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Results for “operations” · papers 16 · wiki 3
Academic Papers · 16arXiv q-fin live 15 · desk corpus 3
arXiv · arXiv q-fin · 2025

The Price of Liquidity: Implied Volatility of Automated Market Maker Fees

An automated market maker (AMM) provides a method for creating a decentralized exchange on the blockchain. For this purpose, individual investors lend liquidity to the AMM pool in exchange for a stream of fees earned from its operations as a market maker. Within this work, we reinterpret the loss-versus-rebalancing as the implied fee stream generated by an AMM so that a risk-neutral investor is indifferent in the dec

Maxim Bichuch, Zachary Feinstein
arXiv · arXiv q-fin · 2024

A Derivative Pricing Perspective on Liquidity Tokens in Constant Product Market Makers

In decentralized finance, any individual can pool their assets into an automated market maker (AMM) -- herein we focus on the constant product market maker (CPMM) -- in exchange for a claim on a fraction of future pool assets and fees earned from the market making operations. This position is represented by a liquidity token, whose prevailing on-chain price is effectively the initial deposited assets. Though this pri

Maxim Bichuch, Zachary Feinstein
arXiv · arXiv q-fin · 2023

Artificial Intelligence-based Analysis of Change in Public Finance between US and International Markets

Public finances are one of the fundamental mechanisms of economic governance that refer to the financial activities and decisions made by government entities to fund public services, projects, and operations through assets. In today's globalized landscape, even subtle shifts in one nation's public debt landscape can have significant impacts on that of international finances, necessitating a nuanced understanding of t

Kapil Panda
arXiv · arXiv q-fin · 2021

An Automated Portfolio Trading System with Feature Preprocessing and Recurrent Reinforcement Learning

We propose a novel portfolio trading system, which contains a feature preprocessing module and a trading module. The feature preprocessing module consists of various data processing operations, while in the trading part, we integrate the portfolio weight rebalance function with the trading algorithm and make the trading system fully automated and suitable for individual investors, holding a handful of stocks. The dat

Lin Li
arXiv · arXiv q-fin · 2021

Online Trading Models with Deep Reinforcement Learning in the Forex Market Considering Transaction Costs

In recent years, a wide range of investment models have been created using artificial intelligence. Automatic trading by artificial intelligence can expand the range of trading methods, such as by conferring the ability to operate 24 hours a day and the ability to trade with high frequency. Automatic trading can also be expected to trade with more information than is available to humans if it can sufficiently conside

Koya Ishikawa, Kazuhide Nakata
arXiv · arXiv q-fin · 2025

Optimal Fees for Liquidity Provision in Automated Market Makers

Passive liquidity providers (LPs) in automated market makers (AMMs) face losses due to adverse selection (LVR), which static trading fees often fail to offset in practice. We study the key determinants of LP profitability in a dynamic reduced-form model where an AMM operates in parallel with a centralized exchange (CEX), traders route their orders optimally to the venue offering the better price, and arbitrageurs exp

Steven Campbell, Philippe Bergault, Jason Milionis, Marcel Nutz
arXiv · arXiv q-fin · 2025

Optimal Exit Time for Liquidity Providers in Automated Market Makers

We study the problem of optimal liquidity withdrawal for a representative liquidity provider (LP) in an automated market maker (AMM). LPs earn fees from trading activity but are exposed to impermanent loss (IL) due to price fluctuations. While existing work has focused on static provision and exogenous exit strategies, we characterise the optimal exit time as the solution to a stochastic control problem with an endog

Philippe Bergault, Sébastien Bieber, Leandro Sánchez-Betancourt
arXiv · arXiv q-fin · 2024

Backtesting Framework for Concentrated Liquidity Market Makers on Uniswap V3 Decentralized Exchange

Decentralized finance (DeFi) has revolutionized the financial landscape, with protocols like Uniswap offering innovative automated market-making mechanisms. This article explores the development of a backtesting framework specifically tailored for concentrated liquidity market makers (CLMM). The focus is on leveraging the liquidity distribution approximated using a parametric model, to estimate the rewards within liq

Andrey Urusov, Rostislav Berezovskiy, Yury Yanovich
arXiv · arXiv q-fin · 2013

Portfolio Management Approach in Trade Credit Decision Making

The basic financial purpose of an enterprise is maximization of its value. Trade credit management should also contribute to realization of this fundamental aim. Many of the current asset management models that are found in financial management literature assume book profit maximization as the basic financial purpose. These book profitbased models could be lacking in what relates to another aim (i.e., maximization of

Grzegorz Michalski
arXiv · arXiv · 2024

The puzzle of Carbon Allowance spread

A growing number of contributions in the literature have identified a puzzle in the European carbon allowance (EUA) market. Specifically, a persistent cost-of-carry spread (C-spread) over the risk-free rate has been observed. We are the first to explain the anomalous C-spread with the credit spread of the corporates involved in the emission trading scheme. We obtain statistical evidence that the C-spread is cointegra

Michele Azzone, Roberto Baviera, Pietro Manzoni
arXiv · arXiv q-fin · 2016

Spread, volatility, and volume relationship in financial markets and market making profit optimization

We study the relationship between price spread, volatility and trading volume. We find that spread forms as a result of interplay between order liquidity and order impact. When trading volume is small adding more liquidity helps improve price accuracy and reduce spread, but after some point additional liquidity begins to deteriorate price. The model allows to connect the bid-ask spread and high-low bars to measurable

Jack Sarkissian
arXiv · arXiv q-fin · 2025

Risk-aware Trading Portfolio Optimization

We investigate portfolio optimization in financial markets from a trading and risk management perspective. We term this task Risk-Aware Trading Portfolio Optimization (RATPO), formulate the corresponding optimization problem, and propose an efficient Risk-Aware Trading Swarm (RATS) algorithm to solve it. The key elements of RATPO are a generic initial portfolio P, a specific set of Unique Eligible Instruments (UEIs),

Marco Bianchetti, Gabriele D'Acunto, Gianmarco De Francisci Morales, Yuko Kuroki, Marco Scaringi
arXiv · arXiv q-fin · 2025

Machine Learning Enhanced Multi-Factor Quantitative Trading: A Cross-Sectional Portfolio Optimization Approach with Bias Correction

Rolling-window factor pipelines for Chinese A-share markets contain a subtle but costly flaw: daily price-move limits (+/-10% main-board, +/-20% STAR/ChiNext) render a fraction of closing prices non-executable, yet standard implementations ingest these values before any row-filtering runs. The contaminated aggregates propagate silently through moving averages, correlations, and ranks--a failure mode we term "upstream

Yimin Du
arXiv · arXiv q-fin · 2023

Optimizing Trading Strategies in Quantitative Markets using Multi-Agent Reinforcement Learning

Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging. Within this context, reinforcement learning (RL), which operates on a reward-centric mechanism for optimal control, has surfaced as a potentially effective solution to the intricate financial decision-making conundrums presented. This paper delves into

Hengxi Zhang, Zhendong Shi, Yuanquan Hu, Wenbo Ding, Ercan E. Kuruoglu
arXiv · arXiv q-fin · 2020

Which Trading Agent is Best? Using a Threaded Parallel Simulation of a Financial Market Changes the Pecking-Order

This paper presents novel results generated from a new simulation model of a contemporary financial market, that cast serious doubt on the previously widely accepted view of the relative performance of various well-known public-domain automated-trading algorithms. Various public-domain trading algorithms have been proposed over the past 25 years in a kind of arms-race, where each new trading algorithm was compared to

Michael Rollins, Dave Cliff
arXiv · arXiv q-fin · 2016

Robust Optimization of Credit Portfolios

We introduce a dynamic credit portfolio framework where optimal investment strategies are robust against misspecifications of the reference credit model. The risk-averse investor models his fear of credit risk misspecification by considering a set of plausible alternatives whose expected log likelihood ratios are penalized. We provide an explicit characterization of the optimal robust bond investment strategy, in ter

Agostino Capponi, Lijun Bo
Wiki Entities · 3
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