Yield Curve Research Articles

JGB Yield Curve and Macro-Financial Stability

Given that there is exceptionally high uncertainty around the domestic inflation outlook, allowing for greater flexibility in long-term Japanese Government Bond (JGB) yields by the Bank of Japan (BoJ) could be considered going forward. Against this background, this study empirically finds that a steeper JGB yield curve helps improve banks’ profitability, especially after a year lag, and the overall impact hinges on macroeconomic and financial market responses. A steeper JGB yield curve could also have spillovers on global yields. Financial sector policies to mitigate short-term vulnerabilities in case the JGB yield curve steepens could be considered, including by further strengthening engagement with financial institutions with relatively high exposure to interest rate movements, to better harness the benefits in the medium term.

A hydro-mechanical constitutive model for unsaturated soils over a wide saturation range

A hydro-mechanical constitutive model for unsaturated soils is proposed to describe the hydraulic and mechanical behaviour over a wide saturation range. Bishop’s effective stress and the effective degree of saturation are taken as the basic constitutive variables. A simple and novel loading-collapse yield curve is constructed to capture the variation of the yield stress with the hydraulic state over a wide saturation range. A non-orthogonal plastic flow rule is adopted to obtain the direction of the plastic strain increment. A simple water retention model is developed to describe the hydraulic behaviour of unsaturated soils. The proposed constitutive relation is presented through the calculation of the total strain increment and the calculation of the increment of the effective degree of saturation. All material parameters can be determined through conventional laboratory tests. The performance of the proposed model is illustrated through numerical examples of three classical stress paths, i.e., the isotropic compression path with constant suction, the wetting path with constant net stress, and the triaxial shearing path with constant suction and mean net stress. The capability of the proposed model to capture the hydraulic and mechanical behaviour of unsaturated soils is validated by simulating the test results from the literature.

Towards a macroprudential regulatory framework for mutual funds?

AbstractThis paper highlights the procyclical and unstable behaviour of mutual funds, characterized by a varying sensitivity on common asset pricing factors. It proposes a novel factor model that allows for regime changes associated with macroeconomic and financial state variables. Estimated on a panel covering 825 US equity mutual funds over a period of 30 years, it appears that the yield curve, the dividend yield, short term interest rates and the industrial production coincide with regimes switches in the Fama–French factors. Furthermore, the estimated regimes coincide with financial crises and economic downturns, thus confirming the procyclical behaviour of mutual funds' returns. These findings, coupled with the emerging systemic role of mutual funds, promote the consideration for a specific macroprudential regulatory framework targeted at the mutual fund industry.

Are bond returns predictable with real-time macro data?

We investigate the predictability of bond returns using real-time macro variables and consider the possibility of a nonlinear predictive relationship and the presence of weak factors. To address these issues, we propose a scaled sufficient forecasting (sSUFF) method and analyze its asymptotic properties. Using both the existing and the new method, we find empirically that real-time macro variables have significant forecasting power both in-sample and out-of-sample. Moreover, they generate sizable economic values, and their predictability is not spanned by the yield curve. We also observe that the forecasted bond returns are countercyclical, and the magnitude of predictability is stronger during economic recessions, which lends empirical support to well-known macro finance theories.

Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms

The modern in-season crop N recommendation approaches should have high reliability in promoting agricultural sustainability. These approaches are relevant to soil properties, meteorological conditions, management practices, and crop in-season growing status. This study aims to use machine learning (ML) algorithms to incorporate the above variables as well as the field reactive nitrogen (N) losses (i.e., N damage cost) simulated by a DeNitrification–DeComposition (DNDC) model to develop a new strategy for optimizing rice in-season topdressing N (TN) usage. Rice field experiments with multiple N treatments and rice varieties were carried out during 2015–2021 at four study sites in eastern China. Four ML algorithms, namely random forest regression (RFR), support vector regression (SVR), lasso regression (LSR), and partial least square regression (PLSR) were used to develop in-season prediction models of yield and reactive N losses by combining soil, meteorological, and management data with crop remote sensing data. The observed in-season agronomic optimum N rates (AONR) that can maximize rice yield at different sites were in the range of 116.5 to 177.4 kg N ha−1, while the in-season economic optimum N rates (EONR) that can maximize marginal revenue (i.e., yield income minus N fertilizer costs and N damage costs) were in the range of 97.4 to 163.6 kg N ha−1. The developed ML models were further used to simulate yield and marginal revenue responses to a series of assumed TN rates (0–300 kg N ha−1, gradient = 20 kg N ha−1). Comparably, RFR model and SVR model were more suitable for determining optimum TN rates, because their simulated response curves of yield and marginal revenue fit the normal regulation (linear plus plateau or single-peak shapes). Independent validation results showed that the in-season AONR and EONR predicted by RFR and SVR well accorded with the observed values (R2 ≥ 0.64, RRMSE ≤ 18.3 %), and the accuracy of ML models containing both historical and in-season meteorological information is superior to ML models that contain in-season meteorological information only. The proposed ML-based strategy is expected to help the regional rice production systems precisely manage N use, improve net profits, and reduce environmental footprints.

Yield spread selection in predicting recession probabilities

AbstractThe literature on using yield curves to forecast recessions customarily uses 10‐year–3‐month Treasury yield spread without verification on the pair selection. This study investigates whether the predictive ability of spread can be improved by letting a machine learning algorithm identify the best maturity pair and coefficients. Our comprehensive analysis shows that, despite the likelihood gain, the machine learning approach does not significantly improve prediction, owing to the estimation error. This is robust to the forecasting horizon, control variable, sample period, and oversampling of the recession observations. Our finding supports the use of the 10‐year–3‐month spread.

Experimental and Monte-Carlo study of double-hump electron emission yield curves of SiO2 thin films

In this work, we have made experimental measurements of multiple-hump total electron emission yield (TEEY) curves on SiO2 thin films. A Monte-Carlo electron transport model, published in Gibaru et al., J. Electron Spectrosc. Relat. Phenom. 261, 147265 (2022), has been developed to analyze the physical reasons of such atypical behavior. It is shown that the multiple-hump TEEY curves of thin dielectric layers are due to internal recombination effects. However, such kind of phenomenon is demonstrated to be strongly correlated to the incident current density. This analysis reveals that the double-hump TEEY curves observed commonly on insulators are also most probably a measurement artifact, tied to the operating parameters of the electron gun. A careful choice of experimental parameters can eliminate this artifact, by using a constant current density that is also low enough to limit recombination effects.

Recessions and flattening of the yield curve (1960–2021): A two-way road under a regime switching approach

The one-way relationship that goes from the term spread to recessions has been widely studied. However, the relationship between term spread and the business cycle, in addition to being bidirectional, is conditioned by the cyclical phase itself. To demonstrate this, we have modelled the bidirectional relationship between term spread and the business cycle by extracting two interrelated latent Markov variables: the first, drawn from four activity indicators, replicates the phases of the US business cycle; the second, from the term spread of the yield curve, identifies two regimes: an ordinary regime (positive slope) and a flattening regime. By analyzing both the transition between these regimes and forecasted probabilities, we find that this bidirectional relationship is not symmetrical. That is, the term spread signals a change in the business cycle regime while the cyclical factor only signals the beginning of the ordinary regime of the term spread, not its ending. To illustrate the model, we confirm the beginning of the COVID-19 recession in March of 2020, and the corresponding start of the ordinary regime in the term spread.

Exact formula for the effective yield stress of metals with arbitrary stress–strain curves

Sufficiently thick ductile protective targets are perforated by rigid, pointed-nose projectiles in a hole enlargement process. Several recent studies have shown that the (spherical cavitation) effective yield stress YcS is an essential effective material parameter for analytical predictions of ballistic limit velocities. This effective yield stress is also found to be essential in determining ballistic equivalence between two different alloys of the same metal and between two different metals like aluminium and steel. First, the concept of the (spherical cavitation) effective yield stress is presented with comprehensive reference to previous studies, to emphasize the practical importance of this effective material parameter. Thereafter, an exact formula for YcS, which is based on the W−1(x) branch of the Lambert function, is derived and eliminates the need for solving the exact value of YcS by a numerical procedure. Moreover, while approximate expressions of YcS are exist for several stress–strain curves with definite yield stress, the new exact formula is applicable for any stress–strain relation, including stress–strain curves without a definite yield point and curves which take into account thermal softening effect.

SYNTHESIS AND PHOTOELECTROCHEMICAL PROPERTIES OF SU2O-CU3VO4 COMPOSITE FILMS

Cu2O-Cu3VO4 films were obtained by elect­rochemical synthesis. The analysis of polarization curves and Pourbaix diagrams for copper and vanadium ions made it possible to analyze the possible reactions that occur during the deposition of films. At potentials from 0 to -0.2V, mainly monovalent copper oxide Cu2O with Cu3VO4 impurities precipitated in the working solution. At the same time, there are two competing processes of acidification of the near-electrode layer as a result Cu2O formation reaction and alkalinization as a result of the chemical interaction of Cu2O with HVO42-. The formation of an excess of OH- ions can inhibit the reaction rate of the formation of Cu3VO4, accelerating the reaction of the formation of Cu2O. Thus, deposition of Cu3VO4 will take place to a lesser extent compared to Cu2O. Accordingly, to increase the yield of Cu3VO4, an attempt was made to reduce the deposition current, which, according to literature, helps to reduce the effect of the pH change near the electrode layer. Where, as known the critical current limit at change pH starts from 5 or more mA/cm2. For the synthesis of the films, a current of up to 1 mA/cm2 selected, which contributed to the production of the Cu3VO4 - Cu2O composite, as was established further from the analysis of X-ray patterns. It is shown that their photoelectrochemical pro­perties depend on the heat treatment conditions. This is expressed by the difference in the spectral characteristics of the quantum yield and the value of the photocurrent in the samp­les annealed in air and argon. Using the X-ray phase analysis method, it was established that heat treatment in argon contributes to the formation of a Cu3VO4 and Cu2O composite, in contrast to heat treatment in air, where a mixture of CuO and V2O5 oxides is mainly formed. In the film annealed in air due to impact of wide-band oxide compounds, a smaller value of the quantum yield of the photoelectrochemical current and a narrower spectral dependence were observed. The stretching of the spectrum into the region of visible light on the spectral curves of the photocurrent quantum yield is caused by the contribution of copper vanadate with Eg = 1.5 eV. Analysis of photo­current quantum output spectra and X-ray patterns showed that an increase in monovalent copper in the film structure contributes to the growth of photocurrent in the wavelength range of 450-600nm at a potential of -0.2 relative. h.s.e in 2 times. This indicates a positive effect of heat treatment in argon on increasing the efficiency of photocathodes based on a composite of Cu3VO4 and Cu2O for photoelectrochemical cells.

Yield curve of Treasury Bills in Japan under different regimes of non‐traditional monetary policy

AbstractWhen the BOJ (Bank of Japan) adopted a “quantitative and qualitative easing policy,” zero bound restriction existed. The notion of market practitioners that the BOJ would not adopt a “negative interest rate policy” caused less volatility in the TB (Treasury Bill) market in comparison with a regime of a “negative interest rate policy.” After the BOJ decided to adopt a “negative interest rate policy,” zero bound restriction was lifted, and market practitioners expected that the policy rate decided by the BOJ might be lowered. This expectation gave room for TB yields to fluctuate more than before, and caused more volatility in the TB market under the regime of a “negative interest rate policy” than under one of a “quantitative and qualitative easing policy.” This is why the TB yield curve under a “negative interest rate policy” is driven by a single common trend with mutual causalities in all maturities. In other words, the normal transmission function of the TB yield curve is recovered by the introduction of a “negative interest rate policy.”

Does the Exchange Rate Respond to Monetary Policy in Mexico? Solving an Exchange Rate Puzzle in Emerging Markets

AbstractThis paper argues that the null or weak response of emerging market currencies to domestic monetary policy documented in the literature is the result of wide event windows. An event study with intraday data for Mexico shows that an unanticipated tightening appreciates the currency and flattens the yield curve, consistent with the evidence for advanced economies. With daily event windows, however, only the yield curve responds to monetary policy. Noise in daily exchange rate returns explains the lack of response of the currency. Such noise gives rise to a bias that declines after controlling for potential omitted variables.

The information in joint term structures of bond yields

While the open-economy macroeconomics literature amply demonstrates the importance of allowing for trade and financial linkages between countries, the finance literature on the term structure of interest rates has largely adopted a “closed-economy” setting in which yields in one country depend only on their own lagged values. This paper examines whether it is in fact necessary to jointly model yields in multiple countries, as proposed by a handful of recent studies. We show that there is little convincing evidence that would point to such a need. The reason is that bond yields are forward-looking variables: any relevant information about foreign countries is likely to be already reflected in today’s domestic yield curve.

A yield curve for bi-material structures and its application in energy absorption analysis of FML beam

The yield curve for bi-material structures is proposed and applied to energy absorption analysis of fully clamped FML beam with CFRP and metal under transverse load. Firstly, fully clamped FML beam tests under transverse loading are performed to acquire the energy absorption response. Then, a unified yield criterion for bi-material structures, that contains metal and fiber reinforced plastic and CFRP has asymmetry properties under tensile and compressive load, is established and discussed. Based on the yield criterion, a theoretical analytical model for the large deformation to predict energy absorption of fully clamped FML beams with shear angle-ply under the transverse load is developed. Finally, comparison of results obtained by theoretical solution and experiments show that the theoretical analysis can predict the energy absorption capacities of FML beams. In addition, effect of significant parameters on yield curves and energy absorption capacity are discussed.

Effect of Yield Spreads (State Bonds) on Economic Growth Performance in Indonesia

This research analyzes the effect of the government bond yield curve spread on economic growth performance in Indonesia using the indicators of exchange rate, inflation, BI rate, foreign investment, portfolio investment, current account, and government accounts. Furthermore, it aims to prove the accuracy of the vector autoregression (VAR) or vector autoregression model in predicting economic growth from Q1 2010 to Q3 2020. The results showed that the yield curve spread has a significant effect on economic growth. Meanwhile, the exchange rate, inflation, and the BI rate have a negative effect on economic growth. Capital inflows such as foreign direct investment, portfolio investment, as well as the current account balance and government balance have a positive effect on economic growth. These results are useful to government policymakers, fund managers, and investors, as they provide further evidence of the potential use of yield curves as an indicator of future economic activity.

Nowcasting the state of the Italian economy: The role of financial markets

AbstractThis paper compares several methods for constructing weekly nowcasts of recession probabilities in Italy, with a focus on the most recent period of the Covid‐19 pandemic. The common thread of these methods is that they use, in different ways, the information content provided by financial market data. In particular, a battery of probit models are estimated after extracting information from a large dataset of more than 130 financial market variables observed at a weekly frequency. The accuracy of these models is explored in a pseudo out‐of‐sample nowcasting exercise. The results demonstrate that nowcasts derived from probit models estimated on a large set of financial variables are, on average, more accurate than those delivered by standard probit models estimated on a single financial covariate, such as the slope of the yield curve. The proposed approach performs well even compared with probit models estimated on single time series of real economic activity variables, such as industrial production, business tendency survey data or composite PMI indicators. Overall, the financial indicators used in this paper can be easily updated as soon as new data become available on a weekly basis, thus providing reliable early estimates of the Italian business cycle.

Secular Economic Changes and Bond Yields

AbstractWe build a model of bond yields in an economy with secular changes to inflation, real rate, and output growth. Long-run restrictions identify nominal shocks that do not influence the long-run real rate and output growth. Before the anchoring of inflation around the mid-1990s, nominal shocks lifted the output gap and inflation. This led to a higher and steeper yield curve because the short rate was expected to peak after several quarters, following declines in the responses of growth and inflation. With inflation anchored, nominal shocks have small impacts on inflation, output, and bond yields, mostly via the term premium.

Can Brazilian Central Bank communication help to predict the yield curve?

AbstractThis paper investigates whether Brazilian Central Bank communication helps to forecast the yield curve. Our forecast strategy involves two steps: First, we analyze textual Central Bank documents to extract sentiment variables that describe its communication, and then, we include those sentiment variables as additional factors into the dynamic Nelson–Siegel term structure model. We found that sentiment variables contain predictive information for yield curve forecasting. Specifically, when combined with macroeconomic variables, the sentiment variables improve the accuracy of the forecast for short maturities and forecast horizons. In addition, sentiment variables are useful in forecasting for medium and long forecast horizons for all maturities. Besides finding a new source of information to forecast the yield curve, the results indicate that the information provided by Central Bank affects market participants, proving to be a useful tool for monetary policy.

Geopolitical Risks and Yield Dynamics in the Australian Sovereign Bond Market

Geopolitical risks and shocks such as military conflicts, terrorist attacks, and war tensions are known to cause significant economic downturns. The main purpose of this paper is to determine the dynamics between Australian sovereign bond yields and geopolitical risk. This is achieved by employing a quantile regression analysis. The findings of this study indicate that the impact of geopolitical risk on Australian sovereign yield dynamics is asymmetrical. Furthermore, an increase in geopolitical risk only impacts short-term yields at extreme regimes. However, the impact is, by and large, insignificant. On the other hand, an increase in geopolitical risk does have a statistically significant positive impact on medium- and long-term yields across most quantiles. Lastly, an increase in geopolitical risk tends to result in a steeper yield curve at the belly of the curve but causes the yield curve to flatten at the long end. This study is the first study that holistically examines the dynamics between geopolitical risk and Australian sovereign bond yields. The study thereby contributes to the body of knowledge on Australian bond yields, specifically, and adds to the sparse body of knowledge on the dynamics between geopolitical risk and sovereign bond yields. The findings of this study have implications for monetary policy makers, given that shifts in sovereign bond yields could impact all three core mandates of the Australian Reserve Bank. Furthermore, changes in the slope of the yieldcurve could be used by monetary policy makers to pre-empt changes in future economic growth. The results of this study also relate to fiscal policy formulation, given that yields directly impact the cost of government borrowing. Lastly, portfolio managers could benefit from the results of this study, as these results provide information on the ability of Australian sovereign bonds to hedge against geopolitical risk.

Discussion of “Multivariate dynamic modeling for Bayesian forecasting of business revenue”

Discussion of “Multivariate dynamic modeling for Bayesian forecasting of business revenue”