Intelligible factors for the yield curve

We construct a factor model of the yield curve and specify time series processes for these factors, so that the innovations are mutually orthogonal. At the same time, the factors are such that they assume clear, intuitive interpretations. The resulting “intelligible factors” should prove useful for investment professionals to discuss expectations about yield curves and the implied dynamics. Moreover, they allow us to distinguish announced changes of the monetary policy stance versus monetary policy surprises, which we find to be rare. We identify two such events, namely September 11, 2001, and the Fed reaction to the sub-prime crisis of 2007.     

No-arbitrage macroeconomic determinants of the yield curve

No-arbitrage macro-finance models use variance decompositions to gauge the extent of association between the macro variables and yields. We show that results generated by this approach are sensitive to the order of variables in the recursive identification scheme. In a four-factor model, one may obtain 18 different sets of answers out of 24 possible. We propose an alternative measure that is based on levels of macro variables as opposed to shocks. We account for the correlation between the macro and latent factors via projection of the latter onto the former. As a result, the association between macro variables and yields can be computed uniquely via an R²$R^2$. Macro variables explain 80% of the variation in the short rate and 50% of the slope, and 54% to 68% of the term premia.     

The expected real yield and inflation components of the nominal yield curve

The term structure of real yields and expected inflation are two unobserved components of the nominal yield curve. The primary objectives of this study are to decompose nominal yields into their expected real yield and inflation components and to examine their behaviour using state-space and regime-switching frameworks. The dynamic yield-curve models capture three well-known latent factors – level, slope, and curvature – that accurately aggregate the information for the nominal yields and the expected real and inflation components for all maturities. The nominal yield curve is found to increase slightly with a slope of about 120 basis points, while the real yield curve slopes upward by about 20 basis points, and the expected inflation curve is virtually flat at slightly above 2 per cent. The regime-switching estimations reveal that the nominal yield, real yield and expected inflation curves have shifted down significantly since 1999.     

Negative interest rate policy and the yield curve

We evaluate the implications of the ECB's negative interest rate policy (NIRP) on the yield curve. To capture various shapes of the short end of the yield curve induced by the NIRP, we introduce two policy indicators, which summarize the immediate and longer horizon future monetary policy stances. We find that the four NIRP events lowered the short-term interest rate by the same amount. The impact is dampened at longer maturities for the first two event dates, due to lack of forward guidance. By contrast, for the last two dates, forward guidance drives the largest effects in two years.     

Forecasting economic activity from yield curve factors

This paper provides clear-cut evidence that the slope and curvature factors of the term structure of interest rates (yield curve) contain more information about future changes in economic activity than the term spread itself, often used in the literature as a predictive regressor of economic activity. These two factors reflect different information about future economic activity, which is smoothed out by the term spread. The paper shows that the slope factor has predictive power on future economic activity over longer horizons ahead, and thus may be interpreted as reflecting future business cycle conditions. On the other hand, the curvature factor, which enters the term spread with opposite sign than the slope factor, has predictive power on shorter movements of future economic activity which may be associated with changes in the current stance of monetary policy. These results hold for a number of world developed economies.     

Principal component analysis of yield curve movements

An important issue in interest rate modeling is the number and nature of the random factors driving the evolution of the yield curve. This paper uses principal component analysis to examine (1) the inherent dimension of historical yield curve changes indicated by the significance of eigenvalues of the covariance matrix, (2) the practical dimension determined by a variance threshold, (3) the shape of the yield curve change associated with the first principal component, and (4) the persistence of this shape over time. We find that although the first two components explain 93% of the sample variation within a 90% confidence interval, the remaining components make statistically significant contribution to the covariance matrix. Consequently, we can establish a practical limit on the dimension only if we are willing to designate a threshold error variance. Further, our results on the persistence of the shape of the yield curve shift associated with the first component depend upon this threshold. If all components are included, the hypothesis that the shape persists between two sample time periods is rejected. On the other hand, if all but the first six components are eliminated, the hypothesis is not rejected.     

Modelling oil price expectations: Evidence from survey data

Using Consensus Forecast survey data on WTI oil price expectations for 3- and 12-month horizons over the period November 1989 to December 2008, we find that the rational expectation hypothesis is rejected and that none of the traditional extrapolative, regressive and adaptive processes fits the data by itself. We suggest a mixed expectation model defined as a linear combination of these traditional processes, which we interpret as the aggregation of individual mixing behavior and of heterogenous groups of agents using these simple processes. This approach is consistent with the economically rational expectations theory. We show that the target oil price included in the regressive component of this model depends on the long-run marginal cost of crude oil production and on short term macroeconomic fundamentals whose effects are subject to structural changes. For the two horizons, estimation results provide evidence for our mixed expectation model incorporating this break-dependent target price.     

Impact of macroeconomic surprises on the Brazilian yield curve and expected inflation

This study investigates how unexpected announcements in Brazilian and U.S. macroeconomic indicators affect the term structure of nominal interest rates, as well as implicit inflation expectations and real interest rates. Using daily data from March 2005 to December 2012, we employ an extended Vector Error Correction Model to take into account nonstationarity and the long-term equilibrium among different maturities of those curves. We found empirical evidence that macroeconomic surprises, domestic (Brazilian) and external (U.S. American), which lead the market to believe that there might be a higher risk of inflation or an overheated economy, raise nominal interest rates, implicit expected inflation and real interest rates. Surprisingly, in relation to the efficient-market hypothesis, we found that some macroeconomic surprises have a lagged effect on the yield curves. We also tested the impact of the global financial crisis of 2007–09 and found that the crisis affected significantly the direction and magnitude of the responses to macroeconomic news.     

The small open macroeconomy and the yield curve: A state-space representation

This study extends a state-space representation of the yield curve and the macroeconomy to a small open economy in order to study the dynamic interaction between the yield curves in Canada and the U.S. The framework treats the U.S. term structure of interest rates as being exogenous to both the Canadian yield curve and macroeconomy. The empirical results support very strong links between the yield curves in the two countries, with the U.S. yield curve accounting for as much as 45 per cent of the variation of the movement in the level and about 30 per cent of the movements in the slope and the curvature of the Canadian yield curve. Canadian yield-curve factors are found to account for about 50 per cent of the variation in output and the monetary policy rate, and about 25 per cent of the variation in inflation, much larger than the yield curve effects found for future developments of the macroeconomies of other countries. A relatively strong bilateral relationship is found to exist between the yield curve and the instrument of monetary policy, supporting recent studies that find the dynamic relationship between the yield curve and the macroeconomy is due to the pivotal role that monetary policy plays in the macroeconomy.     

Time‐varying yield curve dynamics and monetary policy

Monetary policy, the yield curve and the private sector behaviour of the US economy are modelled as a time‐varying structural vector autoregression. The monetary policy shocks of the early 1980s explain a large portion of the persistence of inflation and the level of the term structure. Changes in inflation expectations implied by the yield curve account for the persistence of the federal funds rate. Failures of the expectations hypothesis are rare, and coincided with the credibility building of Paul Volcker's Fed tenure at the beginning of the 1980s and the sequence of consecutive policy rate cuts around the time of the early 1990s recession. Copyright © 2009 John Wiley & Sons, Ltd.     

COVID-19 related media sentiment and the yield curve of G-7 economies

We explore the connectedness of the components of the sovereign yield curve (slope, level and curvature) across G-7 countries and media sentiment about COVID-19. The recent pandemic is a unique opportunity to identifying the transmitters and receivers of risk. Our results indicate that media sentiment along with the US yield curve components are main transmitter of spillovers, whereas Japan is the leading recipient of spillover. Among the European countries, we notice France as a major transmit, whereas Germany and UK switch role as transmitter and receiver alternatively. The results are important for mapping the interconnectedness between countries. In addition, policy makers can use them when devising disaster plans to prepare for future market crises.     

Identification of triggers of U.S. yield curve movements

We present new evidence for understanding the sources of daily movements in U.S. Treasury yields. We use a novel narrative approach combined with Bayesian inference to identify news-based triggers of yield movements between 2001 and 2019. We show that the U.S. macroeconomic news was the core trigger of U.S. Treasury yield volatility over most of the period under analysis. However, the importance of non-macroeconomic news associated with capital flight has increased significantly since 2011, and they became the dominant source of movements in the long end of the U.S. yield curve after 2016. This highlights the growing importance of the U.S. Treasuries as a safe haven asset and implies possible partial loosening of the relation between U.S. Treasury yields and the U.S. business cycle.     

Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach

This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model uses the short rate and the common components of a large number of macroeconomic variables as factors. Precisely, the dynamics of the short rate are modeled with a Factor-Augmented Vector Autoregression and the term structure is derived using parameter restrictions implied by no-arbitrage. The model has economic appeal and provides better out-of-sample yield forecasts at intermediate and long horizons than a number of previously suggested approaches. The forecast improvement is highly significant and particularly pronounced for short and medium-term maturities.     

Forecasting the business cycle using survey data

Regular business survey data are published as percentages of firms predicting higher, equal or lower values of some reference variable. Time series of such percentages do not fit production data too well. Univariate models often produce forecasts which are just as accurarate. Still, surveys contain anticipative judgement which, when combined with univariate modeling and proper filtering, may produce a good indicator for business cycle turning points. The way survey data are transformed so as to fit statistics on production seems not to be of much importance. A case study of the Finnish forest industry is offered as an example.     

利用测井曲线估算煤层灰分

对煤层灰分进行分析的经典方法包括从钻孔取芯,然后在化验室化验分析得出结果两个步骤。为了克服单纯使用实验室分析煤芯采取率低,钻探岩粉对煤样的污染等产生的误差,采用定量的测井数据来计算煤层的灰分,可以在现场快速评价煤质。同矿区同一煤层的形成条件基本稳定,煤中灰分所吸附的放射性物质与煤层灰分含量有关,利用煤层的自然伽马值和煤层灰分进行回归分析,求出回归方程,并计算出煤层中的灰分。     

Modeling college major choices using elicited measures of expectations and counterfactuals

The choice of a college major plays a critical role in determining the future earnings of college graduates. Students make their college major decisions in part due to the future earnings streams associated with the different majors. We survey students about what their expected earnings would be both in the major they have chosen and in counterfactual majors. We also elicit students’ subjective assessments of their abilities in chosen and counterfactual majors. We estimate a model of college major choice that incorporates these subjective expectations and assessments. We show that both expected earnings and students’ abilities in the different majors are important determinants of a student’s choice of a college major. We also consider how differences in students’ forecasts about what the average Duke student would earn in different majors versus what they expect they would earn both influence one’s choice of a college major. In particular, our estimates suggest that 7.8% of students would switch majors if they had the same expectations about the average returns to different majors and differed only in their perceived comparative advantages across these majors.     

Beyond the audit expectations gap

In seeking to encourage a broader, European dimension to research on auditing and audit expectations, this paper examines the recent history of auditing and its regulation in Spain within the context of international developments in the accounting profession. The more expansive role being assigned to the audit function in Spain following the implementation of the Fourth and Eighth European Company Law Directives is generally viewed by Spanish writers as a progressive step, with largely positive effects. Such views stand in some contrast to the history of auditing in Britain, where the prevalence of an ‘audit expectations gap’ suggests a rather more problematic state of affairs. In exploring both the Spanish context and the nature of the audit expectations gap in Britain, however, the paper reveals a common underlying belief in the potential of auditing. Through this comparative analysis, and by drawing on recent audit research challenging certain long-held assumptions about auditing, a number of questions are asked of the current form and status of auditing and auditing expectations in Britain and Spain. In so doing, the paper raises issues that go beyond the current confines of the audit expectations gap debate, stressing, in particular, the need for greater consideration to be given, through less Anglo-centric analyses, to the varying nature and capabilities of European audit practice.     

Estimating yield spreads volatility using GARCH-type models

The primary focus of this study is on modeling the relationship between the volatility of corporate bond yield spreads and other covariates, including interest rate volatility, equity volatility, and rating. The purpose of this article is to apply various GARCH models to estimate the volatility of corporate bond yield spreads. This attempt is, to the best of our knowledge, the first to analyze the volatility of the yield spreads. In particular, this study utilizes standard GARCH and various asymmetric GARCH models, including E-GARCH, T-GARCH, P-GARCH, Q-GARCH, and I-GARCH models. We select the best fitting models for the noncallable (callable) case based on AIC, and it turns out Q-GARCH (T-GARCH) is the best fitting model. The estimation results indicate that our explanatory variables are statistically significant even at the 1% significance level when we apply the best fitting models. They are generally consistent, but we observe the presence of apparent differences. Our findings should be beneficial to practitioners, including investors.     

Estimation and solution of linear rational expectations models using a polynomial matrix factorization

A method to solve and estimate multivariate linear rational expectations models is described. The method is based on an iterative factorization of the polynomial matrix that describes the lags and expected leads in the model. Our experience is that the method works well in a variety of applications where other methods are either difficult or expensive to use.