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.

169,181 papers · 148 categories

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48 results for “random switches”

Regime-Switching Langevin Monte Carlo Algorithmsstat.CO

New algorithms improve sampling from complex distributions.

problem Sampling from complex probability distributions efficiently.

method Regime-switching Langevin dynamics and Monte Carlo algorithms.

result Convergence guarantees and iteration complexities provided.

Langevin Monte Carlo regime-switching Markov Chain Monte Carlo Wasserstein distance random stepsizes

2025-08-31abs ↗pdf ↗

Consistent asset modelling with random coefficients and switches between regimesq-fin.PR

Model captures external influences through random parameters and regime switching.

problem Capturing external influences in asset dynamics with uncertainty and regime changes.

method Developed a stochastic model with random parameters and regime switching, mathematically consistent and interpretable.

result Demonstrated the model's versatility through local volatility models and characteristic functions.

stochastic model random parameters regime switching local volatility characteristic functions

2024-01-18abs ↗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 ↗

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 ↗

Modulated Information Flows in Financial Marketsmath.PR

Modeling financial information flows using random switches.

problem Understanding how new information sources affect financial markets.

method Modeling continuous-time information flows with random switches and Lévy bridges.

result The model captures complex information dynamics and can price financial options.

financial markets information flows random switches Lévy bridges stochastic volatility

2017-08-23abs ↗pdf ↗

Optimal consumption-investment with coupled constraints on consumption and investment strategies in a regime switching market with random coefficientsmath.PR

Study optimal consumption and investment strategies with constraints in a market with random coefficients.

problem Optimal consumption and investment strategies with constraints in a regime switching market with random coefficients.

method Explicit optimal strategies provided via solutions to new BSDE systems.

result Solving new BSDEs to find optimal values and strategies.

consumption-investment regime switching random coefficients optimal strategies BSDE systems

2022-11-10abs ↗pdf ↗

Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defensescs.LG

Paper proposes HRS to improve neural network robustness without significant accuracy loss.

problem Vulnerability of neural networks to adversarial attacks and performance degradation.

method Hierarchical Random Switching (HRS) for robustness without sacrificing accuracy.

result HRS significantly improves adversarial robustness with minimal accuracy loss.

neural networks adversarial attacks stochastic defenses robustness accuracy trade-off

2019-08-20abs ↗pdf ↗

Fast Policy Learning through Imitation and Reinforcementcs.LG

Combines imitation and reinforcement learning for faster policy improvement.

problem Combining imitation and reinforcement learning for faster policy improvement.

method Formulates RL and IL algorithms in a common mirror descent framework, proposes LOKI strategy.

result LOKI learns to outperform a suboptimal expert and converges faster than RL.

policy learning imitation learning reinforcement learning mirror descent policy gradient

2018-05-26abs ↗pdf ↗

Constrained optimal stopping under a regime-switching modelmath.PR

Study optimal stopping times under regime-switching models with constraints.

problem Optimal stopping times for discounted payoffs on a regime-switching geometric Brownian motion.

method Solve variational inequality to find value functions and optimal thresholds.

result Existence and expressions of optimal stopping times under specific conditions.

optimal stopping regime-switching geometric Brownian motion discounted payoffs variational inequality

2022-04-17abs ↗pdf ↗

Optimal control of risk process in a regime-switching environmentmath.OC

This paper is concerned with cost optimization of an insurance company. The surplus of the insurance company is modeled by a controlled regime switching diffusion, where the regime switching mechanism provides the fluctuations of the random environment. The goal is to find an optimal control that minimizes the total co…

2010-09-16abs ↗pdf ↗

Stochastic Switching Games and Duopolistic Competition in Emissions Marketsmath.OC

We study optimal behavior of energy producers under a CO_2 emission abatement program. We focus on a two-player discrete-time model where each producer is sequentially optimizing her emission and production schedules. The game-theoretic aspect is captured through a reduced-form price-impact model for the CO_2 allowance…

2010-01-20abs ↗pdf ↗

Deep Switch Networks for Generating Discrete Data and Languagecs.LG

Deep switch networks generate discrete data and language.

problem Generating high-dimensional discrete data and natural language.

method Adaptive switches model conditional distributions of discrete random variables. Maximum-likelihood objective function training with stochastic gradient descent.

result Stable and interpretable training of deep networks without backpropagation.

discrete data natural language maximum-likelihood stochastic gradient descent adaptive switches

2019-03-14abs ↗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 ↗

Continuous-time reinforcement learning for optimal switching over multiple regimesmath.OC

The paper develops RL methods for optimal switching between multiple states.

problem Optimal switching between multiple states in continuous time.

method Entropy-regularized exploration, HJB equations, policy improvement, value function convergence.

result The RL algorithm converges to optimal policies as temperature parameter vanishes.

reinforcement learning optimal switching Hamilton-Jacobi-Bellman entropy regularization policy improvement

2025-12-04abs ↗pdf ↗

Multidimensional indefinite stochastic Riccati equations and zero-sum stochastic linear-quadratic differential games with non-Markovian regime switchingmath.OC

Paper solves complex game theory problems with new equations.

problem Zero-sum stochastic games with non-Markovian switching.

method New multidimensional SRE and BSDE solutions.

result Existence and uniqueness of SRE solutions.

stochastic games regime switching SRE BSDE zero-sum

2023-09-10abs ↗pdf ↗

Regime Switching Optimal Growth Model with Risk Sensitive Preferencesmath.OC

Optimizes consumption under regime-switching economic states with risk-sensitive preferences.

problem Optimizing consumption in an economy with uncertain states and random shocks.

method Risk-sensitive optimization of consumption-utility with a Markov chain model of economic states and i.i.d. random shocks.

result Existence of unique optimal policy and value function in stationary policies.

Regime Switching Optimal Growth Risk-Sensitive Euler Equation Stationary Policies

2021-10-28abs ↗pdf ↗

Pricing Energy Contracts under Regime Switching Time-Changed modelsq-fin.PR

The paper improves energy contract pricing models by incorporating jumps and varying parameters.

problem Inaccurate pricing of energy contracts using the Black-Scholes-Merton model.

method Integrates regime switching and time-changed Levy processes with a two-state Markov chain.

result Improved accuracy in pricing energy contracts through a new model.

energy contracts regime switching time-changed models Levy processes Markov chain

2020-05-29abs ↗pdf ↗

Stochastic Control Problems with Infinite Horizon and Regime Switching Arising in Optimal Liquidation with Semimartingale Strategiesmath.OC

Study optimal liquidation strategies with infinite horizon and regime switching.

problem Optimal liquidation with semimartingale strategies in a stochastic environment.

method Characterization of value function and optimal strategy via BSDEs with infinite horizon.

result Existence and uniqueness of optimal control problem solutions.

Optimal liquidation Stochastic control Regime switching BSDEs Infinite horizon

2026-02-24abs ↗pdf ↗

Investment and Consumption with Regime-Switching Discount Ratesq-fin.PM

This paper considers the problem of consumption and investment in a financial market within a continuous time stochastic economy. The investor exhibits a change in the discount rate. The investment opportunities are a stock and a riskless account. The market coefficients and discount factor switch according to a finite…

2013-03-06abs ↗pdf ↗

Utility maximization in constrained and unbounded financial markets: Applications to indifference valuation, regime switching, consumption and Epstein-Zin recursive utilitymath.PR

Study utility maximization in financial markets with bounded and unbounded payoffs.

problem Utility maximization in financial markets with constraints and unbounded payoffs.

method Combines quadratic backward stochastic differential equations and convex duality.

result Established utility indifference valuation, regime switching, and consumption-investment problems in unbounded markets.

utility maximization financial markets bounded and unbounded payoffs convex duality regime switching

2017-07-01abs ↗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 ↗

Biracks and Switch Braid Quiversmath.GT

New polynomial invariants derived from birack and switch structures.

problem Polynomial invariants of braids.

method Switch structures, birack colorings, quiver-valued invariants.

result New polynomial invariants of braids.

biracks switches braids polynomial invariants quivers

2021-10-20abs ↗pdf ↗

Asymptotically optimal strategies in a diffusion approximation of a repeated betting gameq-fin.MF

Optimal strategies are found for a repeated betting game using diffusion approximation.

problem Finding optimal strategies for a repeated betting game with i.i.d. outcomes.

method Constructing a diffusion approximation of the repeated game and analyzing the wealth share process.

result Necessary and sufficient conditions for the wealth share process to be transient or recurrent are derived.

repeated game asymptotically optimal diffusion approximation wealth share Markovian regime switching

2021-08-26abs ↗pdf ↗

Optimal hedging in discrete timeq-fin.PR

Building on the work of Schweizer (1995) and Cern and Kallseny (2007), we present discrete time formulas minimizing the mean square hedging error for multidimensional assets. In particular, we give explicit formulas when a regime-switching random walk or a GARCH-type process is utilized to model the returns. Monte Carl…

2012-11-21abs ↗pdf ↗

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

In this paper, we study optimal switching problems under ambiguity. To characterize the optimal switching under ambiguity in the finite horizon, we use multidimensional reflected backward stochastic differential equations (multidimensional RBSDEs) and show that a value function of the optimal switching under ambiguity …

2016-08-22abs ↗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 ↗

Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densitiesstat.CO

New method samples from piecewise smooth distributions using Hamiltonian Monte Carlo.

problem Sampling from distributions with discontinuous gradients.

method Generalized Randomized Hamiltonian Monte Carlo (GRHMC) for piecewise smooth targets.

result GRHMC processes sample from piecewise smooth target distributions with the desired distribution as the invariant distribution.

Hamiltonian Monte Carlo piecewise smooth discontinuous gradients invariant distribution spike and slab prior

2025-04-25abs ↗pdf ↗

Many processors, little time: MCMC for partitions via optimal transport couplingsstat.ME

New MCMC method tackles label-switching problem for clustering.

problem Label-switching problem impedes MCMC efficiency in discrete clustering.

method Formulated optimal transport couplings for partition space.

result Our method efficiently overcomes label-switching problem.

MCMC clustering label-switching optimal transport partitions

2022-02-23abs ↗pdf ↗

On Investment-Consumption with Regime-Switchingmath.OC

In a continuous time stochastic economy, this paper considers the problem of consumption and investment in a financial market in which the representative investor exhibits a change in the discount rate. The investment opportunities are a stock and a riskless account. The market coefficients and discount factor switches…

2011-07-10abs ↗pdf ↗

On the Identifiability of Switching Dynamical Systemsstat.ML

This work extends identifiability analysis to sequential latent variable models, focusing on Switching Dynamical Systems.

problem Identifying latent variables in sequential data models.

method Proved identifiability of Markov Switching Models and established conditions for Switching Dynamical Systems.

result Identifiability of latent variables and non-linear mappings in Switching Dynamical Systems up to affine transformations.

identifiability Switching Dynamical Systems latent variables Markov models non-linear mappings

2023-05-25abs ↗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 ↗

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 ↗

Parrondo's effects with aperiodic protocolsphysics.soc-ph

Study shows aperiodic sequences enhance Parrondo's effect, with Thue-Morse outperforming others.

problem Enhancing Parrondo's effect through strategic switching protocols.

method Investigated Fibonacci, Thue-Morse, and Rudin-Shapiro sequences; analyzed capital correlation and persistence.

result Thue-Morse sequence outperforms other aperiodic sequences and benchmark games in capital gain.

Parrondo's effect aperiodic sequences Thue-Morse Rudin-Shapiro capital gain

2024-10-03abs ↗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 ↗

Discrete-time weak approximation of a Black-Scholes model with drift and volatility Markov switchingmath.PR

Study approximates financial market with discrete-time models.

problem Approximating continuous-time financial market models with discrete-time.

method Constructs discrete-time market models with Markov switching and proves convergence.

result Discrete-time models converge to continuous-time Black-Scholes model with Markov switching.

financial market discrete-time models Markov switching weak approximation Black-Scholes model

2025-01-12abs ↗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 ↗

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 ↗

Unsupervised learning of multiscale switching dynamical system models from multimodal neural datacs.LG

New algorithm learns switching dynamics from multiple neural signals.

problem Learning accurate switching dynamical system models from multimodal neural data.

method Unsupervised learning algorithm for multiscale switching dynamical system models.

result Switching multiscale dynamical system models outperform single-scale models in behavior decoding.

neural activity switching dynamics multimodal data unsupervised learning behavior encoding

2025-12-14abs ↗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 ↗

Alleviating Label Switching with Optimal Transportcs.LG

Solves label switching in mixture models using optimal transport.

problem Label switching in mixture model posterior inference prevents meaningful statistics assessment.

method Proposes an algorithm leveraging optimal transport to compute posterior statistics in a quotient space.

result Demonstrates advantages over alternative approaches on simulated and real data.

label switching mixture models optimal transport posterior inference

2019-11-05abs ↗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 ↗

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 ↗

Testing of Binary Regime Switching Models using Squeeze Duration Analysisq-fin.CP

Developed a new statistic to test binary regime switching models.

problem Testing the model assumption of binary regime switching extension of GBM.

method Proposed a new discriminating statistics and identified an admissible class of regime switching candidate models.

result Sampling distribution of the test statistics differs significantly between different regime switching models.

regime switching binary model statistical inference geometric Brownian motion Markov modulated GBM

2018-07-12abs ↗pdf ↗

Residual Switching Network for Portfolio Optimizationq-fin.ST

A new network learns market conditions and predicts stock performance.

problem Optimizing stock portfolio performance in the US equities market.

method Residual Switching Network combining two ResNets: a switching module and a main module.

result The residual switching network strategy outperformed other models with an average annual Sharpe ratio of 2.22.

portfolio optimization deep learning market regimes residual networks attention mechanism

2019-10-16abs ↗pdf ↗

Explicit-Duration Markov Switching Modelsstat.ML

Explicit-duration MSMs model time spent in different regimes.

problem Modeling time spent in different regimes of a time series.

method Graphical models to encode different information about regime change/reset boundaries.

result Models can define duration distributions of any form and reset dynamics.

Markov switching models hidden semi-Markov models changepoint models reset models graphical models

2019-09-12abs ↗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 ↗

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 ↗

Online learning with feedback graphs and switching costscs.LG

Study online learning with feedback graphs and switching costs, providing algorithms and optimal regret bounds.

problem Online learning with partial feedback and switching costs.

method Analysis of feedback graphs, lower bound on expected regret, new algorithms (Threshold Based EXP3, EXP3. SC).

result Order optimal algorithms for specific cases and Threshold Based EXP3 outperforms in empirical evaluations.

online learning feedback graphs switching costs regret bounds algorithms

2018-10-23abs ↗pdf ↗