Study shows Nelson-Siegel curves fit well with Ho-Lee and Hull-White models.
problem Fitting observed interest rate term structures with interest rate models.
method Examined Nelson-Siegel curves in the context of Ho-Lee and Hull-White models.
result Extended Nelson-Siegel curves emerge from the forward curve process of the models.
Bayesian approach improves Nelson-Siegel yield curve modeling.
problem Yield curve modeling in finance.
method Hierarchical Bayesian model with MAP estimates via BFGS algorithm and HMC.
result Strong negative correlation between bond price and long-term yield effect, weak positive correlation between short-term rate effect and bond value.
Genetic Algorithm improves Nelson-Siegel-Svensson model calibration for interest rates.
problem Calibrating the Nelson-Siegel-Svensson model is difficult due to nonlinearity and parameter co-dependence.
method Applied Genetic Algorithm to optimize model parameters.
result Constructs stable interest rate curves and model parameters over time.
A new model explains relative spreads between economies using dynamic Nelson-Siegel and functional regression.
problem Analyzing and predicting relative spreads between economies in fixed income markets.
method State-space functional regression model incorporating dynamic Nelson-Siegel model and kernel PCA.
result The new model outperforms the dynamic Nelson-Siegel model in explaining relative spreads.
This study models Burundi's bond market yield curve using Nelson-Siegel and Svensson models.
problem Modeling the yield curve of Burundian bond market for financial analytics.
method Collected treasury securities auction reports, computed zero-coupon rates, and applied Nelson-Siegel and Svensson models.
result Nelson-Siegel model is optimal for Burundian yield curve modeling.
Investment strategies derived from commodity futures curves exploit dynamics in price movements.
problem Modeling and predicting the term structure of commodity futures prices.
method Employed the Nelson-Siegel framework to model term structure, and developed investment strategies based on changes in slope and curvature parameters.
result Significant profits generated from systematic strategies based on the change in slope, unrelated to risk factors and robust to transaction costs.
A robust machine learning approach forecasts U.S. Treasury yields, reducing risk for investors.
problem Noisy and uncertain U.S. Treasury yields pose risk to forecast users.
method Formulates yield curve forecasting as a distributionally robust problem, combining factor models and machine learning.
result Robust forecast combinations improve out-of-sample performance across different maturity periods.
Neural network model improves robustness of mortgage bond yield curve estimation.
problem Overfitting and instability in traditional yield curve estimation methods for small mortgage bond markets.
method Neural network framework with a new loss function for smoothness and stability.
result Empirical results show more robust and stable yield curve estimates compared to existing methods.
We orthogonalize the NSS model to condition and diagnose its ill-conditioned parameters.
problem The ill-conditioning of the NSS model's design matrix.
method Exact orthogonal reparametrization via QR decomposition.
result Orthogonalization isolates the conditioning structure and maintains fit uncertainty.
We derive an equation of motion for interest-rate yield curves by applying a minimum Fisher information variational approach to the implied probability density. By construction, solutions to the equation of motion recover observed bond prices. More significantly, the form of the resulting equation explains the success …
Classifies shapes of yield curves in the Svensson family.
problem Classifying shapes of yield curves in the Svensson family.
method Complete classification of shapes using mathematical analysis.
result Certain complex shapes cannot appear after a deterministic time horizon.
Study forecasts commodity options' implied volatility using Nelson-Siegel factors.
problem Predicting implied volatility in commodity markets.
method Rolling out-of-sample forecasting with Nelson-Siegel factors.
result Nelson-Siegel factors improve forecasting accuracy for energy and precious metals options.
Metaheuristics improve yield curve estimation for Costa Rica.
problem Estimating the yield curve for Costa Rica using historical data.
method Used Nelson-Siegel and Svensson models with four metaheuristics (Ant colony, Genetic, Particle Swarm, Simulated Annealing) for optimization.
result Metaheuristics achieved better results than classical methods, especially Particle Swarm and Simulated Annealing.
Deep learning framework for bond and yield curve forecasting with no-arbitrage constraints.
problem Arbitrage-free yield curve and bond price forecasting.
method Combines Kalman, extended Kalman, and particle filters with LSTM/CLSTM, and introduces AER term.
result Arbitrage regularization improves forecast accuracy, especially at short maturities.
In this work we introduce Heath-Jarrow-Morton (HJM) interest rate models driven by fractional Brownian motions. By using support arguments we prove that the resulting model is arbitrage free under proportional transaction costs in the same spirit of Guasoni [Math. Finance 16 (2006) 569-582]. In particular, we obtain a …
Study on liquidity dynamics in Uniswap v3 pools using statistical methods.
problem Characterize liquidity in Uniswap v3 pools.
method Functional principal component analysis (FPCA) and dynamic factor methods.
result Liquidity dynamics in Uniswap v3 pools are well-captured by a low-order Legendre polynomial basis.
Machine learning models outperform traditional econometric methods for forecasting term structure of government bonds
problem Forecasting the term structure of government bonds
method Combining traditional econometric models with neural network architectures
result Neural network models consistently outperform traditional models in both forecasting accuracy and portfolio performance
The paper contributes to the rare literature modeling term structure of crude oil markets. We explain term structure of crude oil prices using dynamic Nelson-Siegel model, and propose to forecast them with the generalized regression framework based on neural networks. The newly proposed framework is empirically tested …
The study constructs models for SOFR term rates using futures data.
problem Disruption of the LIBOR market and lack of liquid SOFR derivatives.
method Dynamic arbitrage-free models using historical SOFR futures prices.
result Shadow-rate extension needed for zero-boundary term rates.
Paper uses RL for dynamic swaption hedging, outperforming traditional methods.
problem Dynamic hedging of swaptions using reinforcement learning.
method Design agents with three objective functions to adapt hedging strategies dynamically.
result Deep hedging strategies using two swaps outperform traditional methods, even with model misspecification.
Bayesian model predicts interest rates with short-term accuracy and long-term stability.
problem Improving short- and long-term prediction of time series with temporary non-stationary behavior.
method Time-varying autoregressive model with Bayesian regularization and MCMC inference.
result Model outperforms existing methods in both short and long-term predictions.
The study explores Bertrand and Mannheim curves in 4D Euclidean space for framed curves.
problem Exploring Bertrand and Mannheim curves in 4D Euclidean space for framed curves.
method Defining and investigating Bertrand and Mannheim curves of framed curves in 4D Euclidean space.
result Bertrand and Mannheim curves exist even for framed curves in 4D Euclidean space, contrary to regular curves.
The study examines Bertrand Legendre curves in the unit tangent bundle over Euclidean plane.
problem Investigating properties of Legendre curves and their associated curves.
method Analyzing Bertrand Legendre curves and their associated curves, including parallel, evolute, and involute curves.
result Existence conditions and inverse operation for Bertrand Legendre curves are provided.
Method for generating new curves from plane curves on cylinders.
problem Generating new space curves from given plane curves.
method Defining a non-planar space curve on a right generalized cylinder and examining its focal curve.
result Parametric representation of the focal curve of a cylindrical curve.
In this study, we introduce a new approach to curve pairs by using integral curves. We consider the direction curve and donor curve to study curve couples such as involute-evolute curves, Mannheim partner curves and Bertrand partner curves. We obtain new methods to construct partner curves of a unit speed curve and giv…
The paper characterizes curves in pseudo-Galilean 4-space.
problem Characterizing curves in the pseudo-Galilean 4-space G14. method Investigation and characterisation of admissible curves in terms of curvature functions.
result Necessary and sufficient conditions for admissible rectifying curves in G14. In this paper, we introduce a new approach to non-lightlike curve pairs by using integral curves in Minkowski 3-space. We consider direction curve and donor curve to study non-lightlike curve couples such as involute-evolute curves, Mannheim partner curves and Bertrand partner curves. We obtain new methods to construct…
The paper explores Bertrand and framed curves in 3D space.
problem Characterizing Bertrand and framed curves in Euclidean 3-space.
method Analyzing curves where tangent, normal, or binormal lines match another curve's lines.
result Conditions for the existence of Bertrand and framed curves are clarified.
The paper examines how closed curves on surfaces intersect and how this intersection determines the curves.
problem Determining closed curves on surfaces based on their intersections.
method Constructing and studying k-equivalent curves, analyzing intersections with other curves. result Curves are determined by their intersections with all other curves, but non-simple curves require infinitely many intersections to distinguish.
Approximating complex curves with simple parametric curves is widely used in CAGD, CG, and CNC. This paper presents an algorithm to compute a certified approximation to a given parametric space curve with cubic B-spline curves. By certified, we mean that the approximation can approximate the given curve to any given pr…
The study classifies singularities of spherical orthotomic curves.
problem Classifying singularities of spherical orthotomic curves.
method Defining spherical orthotomic curves and classifying their singularities.
result Singularities of spherical orthotomic curves are classified.
Flow deforms locally convex curves to curves of constant k-order width.
problem Evolve locally convex curves to curves of constant k-order width.
method Introduced a nonlocal curvature flow to evolve locally convex curves in the plane.
result The flow converges to a smooth, locally convex curve of constant k-order width as time goes to infinity.
Modified curve shortening flow constructs λ-Angenent curve.
problem Constructing λ-Angenent curve. method Modified curve shortening flow
result Constructs λ-Angenent curve. Study on CR curves in 3-sphere, focusing on critical curves integration and existence.
problem Addressing the integration and existence of critical curves in the CR 3-sphere.
method Provided a procedure for the explicit integration of general critical curves and characterized closed curves.
result Existence of infinite countably many closed critical curves.
Study rectifying curves in 3D multiplicative Euclidean space.
problem Investigate rectifying curves in a non-Newtonian geometry setting.
method Apply multiplicative differential-geometric concepts to rectifying curves.
result Classify multiplicative rectifying curves using spherical curves.
In classical curve theory, the geometry of a curve in three dimensions is essentially characterized by their invariants, curvature and torsion. When they are given, the problem of finding a corresponding curve is known as 'solving natural equations'. Explicit solutions are known only for a handful of curve classes, inc…
The paper characterizes pedal curves of quadratic curves.
problem Understanding pedal curves of quadratic curves.
method Analyzing the inverse construction of pedal curves.
result Characterization of pedal curves of quadratic curves.
Unified description of aesthetic curves through self-affinities.
problem Characterizing log-aesthetic curves and their properties.
method Reformulating and proving self-affinities of planar curves, integrating equiaffine geometry.
result Unified characterization of constant curvature curves in similarity and equiaffine geometries.
Primitive curves in handlebodies form a connected complex.
problem Understanding the structure of curves in handlebodies.
method Defining and analyzing primitive curves and constructing sequences between them.
result The primitive curve complex for a handlebody is connected.
Study on Bertrand lightcone framed curves in Lorentz-Minkowski 3-space.
problem Analyzing mixed types of curves with singular points in Lorentz-Minkowski 3-space.
method Using lightcone frame to consider Bertrand types for lightcone framed curves.
result Existence conditions of Bertrand lightcone framed curves in all cases.
Study isotopy of rational cuspidal curves in 4-manifolds.
problem Isotopy of rational cuspidal curves in 4-manifolds.
method Tame symplectic curves, pseudo-holomorphic curves, log pairs, 4-dimensional topology.
result Every rational cuspidal curve is isotopic to a complex curve in degrees up to 5.
Defines new curves from tangent indicatrix of curves, linking them to helices and slant helices.
problem Understanding and constructing helices and slant helices from spherical curves.
method Defining integral curves of Frenet vectors and using their curvatures.
result Established relationships and methods to create helices and slant helices from specific spherical curves.
In this study, we introduce a new type of surface curves called D-type curve. This curve is defined by the property that the unit Darboux vector W0 of a space curve r(s) and unit surface normal n along the curve r(s) satisfy the condition <n,W0>=constant. We point out that a D-type curve is a geodesic curve or an asymp…
Study on triharmonic curves in f-Kenmotsu manifolds.
problem Characterizing triharmonic curves in f-Kenmotsu manifolds.
method Investigation of necessary and sufficient conditions for Frenet curves, slant, and Legendre curves to be triharmonic. Proof of specific properties of triharmonic Frenet curves.
result Triharmonic Frenet curves with constant curvature are Frenet helices in three dimensional f-Kenmotsu manifolds.
The paper generalizes rectifying and normal curves in Lorentzian n-space.
problem Characterizing and classifying g−rectifying and g−normal curves in Lorentzian n-space. method Introducing a g−position vector field and defining g−rectifying and g−normal curves based on this field. result Comprehensive characterization and classification of g−rectifying and g−normal curves. New findings on hyperbolicity of fine curve graphs and their subgraphs.
problem Investigating hyperbolicity of fine curve graphs and their subgraphs.
method Analyzing large subgraphs of fine curve graphs and computing distances in specific cases.
result Large subgraphs of fine curve graphs contain flats of every finite dimension, indicating they are not hyperbolic.
In this paper we study null Bertrand curves in R14 under the assumption the curve has a Cartan frame. We show that if the derivative vectors of the null Cartan curve in R14 is linearly independent, then this curve is not a Bertrand curve. Since then the already known notion of null Bertrand curves in $R…
Study of p-biharmonic curves and their properties.
problem Generalizing biharmonic curves to p-biharmonic curves. method Classification and analysis of p-biharmonic curves on surfaces and space forms. result Existence and stability of p-biharmonic curves on closed surfaces.