey and estimate the time-variable parameters of the model by employing a structural extended Kalman filter (EKF). The results indicate that the EKF performs better than the standard Kalman filter in estimating the reaction function of the central bank.