Forward Rate Research Articles

Ideal gas reference for association/dissociation reactions: Concentration bias and kinetic reference voltage/potentials in electrolysis.

The water electrolysis reaction involves a large kinetic overvoltage, and considerable research efforts are currently devoted to the search for better electrocatalysts. It is commonly expected that, at least, in principle, an ideal electrocatalyst would enable significant reaction rates close to the equilibrium voltage. In the present work, we question this expectation. For reactions, such as water electrolysis, which involve a significant change in the concentration between the reactant and product states, the position of the equilibrium voltage generally becomes decoupled from the onset of macroscopic kinetic currents. The reason is the dependence of the equilibrium voltage on the concentrations of both reactant and product species, whereas the forward rate of the reaction does not, in general, depend on the latter. Based on a new ideal gas reference for association/dissociation reactions, we develop a formalism to decompose the equilibrium voltage of electrolysis reactions into two distinct contributions: first, a contribution due to unbalanced relative concentrations between reactants and products second, a contribution due to the (mis)alignment of reactant and product states within the potential energy surface. The latter defines an intrinsic "kinetic reference voltage" that agrees remarkably well with the experimentally observed onset of water electrolysis, providing a new perspective on the origin of a significant fraction of the respective overvoltage. We expect the concept of kinetic reference voltages/potentials to be also useful in the context of other reactions involving significant concentration changes from the reactant to the product.

Dynamics of two-step reversible enzymatic reaction under fractional derivative with Mittag-Leffler Kernel.

Chemical kinetics is a branch of chemistry that is founded on understanding chemical reaction rates. Chemical kinetics relates many aspects of cosmology, geology, and even in some cases of, psychology. There is a need for mathematical modelling of these chemical reactions. Therefore, the present research is based on chemical kinetics-based modelling and dynamics of enzyme processes. This research looks at the two-step substrate-enzyme reversible response. In the two step-reversible reactions, substrate combines with enzymes which is further converted into products with two steps. The model is displayed through the flow chart, which is then transformed into ODEs. The Atangana-Baleanu time-fractional operator and the Mittag-Leffler kernel are used to convert the original set of highly nonlinear coupled integer order ordinary differential equations into a fractional-order model. Additionally, it is shown that the solution to the investigated fractional model is unique, limited, and may be represented by its response velocity. A numerical scheme, also known as the Atangana-Toufik method, based on Newton polynomial interpolation technique via MATLAB software, is adopted to find the graphical results. The dynamics of reaction against different reaction rates are presented through various figures. It is observed that the forward reaction rates increase the reaction speed while backward reaction rates reduce it.

Investigations of Vacancy-Assisted Selective Detection of NO2 Molecules in Vertically Aligned SnS2.

Two important methods for enhancing gas sensing performance are vacancy/defect and interlayer engineering. Tin sulfide (SnS2) has recently attracted much attention for sensing of the NO2 gas due to its active surface sites and tunable electronic structure. Herein, SnS2 has been synthesized by the chemical vapor deposition (CVD) method followed by nitrogen plasma treatment with different exposure times for fast detection of NO2 molecules. Plasma treatment created a substantial number of surface vacancies on SnS2 flakes, which were controlled by the exposure period to modify the surface of flakes. After 12 min of nitrogen plasma treatment, SnS2 nanoflakes show considerable improvement in NO2 sensing characteristics, including a high sensing response of ∼264% toward 100 ppm NO2 at 120°C. The enhancement in the relative response of the sensor is due to the electronic interaction between NO2 molecules and the S vacancies on the surface of SnS2. Density functional theory (DFT) computations indicate that the S-vacancy defects on the surface dominate the effective NO2 detection and the NO2 adsorption mechanism transition from physisorption to chemisorption. Adsorption kinetics of the NO2 gas over SnS2 nanoflake-based chemiresistor sensors were studied using the Lee and Strano model [ Langmuir 2005, 21(11), 5192-5196]. The irreversible rate of the reaction for various NO2 concentrations exposed to the gas sensor is extracted using this model, which also appropriately describes the response curves. The forward rate constant of the irreversible gas sensor increased with the increase of the N2 plasma treatment time and reached the maximum in the 12 min plasma-treated sample. Through defect engineering, this research may open up new vistas for the design and synthesis of 2D materials with enhanced sensing properties.

The effect of thermal non-equilibrium on kinetic nucleation

Context. Nucleation is considered to be the first step in dust and cloud formation in the atmospheres of asymptotic giant branch (AGB) stars, exoplanets, and brown dwarfs. In these environments dust and cloud particles grow to macroscopic sizes when gas phase species condense onto cloud condensation nuclei (CCNs). Understanding the formation processes of CCNs and dust in AGB stars is important because the species that formed in their outflows enrich the interstellar medium. Although widely used, the validity of chemical and thermal equilibrium conditions is debatable in some of these highly dynamical astrophysical environments. Aims. We aim to derive a kinetic nucleation model that includes the effects of thermal non-equilibrium by adopting different temperatures for nucleating species, and to quantify the impact of thermal non-equilibrium on kinetic nucleation. Methods. Forward and backward rate coefficients are derived as part of a collisional kinetic nucleation theory ansatz. The endother-mic backward rates are derived from the law of mass action in thermal non-equilibrium. We consider elastic collisions as thermal equilibrium drivers. Results. For homogeneous TiO2 nucleation and a gas temperature of 1250 K, we find that differences in the kinetic cluster temperatures as small as 20 K increase the formation of larger TiO2 clusters by over an order of magnitude. Conversely, an increase in cluster temperature of around 20 K at gas temperatures of 1000 K can reduce the formation of a larger TiO2 cluster by over an order of magnitude. Conclusions. Our results confirm and quantify the prediction of previous thermal non-equilibrium studies. Small thermal non-equilibria can cause a significant change in the synthesis of larger clusters. Therefore, it is important to use kinetic nucleation models that include thermal non-equilibrium to describe the formation of clusters in environments where even small thermal non-equilibria can be present.

Ground nesting in passerine birds: evolution, biogeography and life history correlates

Nest location is one of the key components of avian reproduction and sharp transitions between different nest location strategies may have profound ecological and evolutionary consequences. Here, we used a phylogenetically‐informed comparative framework to reconstruct the evolution of ground nesting behaviour in passerine birds, quantify its biogeographical and habitat variation, and test for its associations with life history traits. Our dataset comprised over 1600 species distributed worldwide and representing ca 90% of all extant passerine families. Our analyses revealed a scattered phylogenetic distribution and moderate phylogenetic signal in the occurrence of ground nesting in passerines. We also found relatively high forward and backward transitions rates between character states of ground and non‐ground nesting, indicating strong evolutionary lability. Non‐ground nesting was identified as a likely ancestral state at the root of passerine phylogeny. Occurrence of ground nesting was clearly associated with habitat variation, as open habitats generally supported greater proportion of ground nesting species than non‐open habitats (forests). Within the major habitat categories we found greater proportion of ground nesters in boreal and temperate than subtropical and tropical zones. This reflected a general latitudinal gradient in the occurrence of ground nesting, with higher proportion of ground nesting species at higher latitudes (especially at the northern hemisphere). Ground nesting was also associated with fast life histories, as ground nesters had larger clutches, shorter incubation periods and faster chick development rates than non‐ground nesters. This variation was possibly driven by higher predation rates on nestlings and adult birds in ground nesting species. Our study lays a foundation for a comprehensive understanding of mechanisms and processes that have driven macroevolution of ground nesting behaviour in the most species‐rich extant avian lineage.

Shock-Tube Measurements of Atomic Nitrogen Collisional Excitation in 8000-12000 K Partially Ionized Nitrogen-Argon Mixtures.

We report on shock-tube experiments measuring the collisional excitation of atomic nitrogen using tunable diode laser absorption spectroscopy (TDLAS). Conditions behind the reflected shocks ranged from 8000 to 12000 K and 0.1 to 1.1 atm in mixtures of 1 or 2% molecular nitrogen (N2) in argon (Ar). Absorption from the transition between atomic nitrogen quantum states 4P to 4D at 868 nm was used to monitor the formation of electronically excited nitrogen. Population measurements of the 4P state were made at a rate of 50 kHz. In connection with these measurements, a multitemperature kinetic mechanism is proposed for nitrogen excitation. Measurements suggest a multistage process. In early test times, a period of induction due to N2 dissociation is followed by a rise via heavy particle excitation. The dominant channel causing this excitation is believed to be N + N ↔ N(4P) + N with a measured forward rate constant of 3.65 × 10-18 exp(-119892/T) [m3/s]. As test time evolves, the excitation of 4P, referred to as N*, is subsequently interrupted and then resumes, as the kinetic environment becomes increasingly electron-dominated. The most impactful reactions of the mechanism are optimized to reduce the residual between simulations and the measurements. The measured N* populations indicate strong, though indirect, sensitivity to adjacent processes, including the excitation of metastable nitrogen, and ionization channels.

CMS Spread Options Pricing under the CHH Model

Based on the Chen, Hsieh, and Huang (2017) interest rate model, this research explores the analytical approach for pricing CMS spread options. We first derive a complex joint density for two swap rates composed of sequential forward rates and approximate the joint density by bivariate normals. After applying the methods of Pearson (1995) and Li, Deng, and Zhou (2008), we obtain two analytical pricing models and examine their accuracy using numerical analysis. Finally, we empirically show the predictive power of the implied volatility of CMS options for future economic states.

Thermochemical conversion of millimeter-sized single char particle in steam dominated environments under varying temperature, reactant composition and flux—Experimental and numerical analysis

This work reports experimental and numerical investigations of biomass char conversion in H2O-dominated thermal environment. Temperature parametric analysis establishes 730 °C as the temperature beyond which char conversion rate becomes practically relevant — 0.4 mg min−1 °C−1. The mass loss rate of char particles of different sizes (8–20 mm) is studied under a wide range of temperatures (800–1000 °C), H2O concentrations (10%–100%, bal. N2/H2/CO, at varying ratios), and combinations thereof. Increasing the temperature/reactant concentration by 10% reduces the conversion time scales by up to 2 times. Temperature and reactant concentration in combination control the conversion regime (kinetic limit to diffusion limit) and can be used as control parameters. It is observed that the presence of H2 inhibits the char–steam reaction, attributed to adsorption of H2 on the char surface: 25% H2 in feed reduces the reaction rate by 50%. The CO+H2O reaction is found to play a pivotal role in controlling the char conversion by virtue of being the source of both H2 (blocking active sites) and CO2 (curtailing the forward reaction rate), and the sink for H2O (reduced reactant concentration). A novel method to identify the conversion regime based on temperature and reactant concentration is hypothesized and validated.

Analysing Quantiles in Models of Forward Term Rates

The class of forward-LIBOR market models can, under certain volatility structures, produce unrealistically high long-dated forward rates, particularly for maturities and tenors beyond the liquid market calibration instruments. This paper presents a diagnostic tool for analysing the quantiles of distributions for forward term rates in a displaced lognormal forward-LIBOR model (DLFM). In particular, we provide a quantile approximation that can be used to assess whether the modelled term rates remain within realistic bounds with a high probability. Applying this diagnostic tool (verified using Quasi-Monte Carlo (QMC) simulations), we show that realised forward term rates for long time horizons may be kept within realistic limits by appropriately damping the tail of the DLFM volatility function.

Shrinking gate fluorescence correlation spectroscopy yields equilibrium constants and separates photophysics from structural dynamics

Fluorescence correlation spectroscopy is a versatile tool for studying fast conformational changes of biomolecules especially when combined with Förster resonance energy transfer (FRET). Despite the many methods available for identifying structural dynamics in FRET experiments, the determination of the forward and backward transition rate constants and thereby also the equilibrium constant is difficult when two intensity levels are involved. Here, we combine intensity correlation analysis with fluorescence lifetime information by including only a subset of photons in the autocorrelation analysis based on their arrival time with respect to the excitation pulse (microtime). By fitting the correlation amplitude as a function of microtime gate, the transition rate constants from two fluorescence-intensity level systems and the corresponding equilibrium constants are obtained. This shrinking-gate fluorescence correlation spectroscopy (sg-FCS) approach is demonstrated using simulations and with a DNA origami-based model system in experiments on immobilized and freely diffusing molecules. We further show that sg-FCS can distinguish photophysics from dynamic intensity changes even if a dark quencher, in this case graphene, is involved. Finally, we unravel the mechanism of a FRET-based membrane charge sensor indicating the broad potential of the method. With sg-FCS, we present an algorithm that does not require prior knowledge and is therefore easily implemented when an autocorrelation analysis is carried out on time-correlated single-photon data.

EXCHANGE RATE FORECASTING: THE FUNDAMENTAL FORECASTING MODEL

This paper is using the fundamental forecasting model, which is a monetarist theory of exchange rate determination, for the current forecasting. This theory is tested empirically by using data, spot and forward rates and a variety of macro-variables from seven different countries with respect the U.S., as our domestic country. A GARCH-M model is used to forecast the volatility of the spot exchange rate. The paper is also using a Vector Auto-regression (VAR) framework to forecast simultaneously spot (s_t) and forward (f_t) exchange rates by utilizing exogenous macro-variables, time trends, and policy instruments. Further, at the end an impulse response function and a Hodrick-Prescott filter are used to present visually the behavior of the spot exchange rate. The countries used in the empirical work are, U.S. with respect the Euro-zone, Mexico, Canada, U.K., Switzerland, Japan, and Australia. The results show that these methods are giving very good forecasting for these seven exchange rates by minimizing the standard error of the regression (SER) and the root mean squared error (RMSE). Of course, uncertainty exists always in the forecasting of any economic variables, due to unanticipated public policies (monetary, fiscal, and trade) and other “innovations” in our financial markets, plus the new philosophies (i.e., liberalism, lack of ethics, perversions, DEI, AI, wars, BRICS, etc.), official measurements, and value system in our markets, societies, and way of living.

The Impact of Diversification Policy on Revenues of Commercial Banks: A Case of Iraqi Commercial Banks

The study aims to highlight the importance of the diversification policy in Arab banks in general, and Iraqi banks in particular, and its role in improving investment returns and achieving profits in light of providing a measure of protection against crises by reducing the risks that accompany banking work for the period 2010-2020 as one of the most important Serious and objective formulas to bring the banking sector to a level of stability capable of supporting other economic sectors and pushing forward growth rates and economic development. To achieve the foregoing, the study relied on the Balanced Panel Data analysis methods, which include estimating the model according to the aggregate regression methodology (PRM), the fixed effect (FEM), and the random effect (REM). The study reached a set of results, the most important of which are: the diversity of factors affecting the returns and risks of Iraqi commercial banks in terms of including the diversification policy as an independent variable and the controlling variables for the bank (bank size, income diversification, lending ratio, capital adequacy, efficiency of the bank’s activity) and their varying effects According to the indicator adopted to express the bank returns, as well as the insignificance of the diversification variable in the models. Many important recommendations were made in this study. Iraqi banks reconsider their diversification policy in light of the harmonization between profitability and safety and in a manner that enhances the benefit of the bank’s diversification advantages and in a manner that achieves satisfactory returns for them, in light of reaching a reasonable degree of risk. Also, directing Arab banks towards deepening the effective diversification policy and taking advantage of its advantages in raising their returns and reducing their risks.

Are Determinants of Government Expenditure Symmetry or Asymmetry? Fresh Evidence from Nigeria

Nigeria government has been playing the role of internalizing economic externalities, dealing with issue of unemployment and overall welfare of the populace. However, in the presence of huge and rising government expenditure, unemployment, and inflation rate still persist. This therefore called for a revisit of what determines government expenditure. There are three issues yet unresolved in the debate of what drives government expenditure. These are omitted variables bias, aggregation bias and asymmetry issue. To deal with aggregation bias, we focus on the components of government expenditure, that is, capital and recurrent. To address the issue of asymmetry, nonlinear autoregressive distributed lag was employed. Data are obtained for relevant variables spanning 1981–2021. Model of government expenditure developed by Peacock and Wiseman (1961) combined with Devarajan et al (1996) and Giavazzi, et al (2000) models are utilized. The following results are obtained. First, government capital expenditure is countercyclical while recurrent expenditure is procyclical. Second, some drivers of government expenditure, such as exchange rate and oil price, exhibit asymmetry behavior. Asymmetric tax revenue shows potential to drive capital expenditure but significantly and positively influences recurrent expenditure. Asymmetric behavior of oil revenue and exchange rate also engenders capital expenditure. However, asymmetric behavior of degree of openness and inflation rate negatively affects capital expenditure. Asymmetric behavior of tax revenue and oil revenue posted positive effect while exchange rate and degree of openness have negative effect on recurrent expenditure. Period of election is also a strong positive determinant of recurrent expenditure both in the short and long run. Following the nature of cyclicality of the component of government expenditure, the priority of government could be on capital expenditure since it will provide essential public goods required for the economy to flourish. Bearing in mind that oil revenue is volatile, it is imperative for government to rely more on tax revenue than oil revenue. Engaging in forward exchange rate might be appropriate to deal with any possible exchange rate fluctuation.

Defaultable Discrete Forward Rate Model with Covariance Structure Guaranteeing Positive Credit Spreads

Defaultable Discrete Forward Rate Model with Covariance Structure Guaranteeing Positive Credit Spreads

The optimization of continuous discount function through the continuous yield curve trajectories involving the parsimonious Nelson-siegel model

Yield curves which explain the variation in interest rates over varying maturities, provide important indicators with potentially useful implications on the investment choices, risk management strategies of financial institutions and fiscal policies of regulators. Accurately estimating the parsimonious parameters of the yield curve and modelling the discount function is highly important. The continuous forward rate function is a transformed discount function as a numerical device employed to obtain the price of a collection of bonds since the present value of a set of cash flows is computed by finding the product of these cash flows and the associated discount function. Nigeria’s bond market representing a major segment of the capital market and an important means of monetary transmission framework has suffered continuous liquidity problems. The lack of functional capital market instruments in form of government bonds has accounted for the poor performance of bond market. Consequently, this study intends to (i) Compute the discount function and (ii) Show its applications on life insurance offerings. This study analysed the term structure of interest rates using the Nigerian Eurobond which was collected for the years 2018 and 2019 from which the discount functions were constructed by adopting the continuous Nelson Siegel continuous function. A t-test conducted on the adjusted R2 on the model using Ordinary Least Square method after fixing the shape parameters was applied after computing the exponentially decaying factor. Computational evidence from the results reveals that the adjusted 𝑅square for 2018 and 2019 are 0.976and respectively0.986. This indicates that 97.6%of 2018 and 98.6% of the observed data can be explained by the Nelson-Siegel model of data using the estimated parameters for the two years and hence the result suggests a high level of accuracy confirming the degree to which the Nelson-Siegel yield curve parameters has estimated the illiquid Nigerian financial market.

An indirect approach to optimize the reaction rates of thermal NO formation for diesel engines

With stringent emission regulations, it has become more important for modern diesel engine manufacturers to accurately predict engine-out nitrogen oxide (NOx) emissions across a wide range of operating conditions. Thermal NO is the major source of engine-out NOx in modern diesel engines. For thermal NO formation, several earlier studies have recommended the forward and reverse reaction rate coefficients of the rate-limiting reaction (O + N2⇌ NO + N). However, due to deficiencies in sub-models and inadequacies of reduced chemical mechanisms to represent diesel combustion, these recommended values more often than not need to be adjusted in reduced order combustion models to accurately predict engine-out NOx. Hence, in this work a systematic and computationally efficient approach has been proposed to streamline the process of determining the optimum reaction rate coefficients. To develop the optimization approach, four different production diesel engines with different operating conditions in terms of speed, load, and exhaust-gas recirculation have been considered. Numerical simulations have been performed using a detailed zero-dimensional velocity-composition-frequency transported probability density function (0D-VCF-tPDF) model that uses hundreds of notional particles to capture in-cylinder stratification. Four different combinations of hydrocarbon and NOx chemical mechanisms were used to represent chemistry. It was found that for the rate-limiting reaction, the pre-exponent factors (Af1,Ar1) and activation energies (EA,f1,EA,r1) of the forward and reverse reaction rates follow a linear band in Af1−EA,f1 and Ar1−EA,r1 space where predicted engine-out NOx match the measured values closely. By encompassing such bands from different engines and considering constraints on activation energies, a reduced search domain of pre-exponent factors and activation energies was constructed that is expected to be applicable to any diesel engine. Eventually, computationally efficient three-line and one-line search approaches were proposed to determine the optimum values of the pre-exponent factors and activation energies that led to a minimum error between measured and predicted engine-out NOx. Finally, these three-line and one-line NOx optimization approaches were applied to a fifth production diesel engine for which the 0D-VCF-tPDF model showed a very good predictive performance in terms of predicting peak pressure, 50% burn rate, and engine-out NOx when compared to measured and 3D-CFD values.

Asymmetric short-rate model without lower bound

We propose a new short-rate process which appropriately captures the salient features of the negative interest rate environment. The model combines the advantages of the Vasicek and Cox–Ingersoll–Ross (CIR) dynamics: it is flexible, tractable and displays positive skewness without imposing a strict lower bound. In addition, a novel calibration procedure is introduced which focuses on minimizing the Jensen–Shannon (JS) divergence between the model- and market-implied forward rate densities rather than focusing on the minimization of price or volatility discrepancies. A thorough empirical analysis based on cap market quotes shows that our model displays superior performance compared to the Vasicek and CIR models regardless of the calibration method. Our proposed calibration procedure based on the JS divergence better captures the entire forward rate distribution compared to competing approaches while maintaining a good fit in terms of pricing and implied volatility errors.

Influence of effusion cooling air on the CO production in the primary zone of a pressurized single sector model gas turbine combustor

In this study, the influence of effusion cooling air on the CO production in the primary zone of a pressurized single sector model gas turbine combustor is investigated in a parametric study using a combination of laser-based diagnostics. Three species (OH, CO, CH2O) are probed using laser-induced fluorescence (LIF). In principle, this combination of probed species allows to derive the forward reaction rate of CO oxidation and the local heat release rate from the LIF signals. Based on simulations and measurements in a laminar flame, we show that the limited optical resolution of the intensified cameras severely limits the applicability of the method for pressurized flames. However, by employing a conditioning strategy, mainly using CH2O-LIF as a marker for low temperature chemistry, it was shown that effusion cooling air affects the structure of the premixed flame at large distances from the effusion cooled liner. At higher blowing ratios, samples measured in the primary zone during the CO production phase exhibit a higher CO concentration at a given level of OH concentration. Most likely, this is caused by the strong non-linear sensitivity of OH concentration to temperature, shifting the local equilibrium towards higher CO concentrations, when fractions of the effusion cooling air are recirculated towards the inlet nozzle. In the exhaust phase, dilution effects seem to dominate, as a higher effusion cooling air mass flow systematically lowers both measured OH and CO signals.

TGRV: A trust-based geographic routing protocol for VANETs

Vehicular ad-hoc networks (VANETs) consist of highly mobile and self-organized nodes that wirelessly communicate with one another and transmit a variety of information, some of which may be critical information. Due to the rapidly changing topology of VANETs and the high-speed mobility of the participating vehicles, the routing of packets in these networks is a challenging task. Moreover, the presence of malicious vehicles in VANETs makes the correct routing of packets more challenging. In this paper, we propose a trust-based geographic routing protocol for VANETs (TGRV) that limits the participation of malicious vehicles in routing. In TGRV, to select the next-hop, a sender not only considers the distance, speed, and direction of its neighbors but also evaluates their direct trust and recommendation trust. For this purpose, TGRV uses a monitoring system that allows each vehicle to monitor the correct packet forwarding rate of its next-hop. In this way, the vehicle updates its direct trust to the next-hop and retransmits the packets if the packets are lost. The vehicle also sends its observations of the next-hop to its neighbors with a push-based notification, and based on that, the neighbors can update their recommendation trust about the next-hop. The monitoring system applies distance prediction in a modified promiscuous mode to better estimate the correct packet forwarding rate of the next-hop. To enhance the accuracy of trust management, the trust values of interactions are reduced over time by using a decay factor. TGRV uses the number and trust of two-hop neighbors, which helps in selecting the next-hop that is in a more trusted zone. Our extensive simulations on OMNeT++ show that when the percentage of malicious vehicles in an urban scenario increases from 0 to 25%, the packet delivery ratio of TGRV decreases from 95.1 to 88.7%, which performs very well compared to the GPSR and PGRP protocols. Also, the end-to-end delay of TGRV increases from 3.79 to 7.07 s and the average hop count of TGRV increases from 6.7 to 9.9, which are significant increases compared to the other two protocols. These increases are acceptable because, in the other two protocols, there is no monitoring and retransmission, and the probability of packet delivery failure on longer routes is higher. The cost and security analysis also show that the memory, communication, and computational overheads of TGRV are acceptable, and TGRV is resistant and resilient to some important trust-based attacks.

Simultaneous Inference on the Korean Won-US Dollar Forward Premium Anomaly

The forward premium anomaly, which refers to the empirical failure of the uncovered interest parity (UIP), has been primarily examined by the forward premium regression of [Fama, E. (1984). Forward and spot exchange rates. Journal of Monetary Economics, 14(3), 319–338. https://doi.org/10.1016/0304-3932(84)90046-1]. Some studies apply the rolling-window regression to capture the time-varying coefficient on the forward premium, with difficulty in statistically testing the deviation of the coefficient from the UIP over time. We follow [Baillie, R., & Kim, K. (2015). Was it risk? Or was it fundamentals? Explaining excess currency returns with kernel smoothed regressions. Journal of Empirical Finance, 34, 99–111] to apply the simultaneous inference procedure to the Korean Won-US Dollar spot and forward exchange rates by estimating the time-varying coefficient from the kernel-smoothed local-linear regression and constructing the uniform confidence band to test the local deviation. We find that, while the UIP is not rejected from the baseline regression, the simultaneous inference shows that the deviation from the UIP is mainly observed during the early 2000s and 2010s. Time-variation of the forward premium coefficient tends to be significantly affected by economic uncertainties such as the interest rate, inflation, and stock return volatilities in Korea and US.