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Results for “sum of parts” · papers 18 · wiki 1
Academic Papers · 18arXiv q-fin live 0 · desk corpus 184
arXiv · arXiv · 2026

Deep Learning of Robust Market Making under Regime-Switching Order Flow

Classical market-making strategies based on stochastic control, such as the Avellaneda-Stoikov and the Guéant-Lehalle-Fernandez-Tapia (GLFT) extension, provide closed-form quoting rules, but rest on assumptions that break down at realistic microstructure timescales. One of them is that order flow is stationary, while empirical evidence points to the existence of regimes, possibly associated with algorithmic execution

Felipe Moret, Fabrizio Lillo
arXiv · arXiv · 2024

Credit Spreads' Term Structure: Stochastic Modeling with CIR++ Intensity

This paper introduces a novel stochastic model for credit spreads. The stochastic approach leverages the diffusion of default intensities via a CIR++ model and is formulated within a risk-neutral probability space. Our research primarily addresses two gaps in the literature. The first is the lack of credit spread models founded on a stochastic basis that enables continuous modeling, as many existing models rely on fa

Mohamed Ben Alaya, Ahmed Kebaier, Djibril Sarr
arXiv · arXiv · 2023

A stochastic control perspective on term structure models with roll-over risk

In this paper, we consider a generic interest rate market in the presence of roll-over risk, which generates spreads in spot/forward term rates. We do not require classical absence of arbitrage and rely instead on a minimal market viability assumption, which enables us to work in the context of the benchmark approach. In a Markovian setting, we extend the control theoretic approach of Gombani & Runggaldier (2013) and

Claudio Fontana, Simone Pavarana, Wolfgang J. Runggaldier
arXiv · arXiv · 2012

Funding Liquidity, Debt Tenor Structure, and Creditor's Belief: An Exogenous Dynamic Debt Run Model

We propose a unified structural credit risk model incorporating both insolvency and illiquidity risks, in order to investigate how a firm's default probability depends on the liquidity risk associated with its financing structure. We assume the firm finances its risky assets by mainly issuing short- and long-term debt. Short-term debt can have either a discrete or a more realistic staggered tenor structure. At rollov

Gechun Liang, Eva Lütkebohmert, Wei Wei
arXiv · arXiv · 2021

Liquidity-free implied volatilities: an approach using conic finance

We consider the problem of calculating risk-neutral implied volatilities of European options without relying on option mid prices but solely on bid and ask prices. We provide an approach, based on the conic finance paradigm, that allows to uniquely strip risk-neutral implied volatilities from bid and ask quotes, and that does not require restrictive assumptions. Our methodology also allows to jointly calculate the im

Matteo Michielon, Asma Khedher, Peter Spreij
arXiv · arXiv · 2021

From bid-ask credit default swap quotes to risk-neutral default probabilities using distorted expectations

Risk-neutral default probabilities can be implied from credit default swap (CDS) market quotes. In practice, mid CDS quotes are used as inputs, as their risk-neutral counterparts are not observable. We show how to imply risk-neutral default probabilities from bid and ask quotes directly by means of formulating the CDS calibration problem to bid and ask market quotes within the conic finance framework. Assuming the ri

Matteo Michielon, Asma Khedher, Peter Spreij
arXiv · arXiv · 2026

Liquidity-Based Audit of Algorithmic Trading Strategies

We show that net demand for liquidity by algo strategies is identifiable from its trade and price history alone, with no knowledge of its signal or optimization problem. An exact multi-period regret decomposition implies that the sign of this statistic classifies a linear strategy as a net liquidity consumer or provider, recovering the Kyle (1985) informed-trader/market-maker dichotomy from observables alone. Under a

Irene Aldridge
arXiv · arXiv · 2026

A unified theory of order flow, market impact, and volatility

We propose a microstructural model for the order flow in financial markets that distinguishes between {\it core orders} and {\it reaction flow}, both modeled as Hawkes processes. This model has a natural scaling limit that reconciles a number of salient empirical properties: persistent signed order flow, rough trading volume and volatility, and power-law market impact. In our framework, all these quantities are pinne

Johannes Muhle-Karbe, Youssef Ouazzani Chahdi, Mathieu Rosenbaum, Grégoire Szymanski
arXiv · arXiv · 2026

Directional Liquidity and Geometric Shear in Pregeometric Order Books

We introduce a structural framework for the geometry of financial order books in which liquidity, supply, and demand are treated as emergent observables rather than primitive market variables. The market is modeled as a relational substrate without assumed metric, temporal, or price coordinates. Observable quantities arise only through observation, implemented here as a reduction of relational degrees of freedom foll

João P. da Cruz
arXiv · arXiv · 2026

Pregeometric Origins of Liquidity Geometry in Financial Order Books

We propose a structural framework for the geometry of financial order books in which liquidity, supply, and demand are treated as emergent observables rather than primitive economic variables. The market is modeled as an inflationary relational system without assumed metric, temporal, or price coordinates. Observable quantities arise only through projection, implemented here via spectral embeddings of the graph Lapla

João P. da Cruz
arXiv · arXiv · 2025

Forecasting Liquidity Withdraw with Machine Learning Models

Liquidity withdrawal is a critical indicator of market fragility. In this project, I test a framework for forecasting liquidity withdrawal at the individual-stock level, ranging from less liquid stocks to highly liquid large-cap tickers, and evaluate the relative performance of competing model classes in predicting short-horizon order book stress. We introduce the Liquidity Withdrawal Index (LWI) -- defined as the ra

Haochuan, Wang
arXiv · arXiv · 2025

Statistical modeling of SOFR term structure

SOFR derivatives market remains illiquid and incomplete so it is not amenable to classical risk-neutral term structure models which are based on the assumption of perfect liquidity and completeness. This paper develops a statistical SOFR term structure model that is well-suited for risk management and derivatives pricing within the incomplete markets paradigm. The model incorporates relevant macroeconomic factors tha

Teemu Pennanen, Waleed Taoum
arXiv · arXiv · 2025

Arbitrage with bounded Liquidity

We derive the arbitrage gains or, equivalently, Loss Versus Rebalancing (LVR) for arbitrage between \textit{two imperfectly liquid} markets, extending prior work that assumes the existence of an infinitely liquid reference market. Our result highlights that the LVR depends on the relative liquidity and relative trading volume of the two markets between which arbitrage gains are extracted. Our model assumes that tradi

Christoph Schlegel, Quintus Kilbourn
arXiv · arXiv · 2025

Agent-based Liquidity Risk Modelling for Financial Markets

In this paper, we describe a novel agent-based approach for modelling the transaction cost of buying or selling an asset in financial markets, e.g., to liquidate a large position as a result of a margin call to meet financial obligations. The simple act of buying or selling in the market causes a price impact and there is a cost described as liquidity risk. For example, when selling a large order, there is market sli

Perukrishnen Vytelingum, Rory Baggott, Namid Stillman, Jianfei Zhang, Dingqiu Zhu
arXiv · arXiv · 2025

Optimal Investment in Equity and Credit Default Swaps in the Presence of Default

We consider an equity market subject to risk from both unhedgeable shocks and default. The novelty of our work is that to partially offset default risk, investors may dynamically trade in a credit default swap (CDS) market. Assuming investment opportunities are driven by functions of an underlying diffusive factor process, we identify the certainty equivalent for a constant absolute risk aversion investor with a semi

Zhe Fei, Scott Robertson
arXiv · arXiv · 2025

Dynamic Asset Pricing Theory for Life Contingent Risks

Although the valuation of life contingent assets has been thoroughly investigated under the framework of mathematical statistics, little financial economics research pays attention to the pricing of these assets in a non-arbitrage, complete market. In this paper, we first revisit the Fundamental Theorem of Asset Pricing (FTAP) and the short proof of it. Then we point out that discounted asset price is a martingale on

Patrick Ling
arXiv · arXiv · 2024

PolyModel for Hedge Funds' Portfolio Construction Using Machine Learning

The domain of hedge fund investments is undergoing significant transformation, influenced by the rapid expansion of data availability and the advancement of analytical technologies. This study explores the enhancement of hedge fund investment performance through the integration of machine learning techniques, the application of PolyModel feature selection, and the analysis of fund size. We address three critical ques

Siqiao Zhao, Dan Wang, Raphael Douady
arXiv · arXiv · 2024

Reinforcement Learning for Optimal Execution when Liquidity is Time-Varying

Optimal execution is an important problem faced by any trader. Most solutions are based on the assumption of constant market impact, while liquidity is known to be dynamic. Moreover, models with time-varying liquidity typically assume that it is observable, despite the fact that, in reality, it is latent and hard to measure in real time. In this paper we show that the use of Double Deep Q-learning, a form of Reinforc

Andrea Macrì, Fabrizio Lillo
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