Interest Rate Forecasts Research Articles

Why are Target Interest Rate Changes so Persistent?

While the degree of policy inertia in central banks' reaction functions is a central ingredient in theoretical and empirical monetary economics, the source of the observed policy inertia in the U.S. is controversial, with tests of competing hypotheses such as interest-smoothing and persistent-shocks theories being inconclusive. This paper employs real time data; nested specifications with flexible time series structures; narratives; interest rate forecasts of the Fed, financial markets, and professional forecasters; and instrumental variables to discriminate competing explanations of policy inertia. The presented evidence strongly favors the interest-smoothing explanation and thus can help resolve a key puzzle in monetary economics.

Central Bank Communication and the Perception of Monetary Policy by Financial Market Experts

This paper investigates how financial market experts perceive the interest rate policy of the European Central Bank (ECB). Assuming a Taylor-rule-type reaction function of the ECB, we use qualitative survey data on expectations about the future interest rate, inflation, and output to discover the sources of individual interest rate forecast errors. Based on a panel random coefficient model, we show that financial experts have systematically misperceived the ECB's interest rate rule. While the perception of monetary policy regarding inflation has become more accurate since the clarification of the ECB's monetary policy strategy in May 2003, the experts' misperception regarding the ECB's reaction to output has increased in the financial crisis.

RETURN RISK MAP IN A FUZZY ENVIRONMENT

Within the framework of Assets Liability Management, we understand that immunization is the main method to assure a certain yield in a future date departing from an initial portfolio. Although the objective of passive strategies is to design a portfolio that will achieve the performance of a predetermined benchmark, active bond management strategies rely on expectations of interest rate movements or changes in yield-spread relationships. However, the variation of the duration increases the risk of a portfolio, that why the decision maker will have to choose the combination of expected return (mid-point of the fuzzy number) and risk (width of the fuzzy number) which provides the higher utility. Finally, the construction of a fuzzy return risk map will allow the DM to know the over risk and the over return as regards immunization strategy for each duration and for each risk aversion of the DM. The construction of a risk return map presents the results in an appropriate way. This methodology will help the DM to choose the best duration for the DM interest rate forecast

‘Ex-ante’ Taylor rules – Newly discovered evidence from the G7 countries

This paper addresses the question of whether financial market participants apply the framework of Taylor-type rules in their forecasts for the G7 countries. To this end, we use the Consensus Economic Forecast poll providing us a unique data set of inflation rate, interest rate and growth rate forecasts for the time period 1989–2008. We provide empirical evidence that financial market participants incorporate Taylor-type rules in their forecasts. Thus, the paper uses ex-ante data for the estimation of Taylor rules. This is a new approach, because so far only ex-post (revised) or real-time data have been applied.

Eurocurrency interest rate linkages: A frequency domain analysis

We investigate relations between Eurocurrency interest rates using frequency domain methods, which permit us to decompose test statistics into short-term and long-term causality measures. We document significant linkages between international interest rates. Specifically, we show that the euro plays an increasingly important role in global money markets. In fact, a subperiod analysis suggests that the euro interest rate leads the US dollar rate during the recent financial crisis. We discuss the implications of the findings for understanding global monetary policy dynamics as well as modeling and forecasting of short-term interest rates.

Why Do Financial Market Experts Misperceive Future Monetary Policy Decisions

This paper investigates why flnancial market experts misperceive the interest rate policy of the European Central Bank (ECB). Assuming a Taylor{rule{type reaction function of the ECB, we use qualitative survey data on expectations about the future interest rate, in∞ation, and output to discover the sources of individual interest rate forecast errors. Based on a panel random coe‐cient model, we show that flnancial experts have systematically misperceived the ECB’s interest rate rule. However, although experts tend to overestimate the impact of in∞ation on future interest rates, perceptions of monetary policy have become more accurate since clariflcation of the ECB’s monetary policy strategy in May 2003. We flnd that this improved communication has reduced disagreement over the ECB’s response to expected in∞ation during the flnancial crisis.

How well do experts predict interbank loan rates and spreads?

This study examines Blue Chip forecasts of the 3-month London interbank offered rate (LIBOR), federal funds rate (FFR), and LIBOR–FFR for 1988–2008. We show that the interest rate (spread) forecasts, while directionally accurate, imply asymmetric (symmetric) loss.

Cointegration rank switching model: an application to forecasting interest rates

This paper proposes a new forecasting method in which the cointegration rank switches at unknown times. In this method, time series observations are divided into several segments, and a cointegrated vector autoregressive model is fitted to each segment. The goodness of fit of the global model, consisting of local models with different cointegration ranks, is evaluated using the information criterion (IC). The division that minimizes the IC defines the best model. The results of an empirical application to the US term structure of interest rates and a Monte Carlo simulation suggest the efficacy as well as the limitations of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.

Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters

In this article we introduce time-varying parameters in the dynamic Nelson–Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson–Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive factors. We extend this framework in two directions. First, the factor loadings in the Nelson–Siegel yield model depend on a single loading parameter that we treat as the fourth latent factor. Second, we specify the overall volatility as a generalized autoregressive conditional heteroscedasticity (GARCH) process. We present empirical evidence of considerable increases in within-sample goodness of fit for these advances in the dynamic Nelson–Siegel model.

Term Structure Forecasting using Macro Factors and Forecast Combination

We examine the importance of incorporating macroeconomic information and, in particular, accounting for model uncertainty when forecasting the term structure of U.S. interest rates. We start off by analyzing and comparing the forecast performance of several individual term structure models. Our results confirm and extend results found in previous literature that adding macroeconomic information, through factors extracted from a large number of individual series, tends to improve interest rate forecasts. We then show, however, that the predictive power of individual models varies over time significantly. Models with macro factors are the more accurate in and around recession periods. Models without macro factors do particularly well in low-volatility subperiods such as the late 1990s. We demonstrate that this problem of model uncertainty can be mitigated by combining individual model forecasts. Combining forecasts leads to encouraging gains in predictability, especially for longer-dated maturities, and importantly, these gains are consistent over time.

Consumption and Real Exchange Rates in Professional Forecasts

Standard models of international risk sharing with complete asset markets predict a positive association between relative consumption growth and real exchange-rate depreciations across countries. The striking lack of evidence for this link - the consumption/real-exchange-rate anomaly or Backus-Smith puzzle - has prompted research on risk-sharing indicators with incomplete asset markets. That research generally implies that the association holds in forecasts, rather than realizations. Using professional forecasts for 28 countries for 1990-2008 we find no such association, thus deepening the puzzle. Independent evidence on the weak link between forecasts for consumption and real interest rates suggests that the presence of 'hand-to-mouth' consumers may help to explain the evidence.

Dimension-Invariant Dynamic Term Structures

We model term structure dynamics using a recursive cascade of heterogeneously persistent factors. The cascade naturally orders the factors by their adjustment speeds, and generates smooth zero-coupon bond prices and forward curves in closed form. For a class of specifications, the number of parameters is invariant to the size of the state space, and the term structure converges to a stochastic limit as the number of factors goes to infinity. The cascade construction thereby defeats the curse of dimensionality associated with general affine models. Using a panel of interest rates, we estimate specifications with from one to 15 factors and only five parameters. High-dimensional versions of the model fit empirical yield curves almost perfectly in sample, with root mean squared errors of less than one basis point, while maintaining reasonable maximal Sharpe ratios. Out-of-sample interest rate forecasts significantly outperform prior benchmarks.

Simple Rules Versus Optimal Policy: What Fits?

We estimate a small open-economy DSGE model for Norway with two specifications of monetary policy: a simple instrument rule and optimal policy based on an intertemporal loss function. The empirical fit of the model with optimal policy is as good as the model with a simple rule. This result is robust to allowing for misspecification following the DSGE-VAR approach proposed by Del Negro and Schorfheide (2004). The interest rate forecasts from the DSGE-VARs are close to Norges Bank's official forecasts since 2005. One interpretation is that the DSGE-VAR approximates the judgment imposed by the policymakers in the forecasting process.

Tips from TIPS: The Informational Content of Treasury Inflation-Protected Security Prices

TIPS breakeven inflation rate, defined as the difference between nominal and TIPS yields of comparable maturities, is potentially useful as a real-time measure of market inflation expectations. In this paper, we provide evidence that a fairly large TIPS liquidity premium existed until recently, using a multifactor no-arbitrage term structure model estimated with nominal and TIPS yields, inflation and survey forecasts of interest rates. Ignoring the TIPS liquidity premiums leads to counterintuitive implications for inflation expectations and inflation risk premium, and produces large pricing errors for TIPS. In contrast, models incorporating a TIPS liquidity factor generate much better fit for these variables and reveal a TIPS liquidity premium that was until recently quite large (~1%) but has come down in recent years, consistent with the common perception that TIPS market grew and liquidity conditions improved. Our results indicate that after taking proper account of the liquidity conditions in the TIPS market, the movement in TIPS breakeven inflation rate can provide useful information for identifying real yields, expected inflation and inflation risk premium.

Term Structure Forecasting Using Macro Factors and Forecast Combination

We examine the importance of incorporating macroeconomic information and, in particular, accounting for model uncertainty when forecasting the term structure of U.S. interest rates. We start off by analyzing and comparing the forecast performance of several individual term structure models. Our results confirm and extend results found in previous literature that adding macroeconomic information, through factors extracted from a large number of individual series, tends to improve interest rate forecasts. We then show, however, that the predictive power of individual models varies over time significantly. Models with macro factors are the more accurate in and around recession periods. Models without macro factors do particularly well in low-volatility subperiods such as the late 1990s. We demonstrate that this problem of model uncertainty can be mitigated by combining individual model forecasts. Combining forecasts leads to encouraging gains in predictability, especially for longer-dated maturities, and importantly, these gains are consistent over time.

Why Do Financial Market Experts Misperceive Future Monetary Policy Decisions?

This paper investigates why financial market experts misperceive the interest rate policy of the European Central Bank (ECB). Assuming a Taylor-rule-type reaction function of the ECB, we use qualitative survey data on expectations about the future interest rate, inflation, and output to discover the sources of individual interest rate forecast errors. Based on a panel random coefficient model, we show that financial experts have systematically misperceived the ECB's interest rate rule. However, although experts tend to overestimate the impact of inflation on future interest rates, perceptions of monetary policy have become more accurate since clarification of the ECB's monetary policy strategy in May 2003. We find that this improved communication has reduced disagreement over the ECB's response to expected inflation during the financial crisis.

Stochastic interest rates in the analysis of energy investments: Implications on economic performance and sustainability

A systematic impact assessment of stochastic interest and inflation rates on the analysis of energy investments is presented. A real-options algorithm has been created for this task. Constant interest rates incorporating high risk premium have been extensively used for economic calculations, within the framework of traditional direct cash flow methods, thus favouring immediate, irreversible investments in the expense of, sometimes, insubstantially low anticipated yields. In this article, not only incomes and expenses but also interest and inflation rates are considered stochastically evolving according to specific probabilistic models. The numerical experiments indicated that the stochastic interest rate forecasts fluctuate in such low levels that may signal delayed investment entry in favour of higher expected yields. The implementation of stochastically evolving interest rates in energy investment analysis may have a controversial effect on sustainability. Displacements of inefficient plants may be significantly delayed, thus prolonging high CO2 emission rates. Under the current CO2 allowance prices or their medium-term forecasts, this situation may not be improved and flexible policy interventions may be necessitated.

Does Curvature Enhance Forecasting?

In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential three-factor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to generate volatility and to capture nonlinearities in the yield curve, leading to a significant improvement of forecasting ability. The model is tested against the original Diebold and Li model and some other benchmarks. Based on a forecasting experiment with Brazilian fixed income data, it obtains significantly lower bias and root mean square errors for most examined maturities, and under three different forecasting horizons. Robustness tests based on two sub-sample analyses partially confirm the favorable results.

DOES CURVATURE ENHANCE FORECASTING?

In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential three-factor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to generate volatility and to capture nonlinearities in the yield curve, leading to a significant improvement of forecasting ability. The model is tested against the original Diebold and Li model and some other benchmarks. Based on a forecasting experiment with Brazilian fixed income data, it obtains significantly lower bias and root mean square errors for most examined maturities, and under three different forecasting horizons. Robustness tests based on two sub-sample analyses partially confirm the favorable results.

A Term Structure Decomposition of the Australian Yield Curve*

We use data on coupon‐bearing Australian Government bonds and Overnight Indexed Swap (OIS) rates to estimate risk‐free zero‐coupon yield and forward curves for Australia from 1992 to 2007. These curves and analysts’ forecasts of future interest rates are then used to fit an affine term structure model to Australian interest rates, with the aim of decomposing forward rates into expected future overnight cash rates plus term premia. The expected future short rates derived from the model are on average unbiased, fluctuating around the average of actual observed short rates. Since the adoption of inflation targeting and the entrenchment of low and stable inflation expectations, term premia appear to have declined in levels and displayed smaller fluctuations in response to economic shocks. This suggests that the market has become less uncertain about the path of future interest rates. Towards the end of the sample period, term premia have been negative, suggesting that investors may have been willing to pay a premium for Commonwealth Government securities.