Yield Curve Research Articles

Optimal Monetary and Fiscal Policies to Maximise Non-Parallel Risk Premia in Sovereign Bond Markets

In this paper, we analysed several emerging market (EM) and developed market (DM) sovereign yield curves to identify the proportion of parallel and non-parallel shifts over time. We found that non-parallel shifts are more prevalent in EM due to higher political and economic risks. Key drivers include systemic risk events like wars, debt distress, and pandemics. By backtesting a long butterfly strategy to extract non-parallel risk premia from June 2007 to March 2024, we observed that steeper slopes and greater curvature result in higher returns. We also quantified monetary and fiscal regimes to determine what types of policies are required to extract non-parallel risk premia from these sovereign yield curves. Our research suggests that countries with opposing monetary and fiscal policies possess higher return opportunities whilst countries with complementing policies require tactical butterfly strategies to optimise returns.

Long-Term Investors, Demand Shifts, and Yields

Abstract I exploit a Dutch reform in the regulatory discount curve that makes the liabilities of pension funds and insurance companies (P&Is) more sensitive to changes in 20-year interest rates but less so to longer maturity rates. Following the reform, P&Is reduced their longest maturity bond holdings but increased those with 20-year maturities, steepening the long end of the yield curve. Using the reform as a shock to identify price elasticities of demand at the sector level based on holdings across maturity buckets and time, I show that banks are more price elastic than other investors and absorb demand shocks. (JEL G12, G18, G22, G23, G28)

Zero coupon yield curve dynamics in the Russian sovereign bond market

Yield curve is a graphical representation of a relationship between interest rates and maturity. Shape of yield curve often attracts attention of analysts, because it represents market implied expectation of future interest rate path. However, the analysis of the yield curve shape often lacks theoretical foundation. It is based either on review of term spreads or on a simple visual investigation. In this article we formally define the shape of the yield curve in terms of function invariants. We use Nelson–Siegel model as a backbone for our classification and show that there exists only six possible shapes of yield curve. They are: a normal upward slopping yield curve, inverted yield curve, humped upward slopping, dipped upward slopping, humped inverted and dipped inverted. We analyze dynamics of zero coupon yield curve in Russian market based on real historical data. We show that transition from an upward slopping curve to an inverted one was always preceded by a hump at mid-tem maturities, while the transition back was always done through the dip. This highlights the importance of mid-term rates in reshapening the curve. We explain this behavior by short end of the curve being linked to the key rate and thus being more sticky. The contribution of the paper is twofold. First, it provides a formal framework to analyze the shape of the yield curve. Second, it describes the patterns in dynamic of the ruble yield curve that can be useful for bond investors in the Russian market.

Monetary and Fiscal Policy Impacts on the Indian Sovereign Bond Market: A VAR Approach

This study analyses the dynamic relationship between yield curve behaviour and the macroeconomy in India, with a focus on both monetary and fiscal policy impacts. Using the monthly data on yields of Treasury bills and government securities from April 2000 to March 2020, we employ principal component analysis to extract the three yield curve factors—level, slope and curvature. We then use an unrestricted vector autoregressive model to analyse the relationship between these three yield curve factors and macroeconomic variables: inflation, GDP growth, exchange rate and monetary and fiscal policy indicators. Our findings reveal a bidirectional causality between yield curve factors and macroeconomic variables. Monetary policy plays an important role in shaping the yield curve, with short-term rates having more pronounced effects than long-term rates. Notably, this study is among the first to incorporate fiscal policy indicator in the Indian context, providing a more comprehensive understanding of policy impacts on the sovereign bond market. Our results offer valuable insights for policymakers and investors, showing the interrelationship of fiscal and monetary policies with bond market dynamics in emerging economies. This research contributes to the growing macrofinance literature and enhances our understanding of financial market dynamics in a developing economy. JEL Classification: E430, C32, G120, E44

Exciting Times are Ahead - Gaussian Views and Yield Curve Extrapolation

In the insurance industry, products having a much longer time to maturity and yield values for up to 100 years need to be modeled. J�rg Kienitz and Leenesh Moodliyar propose to apply Gaussian Process Regression (GPR) for the extrapolation. The method is compared to two market standard methods � the Nelson-Siegel-Svensson (NSS) and the Smith-Wilson (SW) methods

Catalytic cracking of methane to H2 and carbon over hydrotalcite-derived sintering-resistant NiVAl catalysts

Catalytic methane cracking produces pure H2 and high value-added carbon, a potentially environmentally friendly process for hydrogen production, but challenges remain in the designing of high-performance catalysts. NiVAl catalysts were obtained by reducing the hydrotalcite precursor, and the samples were analyzed by XRD, ICP, N2 adsorption-desorption, SEM, XPS, and the impacts of reaction temperature and V/Ni ratio on the production of H2 by cracking methane were studied. The results showed that the V doping could promote the reduction of Ni species, improve the specific surface area of the catalyst and inhibit the sintering of Ni particles. The methane cracking hydrogen yield curve illustrates that the performance of NiVAl catalyst shows a volcanic relationship with the V/Ni ratio. The Ni2.4V0.6Al catalyst exhibits optimal performance, with a stable hydrogen yield of about 80% for 210 min at 700 °C. In addition, the reaction temperature also significantly affects the catalyst performance, with high temperatures favoring increased catalytic activity and low temperatures tending to improve stability. The Ni2.4V0.6Al catalyst was reacted at 600 °C for 300 min with 68% hydrogen yield without deactivation.

Yield curve extrapolation with machine learning

Abstract Yield curve extrapolation to unobservable tenors is a key technique for the market-consistent valuation of actuarial liabilities required by Solvency II and forthcoming similar regulations. Since the regulatory method, the Smith–Wilson method, is inconsistent with observable yield curve dynamics, parsimonious parametric models, the Nelson–Siegel model and its extensions, are often used for yield curve extrapolation in risk management. However, it is difficult for the parsimonious parametric models to extrapolate yield curves without excessive volatility because of their limited ability to represent observed yield curves with a limited number of parameters. To extend the representational capabilities, we propose a novel yield curve extrapolation method using machine learning. Using the long short-term memory architecture, we achieve purely data-driven yield curve extrapolation with better generalization performance, stability, and consistency with observed yield curve dynamics than the previous parsimonious parametric models on US and Japanese yield curve data. In addition, our method has model interpretability using the backpropagation algorithm. The findings of this study prove that neural networks, which have recently received considerable attention in mortality forecasting, are useful for yield curve extrapolation, where they have not been used before.

Using functional shocks to assess conventional and unconventional monetary policy in Canada

AbstractWe develop a new series of Canadian monetary policy shocks for the time period 1986 to 2023. Our shocks are constructed as the daily change in the Nelson–Siegel yield curve factors on days of monetary policy events such as announcements of the short‐run policy rate and speeches by Bank of Canada officials. This allows us to look at both conventional and unconventional monetary policy. We find that tighter monetary policy lowers inflation and GDP. Monetary policy shocks, however, often twist the yield curve, potentially offsetting changes in the short‐run policy rate. Finally, speeches also tend to move the yield curve with similar effects on inflation and GDP as formal policy announcements.

Numerical springback prediction for high-strength aluminum alloys based on the sheet metal upsetting test

Springback prediction continues to play a special role in the process design of sheet metal forming processes. During the forming process, elastic energy is stored in the sheet metal, which is released after the tool is opened. The dimensional accuracy and the function of the component in particular can be negatively affected by this. For this reason, the springback is predicted by means of numerical modeling in order to improve the process design. The simulation accuracy depends primarily on the used material model to map the stress-dependent material behavior and the quality of the experimental input data. High-strength aluminum alloys, which have a distinctive springback behavior, have a slightly pronounced tensile-compressive asymmetry. Since tensile and compressive stresses often occur in sheet metal forming processes, the consideration of this effect can lead to an improvement in springback prediction. Besides modeling the yield locus curve for describing the yield strength in the plane stress area, the yield curve data is also relevant for determining the strain hardening behavior. The work hardening is usually characterized by the tensile test or the hydraulic bulge test, which is used to describe the material behavior in the tensile stress state. A promising experimental method for the analysis of the material in the uniaxial compressive stress state is the sheet metal upsetting test. In addition to a local characterization of sheet metal materials, this test also enables the investigation of the material behavior at significantly higher plastic strains than in the tensile test. Thus, in this contribution it is examined to what extent the sheet metal upsetting test is suitable for improving the springback prediction quality of material models in sheet metal forming processes.

Term spread spillovers to Latin America and emergence of the ‘Twin Ds’

This paper investigates the relationship between depreciation and default risks in five key Latin American markets—Brazil, Chile, Colombia, Peru, and Mexico—in response to shifts in the US yield curve slope. Excluding serial defaulters like Argentina, our focus lies on countries still susceptible to the Twin Ds phenomenon amidst high debt levels. We find that global economic spillovers significantly influence the Twin Ds in these markets; with fluctuations in the US term spread serving as an indicator of broader shifts in global economic conditions. Our analysis reveals asymmetric spillover effects, particularly during periods of positive and increasing spreads such as the Global Financial Crisis, where changes in the term spread disproportionately impact the depreciation tail in currency markets and the high-risk tail in sovereign CDS markets. Notably, such effects are absent in stock markets, which accentuate the particular dynamics of currency and sovereign debt markets. The asymmetry of spillover effects although still present during the most recent Covid-19 crisis, was less pronounced, which may be linked to the accumulation of international FX reserves in the region during the last decades. Our findings emphasize the necessity of incorporating risk spillovers into policy frameworks, highlighting the dominance of risk spillovers over price spillovers and the obscured nature of shocks at the center of the variables’ distribution.

The Bond Market: A Pillar of Risk Management and Economic Stability

This essay investigates the utility of the bond market in risk management, corporate finance, and economic forecasting. It explores how the bond market’s inherent characteristics of safety, stability, and liquidity make it a crucial component of the global financial system. By examining the issuance of debt instruments, such as bonds, and their role in maintaining corporate control while accessing capital, the essay highlights the advantages of debt financing. Moreover, it underscores how these attributes help corporations manage financial risks and optimize their capital structure. Furthermore, the bond market’s predictive power is analyzed through key indicators like the yield curve and credit spreads, which provide early warnings of economic downturns. The yield curve, in particular, is known for its ability to forecast recessions when it inverts. Credit spreads, the difference between yields on corporate bonds and government securities, also serve as a barometer for economic health and investor sentiment. To bring these theoretical insights into a practical context, the essay includes case studies, such as Apple Inc.’s strategic use of debt. Apple's case demonstrates how a company can leverage debt to finance growth while preserving equity and maintaining financial flexibility. These examples illustrate the tangible benefits and strategic importance of the bond market in corporate finance. The essay concludes with suggestions for leveraging the bond market’s predictive capabilities, emphasizing the need for continuous monitoring and analysis of bond market signals to inform economic and financial decision-making. It also explores future research directions in the evolving financial landscape, considering how technological advancements and regulatory changes may impact the bond market's role in global finance.

Radiofrequency sheath rectification on WEST: application of the sheath-equivalent dielectric layer technique in tokamak geometry*

Abstract Radiofrequency sheath rectification is a phenomenon relevant to the operation of Ion Cyclotron Range of Frequencies (ICRFs) actuators in tokamaks. Techniques to model the sheath rectification on 3D ICRF antenna geometries have only recently become available (Shiraiw et al 2023 Nucl. Fusion 63 026024; Beers et al 2021 Phys. Plasmas 28 093503). In this work, we apply the ‘sheath-equivalent dielectric layer’ technique, used previously only on linear devices (Beers et al 2021 Phys. Plasmas 28 103508), in tokamak geometry, computing rectified sheath potentials on the WEST ICRF antenna. Advancing the state of the art in sheath rectification modeling, we compute the sheath potentials not just on the limiters, but also on the Faraday Screen bars. The calculations show a peak rectified DC potential of 300 V on the limiters and 500 V on the Faraday screen. Assuming a typical sputtering yield curve, the RF sheath rectification increases the sputtering yield from the limiters by a factor of 2.6 w.r.t. the sputtering due to the non-rectified thermal sheath.

Influence of 5-fluorination on the structure and glycosidic bond stability of the protonated canonical DNA and RNA cytidine nucleosides: Oh, what a difference the 2′-hydroxy substituent makes?

Fluorinated nucleosides are well-established as anticancer and antiviral medications. As with many pharmaceuticals, the effects of fluorine modifications are often only partially understood. In this work, the effects of 5-fluorination of the cytosine nucleobase on the structures and glycosidic bond stabilities of the protonated canonical DNA and RNA cytidine nucleosides (dCyd and Cyd) are examined. Infrared multiple photon dissociation action spectroscopy experiments and electronic structure calculations are employed to probe the structural influences of 5-fluorination. Spectral signatures in the IR fingerprint and hydrogen-stretching regions indicate that 5-fluorination heavily directs for and solely produces O2 protonation para to the 5-fluoro substituent. This differs from the canonical cytidine nucleosides where roughly equal populations of O2 and N3 protonated structures were observed. Energy-resolved collision-induced dissociation experiments combined with survival yield analyses are performed to probe the influence of 5-fluorination on glycosidic bond stability. Trends in the energy-dependence of the survival yield curves indicate that 5-fluorination weakens the glycosidic bond, and that the influence of 5-fluorination on glycosidic bond stability is much greater for dCyd than Cyd. Theory also finds that 5-fluorination weakens the glycosidic bond but predicts that the influence of 5-fluorination on N-glycosidic bond stability is roughly the same for dCyd and Cyd. Oh, what a difference the 2′-hydroxy substituent makes?

EXTRACTING PRICE SIGNALS FROM THE TERM STRUCTURE OF COMMODITY AND CREDIT MARKETS USING AUSTRIAN BUSINESS CYCLE THEORY

Austrian School economists first explained the significance of interest rates for the structure of production in time. Furthermore, they showed how manipulating the level of interest and the credit supply causes the business cycle (v.Böhm-Bawerk, 1891; v.Hayek, 1938; v.Hayek, 1941 and v.Mises, 1949). More recently, Austrian School economists have elaborated the relationship between the term structure of interest rates and the business cycle (Barnett and Block, 2009; Bagus and Howden, 2010; Bagus et al., 2018; Potuzak and Nemec, 2020; Alonso-Neira and Sanchez-Bayon, 2023). At the same time, market practitioners understand the potency of yield curve inversions as a predictor of future recessions as a result of experience and observation unrelated to Austrian Business Cycle Theory (ABCT). Reference textbooks (Stigum and Crescensi, 2007) explain that capital allocators are pricing in future cuts to the central bank discount rate, thus inverting the yield curve. This ignores the role of free-market price signals in credit, which result from supply and demand fundamentals, and are the link connecting ABCT to term structures.The term structure of commodities markets is also affected by actual or anticipated shortfalls in production over different time horizons. This is widely understood, perhaps because settlement by physical delivery is commonplace and tangible (Hull, 2022). Even though credit and derivatives may at first glance seem more abstract, the same underlying market principles are at work there. The theoretical foundations of and recent work on ABCT provide the necessary tools to analyse both markets through the same lens.

Extraction of Anacardium occidentale: a kinetic, thermodynamic, phytochemical identification, and antibacterial study

Cashew tree biomass, Anacardium occidentale, represents an underutilized part of the plant and could have great potential for application in several areas, such as bioengineering, food science, and chemical. The stirred bed process was optimized to produce extracts from Anacardium occidentale stem bark (SBAo) and leaves (LAo) for bactericide purposes. Variables as alcohol content, stirring speed (SS), particle size (PS), solid-to-solvent ratio (S/S), temperature, and extraction time were evaluated. Subsequently, kinetic, thermodynamic and diffusivity fittings of the data were performed using different nonlinear models (Peleg, 2nd order, Elovich, power law, and Fick’s 2nd law) applied to the yield curves. Extracts were characterized by Fourier-transform infrared (FTIR) spectroscopy, total phenolic content (TPC), total flavonoid content (TFC), trolox equivalent antioxidant capacity (TEAC), and ultra-high resolution mass spectrometry (UHRMS) techniques for qualitative and quantitative determination of the phytochemicals. The optimized operating conditions obtained were ethanol in solvent at 70%, PS < 45 μm, 1200 rpm SS, 1/10 S/S ratio, and extraction time of 1 h at 50 ºC. The 2nd order kinetic model was the one that presented the best fits: SBAo (R2 > 0.9893 and RMSE < 3.4293) and LAo (R2 > 0.9985 and RMSE < 3.1117). Both A. occidentale extracts showed high levels of polyphenols and flavonoids, such as anacardic acid. Finally, the optimized extracts showed antibacterial susceptibility, with larger halos against S. aureus, 0.88± 0.07 mm (SBAo) and 0.45 ± 0.03 mm (LAo), in relation to E. coli, 0.80 ± 0.10 mm (SBAo) and 0.69 ± 0.08 mm (LAo).

Charging and Mobilization of Dust Particles on a Surface in Plasma.

We present first experimental results showing that single dust particles on a dielectric surface are mobilized and lofted due to exposure to an electron beam or ultraviolet radiation. It is shown that secondary electrons and/or photoelectrons emitted from a substrate surface are recollected on the surfaces within microcavities between a dust particle and the substrate surface, resulting in large negative charges and subsequently causing mobilization of the dust particle due to Coulomb repulsion. Dust mobility tested against the electron beam energy is shown to follow the secondary electron yield curve of the substrate surface in both the experimental and modeling results. The results verified the role of emitted electrons from the substrate surface in charging and mobilization of single dust particles.

Forecasting the yield curve: the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macro‐economic factors

In this article, we analyse the forecasting performance of several parametric extensions of the popular Dynamic Nelson–Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We also consider the role of several popular restrictions on the dynamics of the factors. Using a novel dataset of end‐of‐month continuously compounded Treasury yields on US zero‐coupon bonds and frequentist estimation based on the extended Kalman filter, we show that a second decay parameter does not contribute to better forecasts. In concordance with the preferred habitat theory, we also show that the best forecasting model depends on the maturity. For short maturities, the best performance is obtained in a heteroscedastic model with a time‐varying decay parameter. However, for long maturities, neither the time‐varying decay nor the heteroscedasticity plays any role, and the best forecasts are obtained in the basic DNS model with the shape of the yield curve depending on macroeconomic activity. Finally, we find that assuming non‐stationary factors is helpful in forecasting at long horizons.

Multiple yield curve modeling and forecasting using deep learning

AbstractThis manuscript introduces deep learning models that simultaneously describe the dynamics of several yield curves. We aim to learn the dependence structure among the different yield curves induced by the globalization of financial markets and exploit it to produce more accurate forecasts. By combining the self-attention mechanism and nonparametric quantile regression, our model generates both point and interval forecasts of future yields. The architecture is designed to avoid quantile crossing issues affecting multiple quantile regression models. Numerical experiments conducted on two different datasets confirm the effectiveness of our approach. Finally, we explore potential extensions and enhancements by incorporating deep ensemble methods and transfer learning mechanisms.

Decoding the Yield Curve: Understanding its Significance in Economic Forecasting

Throughout history, the Romanian yield curve has assumed various shapes that correspond to differing economic conditions, representing market sentiment and anticipation of future economic activity and interest rates. In times of economic stability and growth, the yield curve has generally exhibited an upward slope, signifying investor trust in continued economic expansion and expectations of future interest rate hikes. In contrast, during periods of economic uncertainty or downturns, the yield curve has often flattened or turned negative. A flattening curve suggests uncertainty about future economic conditions, while an inverted curve, where short-term yields surpass long-term yields, indicates significant economic stress and has traditionally been an accurate predictor of forthcoming recessions. These fluctuations offer essential insights for policymakers and investors, helping in the understanding and anticipation of economic trends and in the effective management of financial risks.

Fiscal spillover in emerging economies: Real versus financial channels

Fiscal policy is an important tool for business cycle stabilization and has significant spillover through real and financial channels. This paper estimates the spillover of US fiscal policy shock in emerging economies which is distinct from US monetary policy spillover. We find that - similar to its effect in advanced economies as documented in the literature - the shock lowers both the nominal and real policy rates in emerging economies. Results suggest a disconnect between long-term and policy rates that leads to the steepening of the yield curve in emerging economies in the medium term due to the shock. Most of these effects of US government expenditure shock on the policy rate and the yield curve in emerging economies are direct effects (financial channel) and not indirectly driven by the effect of this shock on GDP growth and inflation (real channel). Contrary to its effect in the US, we find that this shock leads to a prolonged appreciation of real effective exchange rates in emerging economies, hurts their external competitiveness, and leads to a contraction in output in emerging economies. As expected, countries having higher exports and trade-to-GDP ratio experience a bigger decline in output.