On-device research index

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.

169,341 papers · 148 categories

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48 results for “switching problem”

Optimal Switching under Ambiguity and Its Applications in Financeq-fin.MF

Study optimal switching under ambiguity in finance.

problem Optimal switching problems under ambiguity in finance.

method Use multidimensional reflected backward stochastic differential equations (RBSDEs) to characterize the optimal switching.

result Value function of optimal switching under ambiguity coincides with solutions to multidimensional RBSDEs with negative switching costs.

Optimal switching Ambiguity Finance Backward stochastic differential equations Value function

2016-08-22abs ↗pdf ↗

A Problem of Finite-Horizon Optimal Switching and Stochastic Control for Utility Maximizationmath.OC

Paper tackles utility maximization with job-switching and retirement constraints.

problem Maximizing utility with job-switching and retirement constraints.

method Dual-martingale approach and double obstacle problem theory.

result Characterization of optimal job-switching strategy and wealth boundaries.

utility maximization job-switching retirement constraints dual-martingale double obstacle problem

2023-09-22abs ↗pdf ↗

Feedback Solution to Optimal Switching Problems with Switching Costeess.SY

The problem of optimal switching between nonlinear autonomous subsystems is investigated in this study where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to util…

2014-11-17abs ↗pdf ↗

Phase Transitions in Bandits with Switching Constraintscs.LG

Study on bandit problems with switching constraints, revealing phase transitions in regret.

problem Stochastic multi-armed bandit problem with switching cost constraints.

method Proved matching upper and lower bounds on optimal regret, provided efficient algorithms.

result Phase transitions in optimal regret rate with respect to switching budget.

bandit problems switching constraints regret phase transitions stochastic

2019-05-26abs ↗pdf ↗

A Direct Solution Method for Pricing Options in Regime-switching Modelsq-fin.MF

Direct method solves complex option pricing in changing market conditions.

problem Pricing financial options with changing market conditions.

method Reduces complex optimal stopping problems to simpler ones, finding explicit value functions.

result Simpler and more direct solution for option pricing in regime-switching models.

option pricing regime-switching models optimal stopping value functions

2017-11-24abs ↗pdf ↗

Multinomial Logit Bandit with Low Switching Costcs.LG

New algorithm reduces switching costs in multinomial logit bandit problems.

problem Minimizing switching costs in multinomial logit bandit problems.

method Proposed AT-DUCB and FH-DUCB algorithms with low assortment switching costs.

result AT-DUCB and FH-DUCB algorithms achieve almost optimal minimax regret with low switching costs.

multinomial logit bandit switching cost minimax regret assortment switching

2020-07-09abs ↗pdf ↗

Discrete-time risk-aware optimal switching with non-adapted costsmath.OC

Solves risk-aware optimal switching problems in discrete time.

problem Non-Markovian optimal switching problems with risk awareness and general filtration.

method Solves reflected backward stochastic difference equations.

result Existence and uniqueness of solutions for the problems.

optimal switching discrete time risk-aware reflected BSDE hydropower planning

2019-10-09abs ↗pdf ↗

Blind Network Revenue Management and Bandits with Knapsacks under Limited Switchescs.LG

Study on revenue management with limited switches, achieving strong performance and reduced switch counts.

problem Resource-constrained dynamic pricing with limited switching constraints.

method Developed algorithms for blind network revenue management and bandits with knapsacks, achieving optimal regret rates.

result Optimal regret rates are fully characterized by a piecewise-constant function of the switching budget and resource constraints.

revenue management dynamic pricing limited switches regret minimization online learning

2019-11-04abs ↗pdf ↗

Optimal control of multiple Markov switching stochastic system with application to portfolio decisionmath.OC

Optimizes control of hybrid systems with multiple switching processes.

problem Optimal control of hybrid systems with multiple Markov switching processes.

method Combines two separate Markov chains into one synthetic chain, derives HJB equations, and solves the portfolio choice problem.

result Derives explicit solutions and value functions for the optimal control problem.

optimal control hybrid systems Markov switching portfolio choice financial markets

2020-10-30abs ↗pdf ↗

A Survey of Code-switched Speech and Language Processingcs.CL

Survey reviews code-switched speech and language processing.

problem Processing code-switched text and speech for multilingual communities.

method Reviews computational approaches and lists available resources.

result Essential for building intelligent agents that interact in multilingual settings.

code-switching speech language processing multilingual natural language

2019-03-25abs ↗pdf ↗

Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneouslycs.LG

Optimal switching regret for all segmentations in online convex optimisation.

problem Non-stationary online convex optimisation problems.

method Developed an efficient algorithm to achieve optimal switching regret on every possible segmentation.

result Achieved asymptotically optimal switching regret on every possible segmentation simultaneously.

online convex optimisation switching regret non-stationary optimal algorithm dynamic regret

2024-05-31abs ↗pdf ↗

Squirrel: A Switching Hyperparameter Optimizercs.LG

Squirrel switches between optimizers for better performance.

problem Finding the best optimizer for a given problem.

method Switches between different optimizers based on performance.

result Improves performance on various problems.

hyperparameter optimization optimizer switching NeurIPS challenge

2020-12-15abs ↗pdf ↗

To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learningstat.ML

Study tackles balancing policy switching costs in offline RL.

problem Balancing the cost of policy switching in offline RL.

method Optimal transport ideas and Net Actor-Critic algorithm.

result Demonstrated efficiency on multiple RL benchmarks.

Reinforcement Learning Policy Switching Offline RL Optimal Transport Net Actor-Critic

2024-07-01abs ↗pdf ↗

Trading VIX Futures under Mean Reversion with Regime Switchingq-fin.CP

This paper optimizes trading VIX futures using a regime-switching model.

problem Optimizing VIX futures trading under mean reversion and regime switching.

method Regime-switching model, coupled system of variational inequalities, PSOR method with Crank-Nicolson scheme.

result Illustrates optimal boundaries for VIX futures trading strategies.

VIX futures mean reversion regime switching optimal trading variational inequalities

2016-05-25abs ↗pdf ↗

Understand Dynamic Regret with Switching Cost for Online Decision Makingcs.LG

The paper explores dynamic regret with switching cost in online decision making.

problem The relation between dynamic regret and switching cost in online decision making.

method Investigates two classic online settings: Online Algorithms (OA) and Online Convex Optimization (OCO). Provides a new theoretical analysis framework.

result The switching cost impacts dynamic regret differently in OA and has no impact in OCO.

dynamic regret switching cost online decision making online algorithms online convex optimization

2019-11-28abs ↗pdf ↗

On the complexity of switching linear regressionstat.ML

Technical note on switching linear regression complexity.

problem Minimizing error in switching linear regression models.

method Extended recent results on computational complexity.

result Problem is NP-hard but admits a polynomial-time algorithm.

switching linear regression computational complexity NP-hard piecewise-affine models

2015-10-23abs ↗pdf ↗

Managing Cellular Billing Plan Switchingsq-fin.GN

The paper tackles billing plan switching costs for consumers.

problem Optimizing costs for switching billing plans.

method Formal characterization, polynomial approximation.

result Polynomial approximation of target index value.

billing plans cost optimization switching costs polynomial approximation traffic volume

2015-09-19abs ↗pdf ↗

Sample-Efficient Reinforcement Learning with loglog(T) Switching Costcs.LG

New RL algorithm reduces policy switching cost to loglog(T) with similar regret.

problem Low policy switching cost in real-life RL applications.

method Stage-wise exploration and adaptive policy elimination.

result Regret of

O(HSA \log\log T)

with

O(HSA \log\log T)

switching cost.

reinforcement learning policy switching regret stage-wise exploration adaptive elimination

2022-02-13abs ↗pdf ↗

On the bail-out dividend problem for spectrally negative Markov additive modelsq-fin.MF

Optimal dividend strategy found for risk models with regime switching.

problem Optimal dividend strategy for spectrally negative Markov additive models with regime switching.

method Introduced an auxiliary problem and transformed the original problem into a local optimization problem.

result The refraction-reflection strategy with regime-modulated thresholds is optimal.

dividend problem spectrally negative Markov additive models regime switching refraction-reflection strategy optimal control

2019-01-10abs ↗pdf ↗

Contrôle impulsionnel appliqué à la gestion de changement de technologie dans une entreprisemath.PR

We consider an impulse control problem in infinite horizon applied with switching technology. We suppose that the firm decides at certain moments (impulse moments) to switch technology, leading to a jump of the firm value. We show that the value function for such problems satisfies a dynamic programming principle versi…

2010-02-10abs ↗pdf ↗

Continuous-time mean-variance portfolio selection under non-Markovian regime-switching model with random horizonq-fin.MF

Study optimal portfolios in a non-Markovian regime-switching model with random time horizon.

problem Optimal portfolio selection in a market with non-Markovian regime-switching and random time horizon.

method Formulated as a constrained stochastic linear-quadratic optimal control problem, derived closed-form expressions for optimal portfolios and efficient frontier.

result Closed-form expressions for optimal portfolios and efficient frontier derived under non-Markovian regime-switching and random time horizon.

portfolio selection non-Markovian regime-switching random horizon optimal control closed-form solutions

2022-05-13abs ↗pdf ↗

Online Convex Optimization with Switching Cost and Delayed Gradientscs.LG

OMGD algorithm optimizes online convex optimization with switching costs and delayed gradients.

problem Optimizing online convex optimization with switching costs and delayed gradients.

method Proposed an online multiple gradient descent (OMGD) algorithm for quadratic and linear switching costs.

result OMGD achieves optimal dynamic regret in the limited information setting.

online convex optimization quadratic switching cost delayed gradients dynamic regret limited information

2023-10-18abs ↗pdf ↗

A System of BSDEs with Singular Terminal Values Arising in Optimal Liquidation with Regime Switchingq-fin.MF

Study optimal liquidation with multiple regimes using BSDEs with singular terminal values.

problem Optimal liquidation with regime switching in dark pools.

method Introduced a system of BSDEs with jumps and singular terminal values.

result Existence and uniqueness results for the BSDE system are obtained.

Optimal liquidation Regime switching BSDEs Dark pools Singular terminal values

2024-12-26abs ↗pdf ↗

Control randomisation approach for policy gradient and application to reinforcement learning in optimal switchingmath.OC

New framework for policy gradient methods in continuous time reinforcement learning.

problem Addressing policy gradient methods for continuous time reinforcement learning.

method Control randomisation technique to derive policy gradient representation for various Markovian control problems.

result Demonstrated application to optimal switching problems in the energy sector.

policy gradient reinforcement learning control randomisation Markovian control optimal switching

2024-04-27abs ↗pdf ↗

Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transitioncs.LG

Paper analyzes minimax regret in constrained online convex optimization with limited switching opportunities.

problem Minimizing regret in online convex optimization with limited switching opportunities.

method Introduced fugal game relaxation and mini-batching algorithm to establish minimax regret bounds.

result Minimax regret of switching-constrained OCO is Θ(T / √K).

online convex optimization minimax regret switching constraints fugal game mini-batching

2019-10-24abs ↗pdf ↗

Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPscs.LG

New algorithm reduces switching costs in RL beyond linear MDPs.

problem Costly policy switching in reinforcement learning.

method ELEANOR-LowSwitching algorithm for linear Bellman-complete MDPs.

result Achieves near-optimal regret with logarithmic switching cost.

reinforcement learning policy switching Markov Decision Processes regret minimization logarithmic cost

2023-02-24abs ↗pdf ↗

An adaptive approach to Bayesian Optimization with switching costscs.LG

Adaptive Bayesian Optimization for resource-constrained experiments with switching costs.

problem Sequential experimental design with varying costs for changing design variables.

method Adapted batch algorithms to sequential problem, proposing cost-aware and cost-ignorant methods.

result Cost-aware algorithm outperforms tuned process-constrained algorithms in all settings considered.

Bayesian Optimization Sequential Design Resource Constraints Switching Costs Sequential Experimental Design

2024-05-14abs ↗pdf ↗

Stochastic Knapsack Problem Revisited: Switch-Over Policies and Dynamic Pricingq-fin.PR

The stochastic knapsack has been used as a model in wide ranging applications from dynamic resource allocation to admission control in telecommunication. In recent years, a variation of the model has become a basic tool in studying problems that arise in revenue management and dynamic/flexible pricing; and it is in thi…

2007-08-08abs ↗pdf ↗

Optimal portfolio selection in an Itô-Markov additive marketq-fin.PM

Study optimal portfolio selection in a complex market with jumps and regime shifts.

problem Optimal portfolio selection in a market with jumps and regime shifts.

method Modeling a market with Lévy processes and regime switching, using various securities to complete the market, solving the portfolio selection problem for power and logarithmic utilities.

result Conditions for asymptotic-arbitrage-free market and solutions for optimal portfolio selection.

portfolio selection Itô-Markov additive market jump diffusion risk regime switching power-jump securities

2018-06-09abs ↗pdf ↗

Non-homogeneous stochastic LQ control with regime switching and random coefficientsmath.OC

The paper solves a complex control problem with stochastic elements and switching conditions.

problem Non-homogeneous stochastic LQ control with regime switching and random coefficients.

method Explicit optimal control and value obtained through two systems of backward stochastic differential equations (BSDEs). Existence and uniqueness of solutions proved using BMO martingales and contraction mapping method.

result Explicit optimal state feedback control and optimal value derived for the problem.

stochastic control regime switching random coefficients backward stochastic differential equations optimal control

2022-01-05abs ↗pdf ↗

Near-Optimal Adversarial Reinforcement Learning with Switching Costscs.LG

This paper tackles near-optimal adversarial RL with switching costs, providing algorithms and matching lower bounds.

problem Adversarial RL with switching costs, where loss distribution can be non-stationary or adversarial.

method Developed novel switching-reduced algorithms with matching lower bounds for known and unknown transition functions.

result Achieved near-optimal performance in adversarial RL with switching costs, matching theoretical lower bounds.

Adversarial Reinforcement Learning Switching Costs Regret Analysis Lower Bounds Provable Efficiency

2023-02-08abs ↗pdf ↗

Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processescs.LG

Algorithm learns to switch control among agents in a team.

problem Learning to switch control among reinforcement learning agents.

method 2-layer Markov decision process, upper confidence bounds, shared confidence bounds.

result Sublinear total regret with shared confidence bounds.

reinforcement learning team control Markov decision process upper confidence bounds shared confidence bounds

2020-02-11abs ↗pdf ↗

Pricing variance swaps in a hybrid model of stochastic volatility and interest rate with regime-switchingq-fin.MF

The paper develops a new hybrid model for pricing variance swaps.

problem Pricing variance swaps in a model with stochastic volatility and interest rate.

method Hybrid model combining Heston's stochastic volatility and CIR stochastic interest rate with regime-switching.

result A semi-closed form pricing formula for variance swaps is derived.

variance swaps stochastic volatility stochastic interest rate regime-switching

2016-03-28abs ↗pdf ↗

Asset Pricing in a Semi-Markov Modulated Market with Time-dependent Volatilityq-fin.MF

The study extends asset pricing models to include time-dependent volatility and age-dependent regime switching.

problem Asset pricing in a market with time-varying interest rates and volatilities.

method Extension of Markov-modulated models to semi-Markov processes with age-dependent and time-dependent volatility.

result Option pricing in the extended model is equivalent to solving an integral equation.

asset pricing semi-Markov processes regime switching time-dependent volatility integral equation

2016-09-15abs ↗pdf ↗

Testing the Number of Regimes in Markov Regime Switching Modelsecon.EM

This paper resolves the test for Markov regime switching models' regime number.

problem Testing the number of regimes in Markov regime switching models.

method Derives the asymptotic distribution of the likelihood ratio test statistic.

result Establishes the asymptotic validity of the parametric bootstrap.

Markov regime switching likelihood ratio test regime number asymptotic distribution parametric bootstrap

2018-01-21abs ↗pdf ↗

Error Bounds for Piecewise Smooth and Switching Regressionstat.ML

The paper derives error bounds for piecewise smooth and switching regression models.

problem Regression problems with target functions switching between different modes.

method Derives generalization error bounds using Rademacher complexities and chaining arguments.

result Error bounds with radical dependency on the number of modes for piecewise smooth regression, and linear dependency for switching regression.

regression piecewise smooth switching error bounds Rademacher complexities

2017-07-25abs ↗pdf ↗

Reflected Backward SDE approach to the price-hedge of defaultable claims with contingent switching CSAq-fin.PR

In this work we study the price-hedge issue for general defaultable contracts characterized by the presence of a contingent CSA of switching type. This is a contingent risk mitigation mechanism that allow the counterparties of a defaultable contract to switch from zero to full/perfect collateralization and switch back …

2014-12-03abs ↗pdf ↗

A free boundary problem arising from a multi-state regime-switching stock trading modelmath.AP

Study on stock trading model with uncertain market status, proving free boundaries and optimal strategies.

problem Optimal trading strategies in a stock market with uncertain market status.

method Free boundary problem, variational inequality system, degenerate operator, C^∞-smoothness.

result All four switching free boundaries are no-overlapping, monotonic, and C^∞-smooth, and their relative localities are completely determined.

stock trading free boundary problem regime-switching optimal strategies variational inequality

2020-08-17abs ↗pdf ↗

Optimal Dynamic Futures Portfolio in a Regime-Switching Market Frameworkq-fin.PM

Optimal futures trading strategy in a changing market model.

problem Dynamic trading in a regime-switching market.

method Utility maximization approach with HJB equations reduced to linear ODEs.

result Optimal futures positions and portfolio value across market regimes.

dynamic trading regime-switching futures utility maximization HJB equations

2019-10-14abs ↗pdf ↗

A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Costcs.LG

Paper presents an efficient algorithm for linear MDP with low switching cost.

problem Large state space reinforcement learning problems with low switching cost.

method First algorithm for linear MDP with low switching cost, achieving near-optimal regret and switching cost.

result Regret bound of $\widetilde{O}\left(\sqrt{d^3H^4K} ight)$ and near-optimal switching cost of $O\left(d H\log K ight)$.

reinforcement learning Markov decision process linear function approximation regret bound switching cost

2021-01-02abs ↗pdf ↗

Parameters Inference for Nonlinear Wave Equations with Markovian Switchingstat.ML

This paper addresses parameter estimation for wave equations with Markovian switching.

problem Parameter estimation for wave equations with abrupt changes.

method Bayesian statistical framework using discrete sparse Bayesian learning.

result Strong performance in parameter estimation for variable coefficient PDEs.

wave equations Markovian switching parameter inference Bayesian learning sparse learning

2024-08-12abs ↗pdf ↗

Optimal Starting-Stopping and Switching of a CIR Process with Fixed Costsq-fin.MF

This paper analyzes the problem of starting and stopping a Cox-Ingersoll-Ross (CIR) process with fixed costs. In addition, we also study a related optimal switching problem that involves an infinite sequence of starts and stops. We establish the conditions under which the starting-stopping and switching problems admit …

2014-11-22abs ↗pdf ↗

An Algorithm for Stochastic and Adversarial Bandits with Switching Costscs.LG

Algorithm for bandits with switching costs achieves optimal regret bounds.

problem Optimal regret bounds for stochastic and adversarial bandits with switching costs.

method Adaptation of Tsallis-INF algorithm with no prior knowledge of regime or time horizon.

result Achieves minimax optimal regret bounds in various settings.

bandits adversarial stochastic switching costs regret

2021-02-19abs ↗pdf ↗

Generalized Dynkin game of switching type representation for defaultable claims in presence of contingent CSAq-fin.MF

We study the solution's existence for a generalized Dynkin game of switching type which is shown to be the natural representation for general defaultable OTC contract with contingent CSA. This is a theoretical counterparty risk mitigation mechanism that allows the counterparty of a general OTC contract to switch from z…

2014-10-02abs ↗pdf ↗

Optimal mean-variance portfolio selection under regime-switching-induced stock price shocksq-fin.PM

Investigates optimal portfolio selection with regime-switching-induced stock price shocks.

problem Mean-variance portfolio selection with regime-switching and stock price jumps.

method Modeling regime-switching and stock price jumps, deriving optimal portfolio strategy and efficient frontier using ODEs.

result Added complexity due to regime-switching-induced stock price shocks, leading to nonlinear ODEs.

portfolio selection regime-switching stock price jumps mean-variance ODEs

2025-07-26abs ↗pdf ↗

Adaptive time series forecasting with markovian variance switchingstat.ML

New method forecasts time series with changing variances.

problem Real-world processes with changing variances cannot be captured by classical models.

method State-space model with Markov switching variances, using online learning and expert aggregation.

result Proposed method outperforms traditional expert aggregation and is robust to misspecification.

time series forecasting Markov switching variance switching online learning expert aggregation

2024-02-22abs ↗pdf ↗

Regime Switching Banditscs.LG

Study of multi-armed bandits with state-switching rewards using Markov models.

problem Multi-armed bandit problem with state-switching rewards.

method Spectral method-of-moments estimations for hidden Markov models, belief error control, upper-confidence-bound methods.

result Upper bound of

O(T^{2/3}\sqrt{\log T})

for the learning algorithm performance.

multi-armed bandits state-switching rewards Markov models spectral method upper-confidence-bound

2020-01-26abs ↗pdf ↗

Asset liquidation under drift uncertainty and regime-switching volatilityq-fin.MF

Study optimal asset liquidation under uncertain drift and volatility changes.

problem Optimal liquidation of assets with unknown drift and stochastic volatility.

method Modelled as a four-dimensional optimal stopping problem, solved using filtering theory and approximating sequences of three-dimensional problems.

result Determined optimal liquidation strategy and structural properties.

asset liquidation drift uncertainty regime-switching volatility optimal stopping filtering theory

2017-01-30abs ↗pdf ↗