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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. [ABSTRACT FROM AUTHOR]

We quantify the impact of risk‐based and nonrisk‐based intermediary constraints (IC) on the term structure of covered interest rate parity (CIP) violations. Using a stochastic discount factor (SDF) inferred from interest rate swaps, we value currency derivatives. The wedge between model‐implied and observed derivative prices reflects the impact of nonrisk‐based IC because our SDF incorporates risk‐based IC. There is no wedge at short horizons, while the wedge accounts for 40% of long‐term CIP violations. Consistent with IC theory, the wedge correlates with the shadow cost of intermediary capital, and the SDF‐implied interest rate is a weighted average of collateralized and uncollateralized interest rates. [ABSTRACT FROM AUTHOR]

The presented paper discusses the production of radioactive ion beams of francium, radium, and actinium from thick uranium carbide (UC x ) targets at ISOLDE, CERN. This study focuses on the release curves and extractable yields of francium, radium and actinium isotopes. The ion source temperature was varied in order to study the relative contributions of surface and laser ionization to the production of the actinium ion beams. The experimental results are presented in the form of release parameters. Representative extractable yields per μ C are presented for 222 - 231 Ac, several Ra and Fr isotopes in the mass ranges 214 ≤ A ≤ 233 and 205 ≤ A ≤ 231 respectively. The release efficiency for several isotopes of each of the studied elements was calculated by comparing their yields to the estimated in-target production rates modeled by CERN-FLUKA. The maximal extraction efficiency of actinium was calculated to be 2.1(6)% for a combination of surface ionization using a Ta ion source and resonant laser ionization using the two-step 438.58 nm, and 424.69 nm scheme. [ABSTRACT FROM AUTHOR]

I analyze time series momentum along the Treasury term structure. Yield curve momentum is primarily due to changes in the level factor of yields. Because yield changes are partly induced by changes in the federal funds rate, yield curve momentum is related to post-FOMC (Federal Open Market Committee) announcement drift. The momentum factor is unspanned by the information in the term structure today and is hence inconsistent with standard term structure, macrofinance, and behavioral models. I argue that the results are consistent with a model with unpriced longer term dependencies. [ABSTRACT FROM AUTHOR]

Cocoa attainable yields are affected by a complex of pests and diseases in a particular agro-environment. Estimation of yield loss is critical for agronomic and economic decision-making at the farm level. For over 15 months, we monitored 1100 pods from six cocoa clones (PMCT-58, CC-137, CATIE-R1 CATIE-R4, ICS-95, and CCN-51) to assess the incidence of pests and diseases and to elucidate their survival behavior. Cocoa clones grow in a 12-year timber-based cocoa agroforestry plot (1330 cocoa plants ha-1, 100 shade trees ha-1, and 65% shade cover), in La Montaña, Turrialba, Costa Rica. Between 6-12 trees and 120-140 pods per clone of four size classes (very small - 2.5-7 cm, small - 7.1-14 cm, medium - 14.1-21 cm, and large - =21 cm) were tagged and measured fortnightly. Pods were selected at two vertical strata along the tree trunk (below and above 1.5 m) and grouped into three generations (rainy, transition, and dry). Competitive risk and survival analysis were performed per clone, generation, pod size class, and pod position along the tree trunk. Overall, pods reached maturity at the age of 155-165 days and were exposed to several hazards that disrupted their development. The Cox model that better described the cumulative risk during pod development included two covariables with substantial explicative power, generation, and clones. Regardless of clone and pod generation, a combination of diseases/pests accounted for about 45% to 65% of yield losses. The Kaplan-Meier survival analysis showed that pod survival was similar between generations but differed among clones within generations. Pods from CATIE-R1, CATIE-R4 and CC-137 clones showed greater survival rates than those of ICS-95, CCN-51 and PMCT-58 clones. The position of the pod along the tree trunk did not influence pod survival rates. We combined pod counting and pod survival rates calculated in this study and contrasted our yield estimations against a widely used prediction method proposed by a certification body. Overall, yield estimated using the UTZ method applied to 90-day-old pods of CATIE-R1 clone consistently overestimated yield predictions in the range of 27-45%. We proposed the combination of pod counting and pod index with a set of clone-specific discount factors; the survival rates, to reliably forecast on-farm cacao yields over time. [ABSTRACT FROM AUTHOR]

Several authors, especially those who share a Classical–Keynesian point of view, argue that the interest rate determines the rate of profit in the long run. Considering the eleven founding economies of the euro area, I find that, adjusted for the rate of growth of gross national income, there is a positive long-term relationship between the real interest rate and the net rate of profit. The results are confirmed even when I estimate a model with nominal interest rates, inflation, and a yield curve. These results imply that the European Central Bank (ECB), when deciding monetary policy, is not neutral in determining income distribution. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications. [ABSTRACT FROM AUTHOR]

Aim: The variability in regional species richness is determined by the balance between speciation, extinction, and migration, but the underlying causes of high species richness in some regions (e.g. tropics, Mediterranean ecosystems) are challenging to explain. Species richness variability may be amplified by biotic feedbacks that promote species richness in some areas, while decreasing elsewhere. Following the example of species abundance, we speculated that species richness per area in arbitrary geographic units (e.g. quarter‐degree squares) follows a hollow‐shaped curve with the ranks of species richness to yield a species richness rank (SRR) curve. The hollowness of such an SRR curve may indicate biotic feedbacks. Location: South Africa, South West Australia, and global. Materials and Methods: We used vascular plant (VP) and bird data from distinct geographic regions and global syntheses of VP, bird, mammal, and amphibian species richness. These data were subdivided into geographic grids and the deviation from normality of the species richness quantified using skewness and kurtosis and the values ranked to yield SRR curves. Results: These SRR curves all had a consistent hollow shape (corresponding skewness 1.08–3.4, kurtosis 0.23–18.40) distinct from a normal distribution arising if species were allocated randomly to geographic units. The SRR curves indicate that relatively species‐rich regions are rare, while species‐poor areas are common. Main Conclusions: Neutral processes, abiotic determinants, environmental heterogeneity, historical factors (e.g. climate stability), and biotic feedbacks all likely play a role in contributing to the shapes of the curves. Although these curves for diverse taxa and regions integrate these multiple drivers of species richness, they indicate an acceleration of species richness as a function of species richness as a result of speciation and/or immigration, limited by increasing extinction likelihood. Biotic feedbacks provide a parsimonious explanation for the shapes of the SRR curves across taxa and regions. [ABSTRACT FROM AUTHOR]

We examine the impact of global geopolitical risk (GPR) measures on US Treasuries' returns and volatilities, differentiating between long- and short-run investment behaviours among an array of time-to-maturities ranging from 1 month to 30 years, taking into account various economic and financial factors. Using monthly data and a panel autoregressive distributed lag (ARDL) model, the results indicate a negative long-run relationship between US Treasuries' returns and the global GPR index. These results generally hold when we consider geopolitical threats and geopolitical acts, although they exhibit some discrepancies between these two components and across the yield curve. Further results show a positive and strong long-run relationship between the US Treasuries' realized volatilities and the various geopolitical risk measures. The evidence holds true when we disentangle 'bad' from 'good' realized volatilities, although the impact of bad volatility is stronger than that of good volatility, which points to an asymmetric effect of realized volatility in US Treasuries. A sub-sample analysis suggests the robustness of the main results. Our analyses provide the first empirical evidence of the information content of GPR for US Treasury securities' returns and volatilities, which matters to fixed-income investors and decision-makers at the Federal Reserve. [ABSTRACT FROM AUTHOR]

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Time-varying parameter (TVP) regression models can involve a huge number of coefficients. Careful prior elicitation is required to yield sensible posterior and predictive inferences. In addition, the computational demands of Markov Chain Monte Carlo (MCMC) methods mean their use is limited to the case where the number of predictors is not too large. In light of these two concerns, this paper proposes a new dynamic shrinkage prior which reflects the empirical regularity that TVPs are typically sparse (i.e. time variation may occur only episodically and only for some of the coefficients). A scalable MCMC algorithm is developed which is capable of handling very high dimensional TVP regressions or TVP Vector Autoregressions. In an exercise using artificial data we demonstrate the accuracy and computational efficiency of our methods. In an application involving the term structure of interest rates in the eurozone, we find our dynamic shrinkage prior to effectively pick out small amounts of parameter change and our methods to forecast well. [ABSTRACT FROM AUTHOR]

We show that the slope of the sovereign yield curve predicts future economic activity not only through its level but also through its changes (or differences) over time. Our results with US data show that the additional inclusion of the changes of the yield slope in the traditional regressions significantly increases the explanatory power of the yield curve. Through the yield slope decomposition, we find that positive changes in both the risk‐neutral spread and the term premium increase the likelihood of recession in the next 3 or 12 months. Estimated linear equations that directly forecast economic activity confirm the predictive power of both components in the medium run. These predictive equations also identify the term premium as the relevant component of yield slope changes for medium‐run (3–12 months) forecasts. Our out‐of‐sample exercises show that the empirical models including both the level and the differences of the slope perform better than the models including only the yield slope level. [ABSTRACT FROM AUTHOR]

We study the recent Australian experience with yield curve control (YCC) as perhaps the best evidence of how this policy might work in other developed economies. YCC seemingly worked well in 2020, when the market expected short rates to stay at zero for a long period of time. As the global recovery and inflation gained momentum in 2021, liftoff expectations moved up, the Reserve Bank of Australia purchased most of the targeted government bond outstanding, and the target bond's yield dislocated from other financial market instruments. The evidence suggests that central bank bond purchase programs can operate more narrowly than previously considered. [ABSTRACT FROM AUTHOR]

We estimate a model-free term structure of the ex ante dividend risk premium by combining two data sets with different information about future dividends. We aggregate survey forecasts about future dividends for single companies over multiple horizons to construct a term structure of expected S&P 500 dividend growth rates. We use European call and put option prices on the S&P 500 to estimate the term structures of options-implied dividend growth rates and risk-free rates. Applying the method to 2004–2021 data offers a new, ex ante perspective on the conditional time variation of the term structure of the dividend risk premium. [ABSTRACT FROM AUTHOR]

Crushable foam plasticity models are employed to simulate material response under essentially monotonic loading. For the plastic part of the behavior, the default crushable foam model in Abaqus/Explicit is the volumetric hardening model, where the yield surface evolves by the volumetric compacting plastic strain, and the other available model is the isotropic hardening model, where the yield curve is centrally located at the origin in the pressure—the Mises stress plane. In this study, the characteristic of two models was examined by applying them to a simple 18650 lithium-ion cylindrical cell. The computation cell model consists of the shell casing and the homogenized jelly roll which represents the electrode assembly. Both crushable foam models were calibrated to represent the homogenized mechanical properties of the jellyroll, and the load–displacement relations were compared with the experimental results. Then, we examined the deformation characteristic of jellyroll for each crushable foam model. [ABSTRACT FROM AUTHOR]

We propose a new approach to portfolio optimization that utilizes a unique combination of synthetic data generation and a CVaR-constraint. We formulate the portfolio optimization problem as an asset allocation problem in which each asset class is accessed through a passive (index) fund. The asset-class weights are determined by solving an optimization problem which includes a CVaR-constraint. The optimization is carried out by means of a Modified CTGAN algorithm which incorporates features (contextual information) and is used to generate synthetic return scenarios, which, in turn, are fed into the optimization engine. For contextual information, we rely on several points along the U.S. Treasury yield curve. The merits of this approach are demonstrated with an example based on 10 asset classes (covering stocks, bonds, and commodities) over a fourteen-and-half-year period (January 2008–June 2022). We also show that the synthetic generation process is able to capture well the key characteristics of the original data, and the optimization scheme results in portfolios that exhibit satisfactory out-of-sample performance. We also show that this approach outperforms the conventional equal-weights (1/N) asset allocation strategy and other optimization formulations based on historical data only. [ABSTRACT FROM AUTHOR]

The article focuses on the impact of COVID-19 on mental health services in rural areas, highlighting challenges like access barriers and innovations such as telehealth services and community outreach programs. Topics include the adaptation of mental health support during the pandemic, the role of telemedicine in reaching rural populations, and strategies for addressing access challenges in rural communities.

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change. [ABSTRACT FROM AUTHOR]

A reverse event study approach was used to investigate how the South African sovereign bond yield curve reacts to headline news. The change in daily yields, calculated as the difference between the natural log of zero-coupon yields on consecutive business days, were used in the analysis. Dates of abnormal daily yield changes were identified using GARCH models. News items for the sample period were classified into categories using supervised machine learning. A regression model was fitted to determine the link between the abnormal yield changes and the news categories. The results indicated that, for abnormal increases in yield (negative news), political news had an impact on all nodes. For abnormal decreases in yield (positive news), economic news had the greatest impact on the 10-year and political news on the 15- and 20-year nodes of the yield curve. [ABSTRACT FROM AUTHOR]

This article proposes a novel perspective on the term structure of market equity yields. Instead of using market dividend futures, we aggregate equity yields of individual firms to estimate the market equity yield curve. This approach allows studying the aggregation effect that shapes the market equity yield curve. During the period from 1990 to 2019, we find a positive aggregation effect: companies with high equity yields were expected to grow at higher rates than companies with low equity yields. Thus, high-yield companies were expected to generate an increasing share of total market dividends when expanding the investment time horizon. Under the assumption of flat firm-risk premia, this implies an upward-sloping term structure of equity risk premia. Together with the concave bond yield curve, the market equity yield curve was upward-sloping. [ABSTRACT FROM AUTHOR]

This paper provides a nonparametric test for deciding the dimensionality of a policy shock as manifest in the abnormal change in asset returns' stochastic covariance matrix, following the release of a macroeconomic announcement. We use high-frequency data in local windows before and after the event to estimate the covariance jump matrix and then test its rank. We find a one-factor structure in the covariance jump matrix of the yield curve resulting from the Federal Reserve's monetary policy shocks before the 2007–2009 financial crisis. The dimensionality of policy shocks increased afterwards because of the use of unconventional monetary policy tools. [ABSTRACT FROM AUTHOR]

In the post epidemic period, it is important to clarify the relationship between economic growth and tourism growth. The aim of this study is to characterize the co-movement between expected macroeconomic conditions and inbound tourism, focussing on the nonlinear relationship between these variables. Dynamic copula-based GJR-GARCH models are employed to measure nonlinear dependence. Total inbound tourism to Thailand and its disaggregation for its 10 main origin countries, are considered in the empirical study. The results show that there exists significant co-movement between expected economic growth and inbound tourism, and prove the importance of considering nonlinearities and extreme events. Also, copula nonlinear Granger causality is used to conclude that inbound tourism and expected economic growth have nonlinear bi-directional and unidirectional Granger causality relationship. Finally, this paper puts forward some policy suggestions to restore tourism and boost economic growth in the post epidemic period. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to price bonds jointly issued by a group of countries—Eurobonds in the euro-area context. We consider two types of bonds; the first is backed by several and joint guarantees (SJGs), and the second features several but not joint guarantees (SNJGs). The pricing of SJG and SNJG bonds reflects different assumptions regarding the pooling of debtors' fiscal resources. We estimate fiscal limits for the six largest euro-area economies over 2008–2021 and deduce counterfactual Eurobond prices. For the five-year maturity, SNJG bond yield spreads would have been about three times larger than SJG ones over the estimation sample. Hence, issuing SJG bonds could result in gains at the aggregate level. Notwithstanding, our model also predicts that gains may temporarily vanish in periods of acute fiscal stress. We finally envision postissuance redistribution schemes, whereby gains stemming from the issuance of SJG bonds could be shared among participating countries; we argue that these schemes may alleviate the reduction in market discipline resulting from common bonds issuance. This paper was accepted by David Sraer, finance. Funding: This work has benefited from financial support from the Swiss National Science Foundation [Grant 182293]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4740. [ABSTRACT FROM AUTHOR]

We consider an HJM model setting for Markov-chain modulated forward rates. The underlying Markov chain is assumed to induce regime switches on the forward curve dynamics. Our primary focus is on the interest rate and energy futures markets. After deriving HJM-drift conditions for the two markets, we prove under the assumption of affine structure for the term structure that the forward curves are solutions to specific systems of ODEs that can be solved explicitly in many cases. This allows for a tractable model setting, and we present an algorithm for obtaining consistent forward curve models within our framework. We conclude by presenting some numerical examples and an application to real data under a one-factor Gaussian model setting. [ABSTRACT FROM AUTHOR]

A special case of the structural model of a hybrid composite multidirectional-reinforced in the plane was considered, which makes it possible to calculate the yield curve of a composite in the space of principal averageв stresses in a plane stress state (PSS). The composite contains an even number of reinforcing fiber families, which are divided into pairs of families. In each pair of the families, the fibers are made of the same material and are laid symmetrically with respect to the directions of principal stresses in the composite. The constituents of the reinforced composite are isotropic and have different tensile–compressive yield strengths. The mechanical behavior of composition constituents was described by the associated flow rule of an ideal rigid-plastic body with piecewise quadratic and piecewise linear yield curves in the space of principal stresses. The influence of approximation parameters of yield curves of composition constituents in the principal stresses and reinforcement parameters on the shape and dimensions of the yield curves of compositions was studied. It was demonstrated that the plastic flow in a fibrous medium is associated with the calculated yield curves of compositions. [ABSTRACT FROM AUTHOR]

The unbiased expectation theory stipulates that long-term interest rates are determined by the market's expectations of future short-term interest rates. According to this hypothesis, if investors have unbiased expectations about future interest rate movements, the forward interest rates should be good predictors of future spot interest rates. This hypothesis of the term structure of interest rates has long been a subject of debate due to empirical and theoretical challenges. Despite extensive research, a satisfactory explanation for the observed systematic difference between future spot interest rates and forward interest rates has not yet been identified. In this study, we approach this issue from an arbitrage theory perspective, leveraging on the connection between the expectation hypothesis and changes in probability measures. We propose that the observed bias can be explained by two adjustments: a risk premia adjustment, previously considered in the literature, and a stochastic adjustment that has been overlooked until now resulting from two measure changes. We further demonstrate that for specific instances of the Vasicek and Cox, as well as the Ingersoll and Ross, stochastic interest rate models, quantifying these adjustments reveals that the stochastic adjustment plays a significant role in explaining the bias, and ignoring it may lead to an overestimation of the required risk premia/aversion adjustment. Our findings extend beyond the realm of financial economic theory to have tangible implications for interest rate modelling. The capacity to quantify and distinguish between risk and stochastic adjustments empowers modellers to make more informed decisions, leading to a more accurate understanding of interest rate dynamics over time. [ABSTRACT FROM AUTHOR]

This article considers a first order continuous time vector autoregression with random coefficients. We discuss some difficulties that arise when the exact discrete analogue is used for estimating the continuous time parameters and provide an estimation method based on an approximate discrete model. Some expressions for the estimator of the drift parameter matrix, for its approximated bias and for the covariance matrix of the parameter estimates are derived. The finite sample performance of the proposed method is studied by a Monte Carlo experiment. We also illustrate the advantages of our model in an application on the expectations theory of the term structure of interest rates. Results show that the performance of the proposed methodology is good, and allowing for time variation on coefficients results in large reductions in the root mean square error of the parameter estimates. [ABSTRACT FROM AUTHOR]

It is extremely challenging to design a model calibrating both SPX and VIX option prices. A long‐standing conjecture due to Julien Guyon is that it may not be possible to calibrate these two quantities with a continuous model. So far, most studied continuous time models are affine, so we investigate the conjecture among 14 well‐known non‐affine local stochastic volatility models in this article. First, we propose a unified efficient willow tree method for S&P500 and VIX option pricing under non‐affine models. Second, we compare the joint calibration performance on these 14 models on the S&P500 and VIX option prices data from 2006 to 2019. We find that the VIX option price data can provide extra information of the variance dynamics of the models, and the non‐affine structure and the volatility with linear, rather than square‐root, diffusion process provide a better fit for the both data sets than the affine counterparts. Among the 14 stochastic models, the SABR model provides the best in‐ and out‐of‐sample performance (in terms of mean square error) regardless of the state of the economy. Nevertheless, even for the best‐fitted SABR model, the relative error on the VIX option is still around 18%, still quite significant. Therefore, we found the non‐affine and local volatility structure improve the joint calibration but are still far from satisfactory. [ABSTRACT FROM AUTHOR]

Traditional theories of term structure of interest rate consist of four major classical theories, including Pure Expectation Theory, Liquidity Preference Theory, Preferred Habitat Theory and Market Segmentation Theory. However, they cannot be well interpreted by the traditional static term structure of interest rate methods such as polynomial spline and exponential spline. To address problems on low precision and weak stability of traditional methods in constructing static interest rate term structure curve, in this paper, we introduce the tension interpolation spline based on a fourth-order differential equation with local tension parameters calculated by Generalized Reduced Gradient (GRG) algorithm. Our primary focus is to illustrate its better prediction effect and stability with an empirical study conducted using datum of treasury bonds. Then, we divided the datum into intra-sample datum for estimating tension parameters and out-of-sample datum for evaluating their robustness of predicting stochastics collected from Shanghai Stock Exchange on 2nd February, 2019. According to the principle of total least squares and total least absolute deviations, the result shows that the tension interpolation spline model has better precision and stronger stability in prediction of out-of-sample treasury bonds prices compared with the model established by polynomial spline and exponential spline. In addition, it can better explain the Liquidity Preference Theory, which confirms that it is suitable for constructing the static term structure of interest rates in the securities exchange market. [ABSTRACT FROM AUTHOR]

Total housing real returns in large agglomerations in Kazakhstan are approximately 1% per year lower than in the rest of the country. Our results are also supportive of emerging literature, that housing real rent returns, adjusted for population, are generally lower in large agglomerations compared to the rest of the country. We indicate that within‐country heterogeneity of housing returns mainly result from the spatial concentration of economic activity in urban centers. Our findings also suggest that residential real estate in a developing economy produces higher returns compared to financial capital over the long‐run. At the same time, the volatility of holding housing investment is substantially higher than its "safe" alternative (i.e. deposit rate paid for savings deposits). As such, "Yield Curves for Main Street" concept refers to the general positive spread between total housing returns and financial capital returns in a developing economy. [ABSTRACT FROM AUTHOR]

The debt-to-GDP ratio negatively predicts cumulative nominal consumption growth up to a 10-year horizon, resulting from the ratio's ability to forecast lower inflation and real growth. Moreover, the debt-to-GDP ratio is positively associated with yield spreads. I rationalize these facts in a model in which positive shocks to government debt cause lower inflation and growth, making bonds attractive assets. Furthermore, because longer-term bonds are less exposed to current debt shock than are shorter-term bonds, they are better hedges, resulting in high yield spreads in high-debt states. The model highlights the importance of fiscal risk in understanding the Treasury bond market. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

The large amplitude oscillatory shear (LAOS) has been extensively studied for understanding the rheological responses of yield stress fluids. However, the employed methodology for determining the yield stress remains uncertain albeit the fact that many classical or plausible methods exist in the literature. Along these lines, herein, based on Fourier transform (FT) rheology, stress decomposition, and stress bifurcation, a new straightforward method termed as algebraic stress bifurcation was developed. More specifically, the main goal was to determine the yield stress and investigate the solid–liquid transition of fluids in LAOS. A simple and efficient mathematical framework was established and verified by the KVHB, Saramito, Giesekus models, and FT rheology. The main strength of this approach is that only the data from the stress/strain sweep are required instead of Lissajous curves. Alternative curves based on the first harmonic were constructed to demonstrate the non-critical role of both higher harmonics and phenomenological Lissajous curves in determining yield stress. The determined start and end yield points in the solid–liquid transition were compared with the already existing methods. Furthermore, the resulting solid–liquid transition region was analyzed by FT rheology, stress decomposition, and sequence of the physical process to obtain information on nonlinearity and intracycle/intercycle yielding. Our work provides fruitful insights for explaining and reducing the complexities of the stress bifurcation technique by using an easy-to-understand and implement format. Therefore, a concise theoretical framework was introduced for understanding the concept of yield stress, the intercycle yielding process, and the rational choice of yield stress measurement techniques. [ABSTRACT FROM AUTHOR]

Single-point incremental forming (SPIF) has emerged as a cost-effective and rapid manufacturing method, especially suitable for small-batch production due to its minimal reliance on molds, swift production, and affordability. Nonetheless, SPIF's effectiveness is closely tied to the specific characteristics of the employed sheet materials and the intricacies of the desired shapes. Immediate experimentation with SPIF often leads to numerous product defects. Therefore, the pre-emptive use of numerical simulations to predict these defects is of paramount importance. In this study, we focus on the critical role of the forming limit curve (FLC) in SPIF simulations, specifically in anticipating product fractures. To facilitate this, we first construct the forming limit curve for Al1050 sheet material, leveraging the modified maximum force criterion (MMFC). This criterion, well-established in the field, derives FLCs based on the theory of hardening laws in sheet metal yield curves. In conjunction with the MMFC, we introduce a graphical approach that simplifies the prediction of forming limit curves at fracture (FLCF). Within the context of the SPIF method, FLCF is established through both uniaxial tensile deformation (U.T) and simultaneous uniform tensile deformation in bi-axial tensile (B.T). Subsequently, the FLCF predictions are applied in simulations and experiments focused on forming truncated cone parts. Notably, a substantial deviation in fracture height, amounting to 15.97%, is observed between simulated and experimental samples. To enhance FLCF prediction accuracy in SPIF, we propose a novel method based on simulations of truncated cone parts with variable tool radii. A FLCF is then constructed by determining major/minor strains in simulated samples. To ascertain the validity of this enhanced FLCF model, our study includes simulations and tests of truncated cone samples with varying wall angles, revealing a substantial alignment in fracture height between corresponding samples. This research contributes to the advancement of SPIF by enhancing our ability to predict and mitigate product defects, ultimately expanding the applicability of SPIF in diverse industrial contexts. [ABSTRACT FROM AUTHOR]

In this paper, we derive the Laplace transforms, i.e., expected values of the exponentials, of time integrals of a class of Extended Cox–Ingersoll–Ross (CIR) processes which are given as the product of a standard CIR process and a positive deterministic function. Assuming such a process for the short-rate gives rise to an affine term structure model for which we can now provide the bond price formulas that had so far not been accessible by attempting to solve the usual Riccati equation. By conditioning the exponentiated time integral on the potential states of the integrated process at its endpoint, we obtain the building blocks to evaluate certain interest rate derivatives, namely Bermudan swaptions. This is achieved by an algorithm that determines the exercise decision at each state by comparing the available payoff with an explicit lower bound built from such conditional Laplace transforms, without resorting to estimation techniques such as American Monte Carlo. [ABSTRACT FROM AUTHOR]

In this paper we presented a method of G² Hermite interpolation of offset curves of regular plane curves based on approximating the normal vector fields. We showed that our approximant is also C¹ Hermite interpolation of the offset curve. Our method is capable of achieving circular precision. Another advantage of our method is that if the input curve is a polynomial curve, then our method also yields a polynomial curve. Our approximation method was applied to numerical examples and its numerical results were compared to previous offset approximation methods. It was observed that our method is almost optimal with respect to the number of control points of the approximation curves for the same tolerance. [ABSTRACT FROM AUTHOR]

Functional data are frequently accompanied by a parametric template that describes the typical shapes of the functions. However, these parametric templates can incur significant bias, which undermines both utility and interpretability. To correct for model misspecification, we augment the parametric template with an infinite-dimensional nonparametric functional basis. The nonparametric basis functions are learned from the data and constrained to be orthogonal to the parametric template, which preserves distinctness between the parametric and nonparametric terms. This distinctness is essential to prevent functional confounding, which otherwise induces severe bias for the parametric terms. The nonparametric factors are regularized with an ordered spike-and-slab prior that provides consistent rank selection and satisfies several appealing theoretical properties. The versatility of the proposed approach is illustrated through applications to synthetic data, human motor control data, and dynamic yield curve data. Relative to parametric and semiparametric alternatives, the proposed semiparametric functional factor model eliminates bias, reduces excessive posterior and predictive uncertainty, and provides reliable inference on the effective number of nonparametric terms—all with minimal additional computational costs. [ABSTRACT FROM AUTHOR]

We present a novel framework to predict recessions, the depth of recessions (mild or severe) and monetary policy pivots. The first phase introduces three ways to predict recessions. The first method evaluates the effectiveness of a few inverted U.S. Treasury yield curves. The second approach identifies a threshold between the federal funds rate and the 10-year Treasury yield. The final tool employs Probit modeling. The second phase of our analysis utilizes the 10-year/1-year Treasury yield spread to predict the duration of a recession. Historically, 12 consecutive months of a negative 10-year/1-year spread is associated with deeper recessions. When evaluating the tools using data going back to 1955, the 10-year/1-year spread has predicted all 10 recessions with an average lead time of 12 months. The 10-year/FFR threshold has predicted all recessions and monetary policy pivots with an average lead time of 18 months. At present, all three tools are signaling that a recession and/or Fed policy pivot is more likely than not within the next year. Through June 2023, the 10-year/1-year spread has remained negative for 12 consecutive months, which highlights the risk that an upcoming recession may not be mild. Given the historical accuracy of our framework, decision-makers may consider a possibility that the upcoming recession may be severe. [ABSTRACT FROM AUTHOR]

Although China's monetary and financial system differs drastically from its Western counterpart, empirical studies covering this vast economy have often been simple reestimations or recalibrations of models originally designed to describe US or European monetary policy. In this paper, we aim to assess Chinese monetary policy and, in particular, monetary policy transmission through yield curves into the real economy. Our study takes into account the peculiarities of the Chinese economy: Namely, our model includes both China's modern attempts at a market-based monetary policy as well as the "authority-based" one that is a relic of the original banking system. Besides, it considers the special nature of the Chinese treasury bond market, which is separated into two independent ones with very limited direct arbitrage opportunities between almost identical assets. Finally, it incorporates the role of real estate, which played an essential role in China during the last decade. Our results show that different monetary policy shocks cause asymmetric effects on macroeconomic and financial variables. [ABSTRACT FROM AUTHOR]

Ultrasonic waves are capable of helping characterize pores of rocks. A model of viscous squirt is used to simulate phase velocity and the quality factor of ultrasonic P-wave measured in water-saturated Spergen limestone, thus determining pore parameters of the limestone. The measured P-wave had a centroid frequency of ∼0.75 MHz, and two simulations are conducted in this paper. The first simulation yields a dispersion curve with a dipping spike followed by a rising spike. However, it cannot yield the measured quality factor. Another drawback is that one of the pore parameters violates rock physics. The second simulation yields a dispersion curve with a small velocity depression followed by an upward velocity concave; the measured phase velocity and quality factor are simultaneously predicted. The resulting dimensions of the rock unit are 0.3 by 0.333 mm, which is consistent with the mean grain diameter of 0.3 mm. The relative first and second porosities are ascertained to be 0.97 and 0.03, respectively. The aperture distance at contact of grains is inverted as 1.8 µm. Remarkably, the minimum phase velocity of the water-saturated limestone is lower than the Gassmann velocity. [ABSTRACT FROM AUTHOR]

This paper assesses the possible development of government interest expenditures for Germany, France, Italy and Spain. Until 2021, governments could anticipate a substantial further reduction in interest expenditure. This outlook has changed drastically with the surge in inflation and government bond rates. Assuming that bond rates remain at the levels implied by yield curves from December 2022, interest expenditure rises substantially. We also examined scenarios with a further upward shift in yield curves by one or two percentage points. They indicate major medium‐term risks for highly indebted member states with interest expenditure approaching or exceeding levels last observed on the eve of the euro area debt crisis. Governments should take action to achieve a decline in debt‐to‐GDP ratios towards safe levels. They need to make sure public debt remains sustainable at the higher interest rates that are required to achieve price stability in the euro area. [ABSTRACT FROM AUTHOR]

The paper examines whether certain macrofinancial indicators can be used for early detection of recessions. Analysing a sample of small open economies from Central and Eastern European Union, we first identify the most important indicators used for early detection of recessions, and then test the validity of the selection by using the signal method and multivariate probit regressions. Our results imply that the most effective predictors of upcoming recessions are the slope of the yield curve, current account balance to GDP ratio, real estate price index, self-financing ratio of commercial banks, nominal effective exchange rate, global exports and LIBOR rate. Using the Mann-Whitney U Test, we also find that foreign indicators emit earlier signals of incoming recessions in analysed countries than domestic ones. This type of research is important because of the various stakeholders that base their decisions on the signals provided by these indicators. Primarily, these are various government agencies that participate in monetary and fiscal policy making. Early warning of an impending recession allows economic policy makers to take corrective action to avoid a recession or to significantly mitigate its effects, while unreliable indicators may lead to adoption of unnecessary measures with adverse effects on the economy. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

We analyze the predictive ability of real‐time macroeconomic information for the yield curve of interest rates. We specify a mixed‐frequency macro‐yields model in real time that incorporates interest rate surveys and treats macroeconomic factors as unobservable components. Results indicate that real‐time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real‐time macro data. We also find that interest rate surveys can have significant predictive power over and above real‐time macroeconomic variables. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a multi-curve model under the historical probability based upon multiplicative relative spreads, inspired by the HJM and affine factor approaches, which implies positive and ordered spreads. In particular, we focus upon δi-XIBOR relative (instantaneous) forward rates and appropriate XIBOR HJM drift constraints, and we describe the dynamics of the different forward rates and spreads under different measure changes (including forward measures).We introduce an explicit model satisfying both the XIBOR HJM drift constraints as well as the property of positive and ordered spreads. We demonstrate the flexibility of this model for derivative pricing by focusing upon the price of a caplet and of options with a payoff based upon XIBOR forward prices with different tenors. We perform on one hand a calibration of the model based upon cap prices. On the other hand, we do an estimation of a spread curve in our proposed model under the historical probability by using a Kalman filter approach. Numerical results are included, and they confirm that the model performs very well. [ABSTRACT FROM AUTHOR]

The 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. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

While there is a large literature on modeling volatility smile in options markets, most such studies are eventually focused on the forecasting performance of the model parameters and not on the applicability of the models in a trading environment. Drawing on the analogy of volatility smile like a term structure in the context of interest rates in fixed‐income markets, we evaluate the performance of the Dynamic Nelson–Siegel (DNS) approach to modeling the dynamics of volatility smile in a trading environment against competing alternatives. Using model‐based mispricing as our sorting criterion, and deploying a trading strategy of going long the options in the upper deciles and going short the options in the lower deciles, we show that dynamic models consistently outperform their static counterparts, with the worst dynamic model outperforming the best static model in terms of the percentage of mean returns from the trading portfolios and the Sharpe ratio. Specifically, we find that the DNS model consistently outperforms all other competing specifications on most of our selected criteria. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore the failures of Tunisian secondary corporate bond market liquidity to understand the determinants of corporate bond market liquidity at large. Design/methodology/approach: We adopted a qualitative approach to studying the Tunisian Stock Exchange. Dealers' perceptions were collected through semi-structured face-to-face interviews; the data was recorded, transcribed and thematically analysed. Findings: Secondary corporate bond market failures are due, in part, to microstructural choices – especially the use of an over-the-counter market as a trading venue. The absence of a corporate bond yield curve, a narrow investor base, market participants' lack of financial education and authorities' attitudes are equally responsible. Research limitations/implications: This study is useful to researchers, policymakers and practitioners, as it identifies microstructural and other factors affecting the Tunisian secondary corporate bond market. We interviewed only Tunisian dealers while ignoring other categories of market participants. Furthermore, a focus group discussion could have improved our understanding of the determinants of the Tunisian secondary corporate bond market. Originality/value: This paper aimed to qualitatively discuss several issues related to the Tunisian secondary corporate bond market. To date, little academic research has addressed this topic in the illiquid and non-transparent corporate bond markets. [ABSTRACT FROM AUTHOR]