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Results for “compute” · papers 18 · wiki 5
Academic Papers · 18arXiv q-fin live 8 · desk corpus 50
arXiv · arXiv · 2025

Application of CTS (Computer to Screen) Machine in Printing Industries for Process Improvement & Material Optimization

The printing and labeling industries are struggling to meet the need for more complex and dynamic design requirements coming from the customers. It is now crucial to implement technological advancements to manage workflow, productivity, process optimization, and continual improvement. There has never been a time when the imagery and embellishments of apparel has been more commercially viable as it is now. Images and

Tarequl Islam
arXiv · arXiv · 2020

Risk & returns around FOMC press conferences: a novel perspective from computer vision

I propose a new tool to characterize the resolution of uncertainty around FOMC press conferences. It relies on the construction of a measure capturing the level of discussion complexity between the Fed Chair and reporters during the Q&A sessions. I show that complex discussions are associated with higher equity returns and a drop in realized volatility. The method creates an attention score by quantifying how much th

Alexis Marchal
arXiv · arXiv · 2014

Decoding Stock Market Behavior with the Topological Quantum Computer

A surprising image of the stock market arises if the price time series of all Dow Jones Industrial Average stock components are represented in one chart at once. The chart evolves into a braid representation of the stock market by taking into account only the crossing of stocks and fixing a convention defining overcrossings and undercrossings. The braid of stocks prices has a remarkable connection with the topologica

Ovidiu Racorean
arXiv · arXiv q-fin · 2017

Market impact with multi-timescale liquidity

We present an extended version of the recently proposed "LLOB" model for the dynamics of latent liquidity in financial markets. By allowing for finite cancellation and deposition rates within a continuous reaction-diffusion setup, we account for finite memory effects on the dynamics of the latent order book. We compute in particular the finite memory corrections to the square root impact law, as well as the impact de

Michael Benzaquen, Jean-Philippe Bouchaud
arXiv · arXiv q-fin · 2013

Simulating the Synchronizing Behavior of High-Frequency Trading in Multiple Markets

Nearly one-half of all trades in financial markets are executed by high-speed, autonomous computer programs -- a type of trading often called high-frequency trading (HFT). Although evidence suggests that HFT increases the efficiency of markets, it is unclear how or why it produces this outcome. Here we create a simple model to study the impact of HFT on investors who trade similar securities in different markets. We

Benjamin Myers, Austin Gerig
arXiv · arXiv q-fin · 2023

Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy

Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market indices, or other portfolios is of great importance to professional fund managers and individual investors alike. Our research uses the cross-sectional intrinsic entropy (CSIE) model to estimate the cross-sectional volatility of the stock groups that can be considered together as portfolio constituents. I

Claudiu Vinte, Marcel Ausloos
arXiv · arXiv · 2026

Pricing Lookback Options on a Quantum Computer

We develop a quantum algorithm to price discretely monitored lookback options in the Black-Scholes framework using imaginary time evolution. By rewriting the pricing PDE as a Schrodinger-type equation, the problem becomes the imaginary time evolution of a quantum state under a non-Hermitian Hamiltonian. This evolution is approximated with the Variational Quantum imaginary time evolution (VarQITE) method, which replac

Florence Paquette, Tania Belabbas, Emmanuel Hamel, Anne MacKay
arXiv · arXiv · 2026

Slippage-at-Risk (SaR): A Forward-Looking Liquidity Risk Framework for Perpetual Futures Exchanges

We introduce $\textbf{Slippage-at-Risk (SaR)}$, a quantitative framework for measuring liquidity risk in perpetual futures exchanges. Unlike backward-looking metrics such as Value-at-Risk computed on historical returns or realized deficit distributions, SaR provides a \emph{forward-looking} assessment of liquidation execution risk derived from current order book microstructure. The framework comprises three complemen

Otar Sepper
arXiv · arXiv · 2025

Automated Market Makers: A Stochastic Optimization Approach for Profitable Liquidity Concentration

Concentrated liquidity automated market makers (AMMs), such as Uniswap v3, enable liquidity providers (LPs) to earn liquidity rewards by depositing tokens into liquidity pools. However, LPs often face significant financial losses driven by poorly selected liquidity provision intervals and high costs associated with frequent liquidity reallocation. To support LPs in achieving more profitable liquidity concentration, w

Simon Caspar Zeller, Paul-Niklas Ken Kandora, Daniel Kirste, Niclas Kannengießer, Steffen Rebennack
arXiv · arXiv · 2024

Price-Aware Automated Market Makers: Models Beyond Brownian Prices and Static Liquidity

In this paper, we introduce a suite of models for price-aware automated market making platforms willing to optimize their quotes. These models incorporate advanced price dynamics, including stochastic volatility, jumps, and microstructural price models based on Hawkes processes. Additionally, we address the variability in demand from liquidity takers through models that employ either Hawkes or Markov-modulated Poisso

Philippe Bergault, Louis Bertucci, David Bouba, Olivier Guéant, Julien Guilbert
arXiv · arXiv · 2023

A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers

In decentralized finance ("DeFi"), automated market makers (AMMs) enable traders to programmatically exchange one asset for another. Such trades are enabled by the assets deposited by liquidity providers (LPs). The goal of this paper is to characterize and interpret the optimal (i.e., profit-maximizing) strategy of a monopolist liquidity provider, as a function of that LP's beliefs about asset prices and trader behav

Jason Milionis, Ciamac C. Moallemi, Tim Roughgarden
arXiv · arXiv · 2021

Analytic formula for option margin with liquidity costs under dynamic delta hedging

This study derives the expected liquidity cost when performing the delta hedging process of a European option. This cost is represented by an integration formula that includes European option prices and a certain function depending on the delta process. We first define a unit liquidity cost and then show that the liquidity cost is a multiplication of the unit liquidity cost, stock price, supply curve parameter, and t

Kyungsub Lee, Byoung Ki Seo
arXiv · arXiv · 2021

A Deep Deterministic Policy Gradient-based Strategy for Stocks Portfolio Management

With the improvement of computer performance and the development of GPU-accelerated technology, trading with machine learning algorithms has attracted the attention of many researchers and practitioners. In this research, we propose a novel portfolio management strategy based on the framework of Deep Deterministic Policy Gradient, a policy-based reinforcement learning framework, and compare its performance to that of

Huanming Zhang, Zhengyong Jiang, Jionglong Su
arXiv · arXiv · 2020

Competition analysis on the over-the-counter credit default swap market

We study two questions related to competition on the OTC CDS market using data collected as part of the EMIR regulation. First, we study the competition between central counterparties through collateral requirements. We present models that successfully estimate the initial margin requirements. However, our estimations are not precise enough to use them as input to a predictive model for CCP choice by counterparties i

Louis Abraham
arXiv · arXiv · 2019

Transaction Cost Analytics for Corporate Bonds

The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditi

Xin Guo, Charles-Albert Lehalle, Renyuan Xu
arXiv · arXiv · 2012

Heat Kernel Framework for Asset Pricing in Finite Time

A heat kernel approach is proposed for the development of a general, flexible, and mathematically tractable asset pricing framework in finite time. The pricing kernel, giving rise to the price system in an incomplete market, is modelled by weighted heat kernels which are driven by multivariate Markov processes and which provide enough degrees of freedom in order to calibrate to relevant data, e.g. to the term structu

Andrea Macrina
arXiv · arXiv · 2010

Liquidity in Credit Networks: A Little Trust Goes a Long Way

Credit networks represent a way of modeling trust between entities in a network. Nodes in the network print their own currency and trust each other for a certain amount of each other's currency. This allows the network to serve as a decentralized payment infrastructure---arbitrary payments can be routed through the network by passing IOUs between trusting nodes in their respective currencies---and obviates the need f

Pranav Dandekar, Ashish Goel, Ramesh Govindan, Ian Post
arXiv · arXiv q-fin · 2024

Decoding OTC Government Bond Market Liquidity: An ABM Model for Market Dynamics

The over-the-counter (OTC) government bond markets are characterised by their bilateral trading structures, which pose unique challenges to understanding and ensuring market stability and liquidity. In this paper, we develop a bespoke ABM that simulates market-maker interactions within a stylised government bond market. The model focuses on the dynamics of liquidity and stability in the secondary trading of governmen

Alicia Vidler, Toby Walsh
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