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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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199399598797 · Jun 202019922001200920172026
48 results for inventory optimization

A new approach integrates inventory prediction and routing optimization for better supply chain management.

problem Optimizing efficient route selection in supply chain management with uncertain inventory demand.
method Decision-focused learning approach using neural networks to directly integrate inventory prediction and routing optimization.
result Direct integration of inventory prediction and routing optimization leads to better supply chain decisions.

Bayesian optimization improves forest inventory sampling using remote sensing data.

problem Optimizing forest inventory sampling in large areas with limited data.
method Bayesian optimization applied to RS data for improved sampling design.
result The proposed method outperforms baseline methods in terms of MSE values.

Study optimal pricing and inventory control in dynamic settings with censored demand.

problem Optimal pricing and inventory control in dynamic settings with censored demand.
method Approximate optimal policy via high-order MDP, propose novel algorithms for solving Bellman equations.
result Established finite-sample regret bounds and demonstrated efficacy through numerical experiments.

Deep neural networks optimize inventory decisions in complex supply chains.

problem Optimizing inventory decisions in stochastic multi-echelon supply chains.
method Pairwise modeling and DNN agents for order-up-to levels.
result The method performs better than alternate methods in general supply chain networks.

The paper analyzes optimal execution strategies for traders with inventory processes influenced by Brownian motion.

problem Optimal execution strategies for traders with inventory processes influenced by Brownian motion.
method Statistical tests and empirical analysis of intra-day data from the Toronto Stock Exchange.
result Empirical evidence supports the presence of a non-zero Brownian motion component in inventories and wealth processes.

Optimal hidden-target learning for online inventory optimization on general convex sets.

problem Online inventory optimization (OIO) on arbitrary bounded convex capacity sets.
method Maintaining a hidden target and projecting it onto the feasible order-up-to set.
result The method improves the best known regret guarantee for OIO on general convex sets from inverse to inverse-square-root dependence on the common-demand probability.

This paper optimizes perpetual contract liquidity by accounting for funding rates.

problem Optimal liquidity provision for perpetual contracts with stochastic funding rates.
method Formulated a control problem, solved with a HJB scheme, and calibrated on real data.
result Funding-aware market making improves performance and reduces inventory risk.

Study visualizes actor-critic loss landscapes for inventory optimization.

problem Difficulties in solving multi-store dynamic inventory control problems.
method Low-dimensional visualizations of actor loss function.
result Loss landscapes favor optimal policies in reinforcement learning.

We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the world is unobserved and must be inferred by the manager. We also assume that demands are observed only when they are completely met. We first derive t…

2012-06-27abs ↗pdf ↗

Unified theory for optimal execution through signal-adaptive quotes in limit order books.

problem Optimal execution in limit order books with signal-dependent factors.
method Develops a unified solution theory for four execution criteria, incorporating signal-dependent drift, price impact, inventory risk, and execution risk.
result Explicit formulas reveal optimal quoting strategies and show signal-dependent drift can significantly affect execution.

Model analyzes RFQ markets using stochastic control to optimize dealer performance and inventory.

problem Optimizing market making in aggregator-routed RFQ markets with varying dealer performance scores.
method Two-tier stochastic control model that separates RFQ-level price competition from macro routing.
result Optimal controls can be expressed through derivatives of reduced Hamiltonians, leading to interpretable mappings from optimal win probabilities to optimal offsets.

MaxCOSD algorithm tackles non-i.i.d. demands and stateful dynamics in online inventory control.

problem Managing inventory with non-i.i.d. demands and stateful dynamics.
method MaxCOSD, an online algorithm with provable guarantees for non-degeneracy assumptions.
result MaxCOSD achieves optimal performance for non-i.i.d. demands and stateful dynamics.

Optimal vehicle repositioning policy found for shared mobility services.

problem Matching fixed supply with spatial customer demand under uncertain and correlated demand.
method Base-stock repositioning policy, asymptotic optimality, regret analysis, adaptive repositioning algorithm.
result Surrogate Optimization and Adaptive Repositioning algorithm achieves optimal regret of O(n2.5T)O(n^{2.5} \sqrt{T}).

A contextual bandit method evaluates and improves inventory control policies.

problem Evaluating and improving periodic review inventory control policies with nonstationary demand.
method Contextual bandit-based algorithm to evaluate and tweak policies.
result The method achieves favorable guarantees in both theory and practice.

Paper introduces privacy-preserving inventory policy learning for feature-based newsvendor with unknown demand.

problem Privacy-preserving inventory policy learning for feature-based newsvendor with unknown demand distribution and nonsmooth loss function.
method Developed a clipped noisy gradient descent algorithm based on convolution smoothing for optimal inventory estimation within f-differential privacy framework.
result Achieved privacy-preserving optimal inventory policy with provable privacy guarantees and desirable statistical precision.

Solves inventory control with unknown demand trend using singular control.

problem Optimally managing inventory with an unknown demand trend.
method Formulates as a stochastic control problem under partial observation, solves equivalent separated problem using transition between formulations, and applies viscosity theory.
result Constructs an optimal control rule and shows bounded Lipschitz continuity of free boundaries.

New approach uses deep generative models for inventory and pricing decisions.

problem Data-driven inventory and pricing decisions in feature-based newsvendor problems.
method Conditional deep generative models (cDGMs) to learn demand distribution and generate probabilistic forecasts.
result Effective in optimizing inventory and pricing decisions, with theoretical guarantees and real-world applications.

New method reduces inventory inaccuracies by 10x, saving retailers 4% annually.

problem Inaccurate inventory records cost retailers 4% annually, and manual detection is impractical.
method Proposes a new anomaly detection method for low-rank Poisson matrices using cross-sectional data.
result Our approach reduces anomaly detection costs by up to 10x compared to existing methods.

Study bond market making with hit-ratio target using optimal control and HJB equations.

problem Optimizing bond market making with hit-ratio target in OTC markets.
method Stochastic optimal control approach, dualizing hit-ratio target, HJB equation, Riccati equation, linearization.
result Explicit quote decompositions into riskless spread, inventory-risk correction, and hit-ratio correction.

Modeling option market making with hedging-induced price impact.

problem Tackles the challenge of market making in options markets with price impact.
method Models option order flow using Cox processes and studies the dynamics of inventory and price under hedging-induced impact.
result Establishes the well-posedness of the mixed control problem involving quoting and hedging.

The paper develops a hybrid model for optimal order execution in markets with heterogeneous market makers.

problem Optimal liquidation in markets with limited inventory and risk capacity.
method Derives a reduced form model for aggregated inventory dynamics considering price impact.
result Optimal execution can be modeled as a linear-quadratic stochastic control problem.

Study on HFTs' interactions with a large trader using mean field game theory.

problem Interactions between high-frequency traders and a large trader executing assets at discrete times.
method Modeling HFTs' behavior using a jump process and solving the equilibrium through mean field game approach.
result Inventory-averse HFTs lower LT's costs when market impact is large.

Study on inventory management under uncertainty using smooth ambiguity preference.

problem Managing inventory under Knightian uncertainty with smooth ambiguity preference.
method Demonstrates continuous-time smooth ambiguity as the infinitesimal limit of Kalman-Bucy filtering with recursive robust utility. Solves forward-backward stochastic differential equations with quadratic growth to determine cost function. Derives value function and optimal control policy using variational inequalities and viscosity solutions. Transforms problem into two-dimensional singular control.
result Ambiguity drives decision-makers to act earlier, reducing the continuation region.

Paper applies RL to optimize inventory management across multiple products and nodes.

problem Optimizing inventory management for a large number of products with shared capacity in a multi-node supply chain.
method Novel multi-agent hierarchical reinforcement learning framework with A2C algorithm and quantised action spaces.
result The approach optimizes for maximizing product sales and minimizing wastage of perishable products.

The ad-trading desks of media-buying agencies are increasingly relying on complex algorithms for purchasing advertising inventory. In particular, Real-Time Bidding (RTB) algorithms respond to many auctions -- usually Vickrey auctions -- throughout the day for buying ad-inventory with the aim of maximizing one or severa…

2015-11-26abs ↗pdf ↗

Optimal market making strategy with price forecasts reduces inventory costs and spreads.

problem Optimal market making strategy with price forecasts reduces inventory costs and spreads.
method Modeling market making strategy with linear price impact, random slope and intercept, and simultaneous order arrivals.
result Simultaneous order arrivals and price forecasts reduce inventory costs and spreads.

Central bank strategy to maintain currency exchange rate within limits.

problem Maintaining a currency exchange rate within a target zone despite adverse economic trends.
method Modeling the problem with a continuous-time market impact model and solving it as a stochastic control problem.
result Optimal strategy minimizes accumulated inventory of foreign currency.

Study finds inventory inaccuracies are linked to store activity and product perishability.

problem Inventory record inaccuracy in grocery retailing environments.
method Analysis of 24,000 SKUs across 11 stores, field quasi-experiment on audits.
result Inventory audits can boost sales by 11%, especially for perishable items.

Modeling gas fee competition in decentralized exchanges to optimize arbitrage profits.

problem Gas fees and transaction ordering in decentralized exchanges create arbitrage opportunities.
method Developed a first equilibrium model of gas fee competition between two arbitrageurs under three transaction reversion settings.
result Mixed equilibria exist, and their characteristics depend on inventory risk and transaction settings.

In this paper we complete and extend our previous work on stochastic control applied to high frequency market-making with inventory constraints and directional bets. Our new model admits several state variables (e.g. market spread, stochastic volatility and intensities of market orders) provided the full system is Mark…

2013-03-28abs ↗pdf ↗

Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.

problem Limited research on market making in Chinese stock market.
method Optimal market making framework with exponential CARA utility function, accounting for market conditions and risks.
result Impact of volatility and stamp duty on market maker's profit and liquidity.

We propose a continuous-time stock-flow consistent model for inventory dynamics in an economy with firms, banks, and households. On the supply side, firms decide on production based on adaptive expectations for sales demand and a desired level of inventories. On the demand side, investment is determined as a function o…

2016-10-04abs ↗pdf ↗

We consider a repeated newsvendor problem where the inventory manager has no prior information about the demand, and can access only censored/sales data. In analogy to multi-armed bandit problems, the manager needs to simultaneously "explore" and "exploit" with her inventory decisions, in order to minimize the cumulati…

2017-10-16abs ↗pdf ↗

Study liquidity provision with exogenous competition using a reference market maker.

problem Liquidity provision in the presence of exogenous competition.
method Model a reference market maker who optimizes posted depths, competing market makers using a rule of thumb.
result Model admits approximate closed-form solution for a linear-quadratic goal functional.