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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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3527041,0561,408 · Jun 202019922001200920172026
48 results for time-dependent models

Flexible Cox model for time-dependent covariates with complex sparsity patterns.

problem Lack of flexibility in enforcing specific sparsity patterns in time-dependent Cox models.
method Proposes a flexible framework for variable selection in time-dependent Cox models, accommodating complex selection rules.
result Achieves accurate estimation with low false alarm rates for complex covariate structures.

SurvSHAP(t) explains time-dependent survival predictions from machine learning models.

problem Interpreting complex survival models for time-dependent effects.
method SHapley Additive exPlanations (SHAP) adapted for time-dependent survival predictions.
result SurvSHAP(t) detects time-dependent effects and improves variable importance detection.

This work presents an exact solution to the generalized Heston model, where the model parameters are assumed to have linear time dependence The solution for the model in expressed in terms of confluent hypergeometric functions.

2014-02-23abs ↗pdf ↗

A new RNN model tackles long-time dependencies with fast, invertible, and memory-efficient hidden states.

problem Challenges in processing sequential inputs with long-time dependencies in RNNs.
method A novel RNN architecture based on a Hamiltonian system of oscillators.
result The proposed RNN mitigates exploding and vanishing gradient problems, providing state-of-the-art performance.

Develops semi-closed form solutions for barrier and American options on time-dependent OU process.

problem Valuation of barrier and American options on a time-dependent Ornstein-Uhlenbeck process.
method Semi-closed form solutions involving numerical solution of Fredholm equations and integration of Jacobi theta functions.
result Method is more efficient than backward finite difference method and can be as efficient as forward finite difference solver with better accuracy and stability.

Paper develops semi-analytic method for American options in time-dependent jump-diffusion models.

problem Pricing American options in models with time-dependent and exponential jumps.
method Generalizes existing methods for barrier and American options to handle arbitrary time dependencies and solves the problem through algebraic and Fredholm-Volterra equations.
result Presents a semi-analytic solution for American options in time-dependent jump-diffusion models with exponential jumps.

Proposes a method to estimate time-dependent probability density functions using binary classifiers.

problem Estimating time-dependent probability density functions of stochastic processes.
method Trains a time-dependent binary classifier to discriminate between realizations of a stochastic process at two nearby time instants.
result Explicitly models and accurately reconstructs complex time-dependent, multi-modal, and near-degenerate densities.

Develops methods to learn correlation potentials for time-dependent Kohn-Sham systems.

problem Learning the correlation potential for time-dependent Kohn-Sham systems.
method Optimizing a least-squares objective subject to the TDKS equation using adjoints.
result Learned correlation potential models match ground truth electron densities and can have memory.

ParaRNN improves RNN interpretability and parallelizability for time-dependent data.

problem Limited interpretability and slow training of RNNs.
method Parallelized RNN with additive representation and recurrence features.
result ParaRNN achieves comparable performance to vanilla RNNs but with improved interpretability and efficiency.

Modeling regime shifts in co-evolving time series with interactions and time-dependency.

problem Discovering and modeling regime shifts in multiple time series with relationships and time-dependent behaviors.
method Modeling interactions and time-dependency in co-evolving time series using a mapping grid and dynamic network representation for regime identification and time-dependent Cox regression for regime transition probabilities.
result A principled approach for modeling interactions and time-dependency in co-evolving time series.

New method for pricing American options in time-dependent models, improving accuracy and efficiency.

problem Pricing American options in time-dependent models with improved accuracy and efficiency.
method Semi-analytical pricing using a nonlinear Volterra integral equation and numerical methods.
result Improved accuracy and efficiency in pricing American options compared to forward finite difference solvers.

We present three models of stock price with time-dependent interest rate, dividend yield, and volatility, respectively, that allow for explicit forms of the optimal exercise boundary of the finite maturity American put option. The optimal exercise boundary satisfies the nonlinear integral equation of Volterra type. We …

2019-12-11abs ↗pdf ↗

DynForest R package predicts outcomes with time-dependent predictors.

problem Handling time-dependent predictors in random forest models.
method Random forests with time-dependent predictors summarized using flexible linear mixed models.
result DynForest can predict continuous, categorical, and survival outcomes.

Study on relativistic nonholonomic mechanics with time-dependent constraints.

problem Formulating classical time-dependent nonholonomic mechanics.
method Invariant formulation using moving frames and Chaplygin systems.
result Hamiltonization of time-dependent constraints achieved.

The aim of this paper is to geometrize time dependent Lagrangian mechanics in a way that the framework of second order tangent bundles plays an essential role. To this end, we first introduce the concepts of time dependent connections and time dependent semisprays on a manifold MM and their induced vector bundle struc…

2016-07-08abs ↗pdf ↗

Deep learning estimates time-varying Markov model parameters.

problem Estimating time-dependent parameters in Markov models.
method Reframes parameter estimation as an optimization problem using maximum likelihood.
result Real solution close to SDE with neural network-derived parameters under specific conditions.

Efficient semi-analytic methods for pricing double barrier options with time-dependent parameters.

problem Pricing and calibration of double barrier options with time-dependent parameters.
method Two approaches: General Integral transform method and Heat Potential method.
result Semi-analytic techniques are more efficient for pricing double barrier options than traditional numerical methods.

In this article we get a time-dependent Sobolev inequality along the Ricci flow which generalizes the earlier results of Zhang, Ye, Hsu. As an application of the time-dependent Sobolev inequality, we also get a growth of the ratio of bob-collapsing along the Ricci flow.

2008-12-10abs ↗pdf ↗

Paper adapts causal analysis for time-dependent systems, especially energy management.

problem Challenges in root-cause analysis for systems with lagged time-dependencies, particularly in energy management.
method Adapts causal root-cause analysis method to time-dependent systems, discusses two truncation approaches.
result Extension effectively localizes root-causes in feature and time domain with enough lags.

A new framework predicts links in time-dependent networks using Bernoulli autoregression.

problem Predicting links in time-dependent networks with additional auxiliary information.
method A Bernoulli autoregressive model with regularization for link discovery.
result The model can discover new links not present in the data.

The paper extends Marsden-Weinstein reduction to mechanical presymplectic structures for time-dependent Hamiltonian systems.

problem Limitations of Marsden-Weinstein reduction for cosymplectic structures in time-dependent Hamiltonian systems.
method Developed Marsden-Weinstein reduction for mechanical presymplectic structures.
result Mechanical presymplectic structures provide a more suitable framework for time-dependent Hamiltonian systems than cosymplectic structures.

CENNSurv models cumulative effects of time-dependent exposures on survival outcomes.

problem Challenges in modeling cumulative effects of time-dependent exposures on survival outcomes.
method CENNSurv, a novel deep learning approach that captures dynamic risk relationships from time-dependent data.
result CENNSurv reveals multi-year lagged and short-term behavioral shifts in survival outcomes.

In the limit of infinite number of nodes (agents), the Itô-reduced Bouchaud-Mézard network model of economic exchange has a time-independent mean and a steady-state inverse gamma distribution. We show that for a finite number of nodes the mean is actually distributed as a time-dependent lognormal and inverse gamma is q…

2017-04-07abs ↗pdf ↗

We propose the time-dependent generalization of an `ordinary' autonomous human biomechanics, in which total mechanical + biochemical energy is not conserved. We introduce a general framework for time-dependent biomechanics in terms of jet manifolds derived from the extended musculo-skeletal configuration manifold. The …

2009-07-07abs ↗pdf ↗

Proposes a neural network for dynamic risk prediction of AMD using longitudinal fundus images.

problem Dynamic risk prediction for progressive eye disorders like AMD.
method tdCoxSNN, a time-dependent Cox survival neural network integrating CNN.
result Demonstrates commendable predictive performance in AMD and PBC datasets.

The paper justifies time-dependent loss reweighting schemes for flow matching and diffusion models.

problem Theoretical justification for time-dependent loss reweighting schemes in flow matching and diffusion models.
method Clarifies that the loss can depend on both time and state, and shows theoretical justification for time-dependent loss weighting schemes.
result Time-dependent loss weighting schemes are theoretically justified for Generator Matching and Edit Flows.

Paper shows how scattering maps of Schrödinger equations relate to metrics.

problem Relating scattering maps of time-dependent Schrödinger equations to metrics.
method Analyzes scattering maps for specific classes of metrics and diffeomorphisms.
result Scattering maps differ by a compact operator if and only if metrics are related by diffeomorphism.

The usual formulation of time-dependent mechanics implies a given splitting Y=R×MY=R\times M of an event space YY. This splitting, however, is broken by any time-dependent transformation, including transformations between inertial frames. The goal is the frame-covariant formulation of time-dependent mechanics on a bundle…

1997-10-04abs ↗pdf ↗

We discuss a simple extension of the Ho and Lee model with generic time-dependent drift in which: 1) we compute bond prices analytically; 2) the yield curve is sensible and the asymptotic yield is positive; and 3) our analytical solution provides a clean and simple way of separating volatility from the drift in the sho…

2015-02-21abs ↗pdf ↗

In this paper we propose the time-dependent generalization of an `ordinary' autonomous human biomechanics, in which total mechanical + biochemical energy is not conserved. We introduce a general framework for time-dependent biomechanics in terms of jet manifolds associated to the extended musculo-skeletal configuration…

2009-07-12abs ↗pdf ↗

Develops a new method for pricing barrier options in time-dependent Heston model.

problem Pricing barrier options in a time-dependent Heston model with stochastic volatility.
method General Integral Transforms (GIT) method for a two-dimensional integral representation.
result Shows that the GIT method can be extended to two drivers with inhomogeneous correlation.

The usual formulations of time-dependent mechanics start from a given splitting Y=R×MY=R\times M of the coordinate bundle YRY\to R. From physical viewpoint, this splitting means that a reference frame has been chosen. Obviously, such a splitting is broken under reference frame transformations and time-dependent canonical …

1997-02-25abs ↗pdf ↗

Path integral method calculates PDBS option prices with time-dependent parameters.

problem Pricing proportional double-barrier step options with time-dependent interest rates and volatilities.
method Path integral method applied to a quantum mechanical analogy of barrier options.
result Derivation of pricing kernel for PDBS options with time-dependent parameters.

The paper analyzes time-dependent streaming data with biased gradient estimates and proposes improved stochastic optimization methods.

problem Stochastic optimization in a streaming setting with time-dependent and biased gradient estimates.
method Analysis of several first-order methods including SGD, mini-batch SGD, and time-varying mini-batch SGD, along with their Polyak-Ruppert averages.
result Time-varying mini-batch SGD methods can break long- and short-range dependence structures, and biased SGD methods can achieve comparable performance to their unbiased counterparts.

Based on our previous study [IS3] on the stationary scattering theory for the Schrodinger operator on a manifold possessing an escape function we complete our investigation by doing the time-dependent counterpart. A particular class of examples are manifolds with Euclidean and/or hyperbolic ends, possibly with unbounde…

2019-05-08abs ↗pdf ↗