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Constant Function Market Makers (CFMMs) are a tool for creating exchange markets, have been deployed effectively in prediction markets, and are now especially prominent in the Decentralized Finance ecosystem. We show that for any set of…

Computer Science and Game Theory · Computer Science 2023-03-06 Mohak Goyal , Geoffrey Ramseyer , Ashish Goel , David Mazières

Optimization problems involving complex variables, when solved, are typically transformed into real variables, often at the expense of convergence rate and interpretability. This paper introduces a novel formalism for a prominent problem in…

Optimization and Control · Mathematics 2025-04-07 Raneem Madani , Abdel Lisser

Carr and Wu (2004), henceforth CW, developed a framework that encompasses almost all of the continuous-time models proposed in the option pricing literature. Their main result hinges on the stopping time property of the time changes, but…

Probability · Mathematics 2019-07-02 Hasan Fallahgoul , Kihun Nam

Patient trajectories from electronic health records are widely used to estimate conditional average potential outcomes (CAPOs) of treatments over time, which then allows to personalize care. Yet, existing neural methods for this purpose…

Machine Learning · Computer Science 2025-02-19 Konstantin Hess , Stefan Feuerriegel

This paper develops general approaches for pricing various types of American-style Parisian options (down-in/-out, perpetual/finite-maturity) with general payoff functions based on continuous-time Markov chain (CTMC) approximation under…

Computational Finance · Quantitative Finance 2025-03-17 Yuhao Liu , Nian Yang , Gongqiu Zhang

This paper studies motion planning of a mobile robot under uncertainty. The control objective is to synthesize a {finite-memory} control policy, such that a high-level task specified as a Linear Temporal Logic (LTL) formula is satisfied…

Robotics · Computer Science 2017-10-24 Meng Guo , Michael M. Zavlanos

Robust reinforcement learning is essential for deploying reinforcement learning algorithms in real-world scenarios where environmental uncertainty predominates. Traditional robust reinforcement learning often depends on rectangularity…

Machine Learning · Computer Science 2024-06-13 Adil Zouitine , David Bertoin , Pierre Clavier , Matthieu Geist , Emmanuel Rachelson

We study the optimal execution of market and limit orders with permanent and temporary price impacts as well as uncertainty in the filling of limit orders. Our continuous-time model incorporates a trade speed limiter and a trader director…

Mathematical Finance · Quantitative Finance 2017-04-13 Brian Bulthuis , Julio Concha , Tim Leung , Brian Ward

In financial markets, the order flow, defined as the process assuming value one for buy market orders and minus one for sell market orders, displays a very slowly decaying autocorrelation function. Since orders impact prices, reconciling…

Statistical Finance · Quantitative Finance 2015-06-19 Damian Eduardo Taranto , Giacomo Bormetti , Fabrizio Lillo

This paper develops a robust mathematical framework for Constant Function Market Makers (CFMMs) by transitioning from traditional token reserve analyses to a coordinate system defined by price and intrinsic liquidity. We establish a…

Mathematical Finance · Quantitative Finance 2026-03-03 Jimmy Risk , Shen-Ning Tung , Tai-Ho Wang

We consider a class of generalized capital asset pricing models in continuous time with a finite number of agents and tradable securities. The securities may not be sufficient to span all sources of uncertainty. If the agents have…

General Finance · Quantitative Finance 2012-10-23 Ulrich Horst , Michael Kupper , Andrea Macrina , Christoph Mainberger

This paper studies the dynamic programming principle using the measurable selection method for stochastic control of continuous processes. The novelty of this work is to incorporate intermediate expectation constraints on the canonical…

Optimization and Control · Mathematics 2020-04-22 Yuk-Loong Chow , Xiang Yu , Chao Zhou

In this paper we present a framework for risk-averse model predictive control (MPC) of linear systems affected by multiplicative uncertainty. Our key innovation is to consider time-consistent, dynamic risk metrics as objective functions to…

Optimization and Control · Mathematics 2015-11-24 Yin-Lam Chow , Marco Pavone

We devise an optimal allocation strategy for the execution of a predefined number of stocks in a given time frame using the technique of discrete-time Stochastic Control Theory for a defined market model. This market structure allows an…

Mathematical Finance · Quantitative Finance 2019-09-25 Akshay Bansal , Diganta Mukherjee

Commonly used limit order book attributes are empirically considered based on NASDAQ ITCH data. It is shown that some of them have the properties drastically different from the ones assumed in many market dynamics study. Because of this…

Trading and Market Microstructure · Quantitative Finance 2016-03-31 Vladislav Gennadievich Malyshkin , Ray Bakhramov

Continuous-time random walks are a well suited tool for the description of market behaviour at the smallest scale: the tick-to-tick evolution. We will apply this kind of market model to the valuation of perpetual American options:…

Pricing of Securities · Quantitative Finance 2008-12-02 Miquel Montero

A temporal logic is presented for reasoning about the correctness of timed concurrent constraint programs. The logic is based on modalities which allow one to specify what a process produces as a reaction to what its environment inputs.…

Logic in Computer Science · Computer Science 2007-05-23 F. S. de Boer , M. Gabbrielli , M. C. Meo

A new definition of continuous-time equilibrium controls is introduced. As opposed to the standard definition, which involves a derivative-type operation, the new definition parallels how a discrete-time equilibrium is defined, and allows…

Optimization and Control · Mathematics 2021-07-15 Yu-Jui Huang , Zhou Zhou

Time-distributed Optimization (TDO) is an approach for reducing the computational burden of Model Predictive Control (MPC). When using TDO, optimization iterations are distributed over time by maintaining a running solution estimate and…

Optimization and Control · Mathematics 2021-02-25 Dominic Liao-McPherson , Terrence Skibik , Jordan Leung , Ilya Kolmanovsky , Marco M. Nicotra

This paper studies multi-object reallocation without monetary transfers, where agents initially own multiple indivisible objects and have strict preferences over bundles (e.g., shift exchange among workers at a firm). Focusing on marginal…

Theoretical Economics · Economics 2026-02-05 Jacob Coreno , Di Feng