Optimal Execution under Incomplete Information

Fuente: arXiv
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Autori principali: Chevalier, Etienne, Hafsi, Yadh, Vath, Vathana Ly
Natura: Preprint
Pubblicazione: 2024
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author Chevalier, Etienne
Hafsi, Yadh
Vath, Vathana Ly
author_facet Chevalier, Etienne
Hafsi, Yadh
Vath, Vathana Ly
contents We study optimal liquidation strategies under partial information for a single asset within a finite time horizon. We propose a model tailored for high-frequency trading, capturing price formation driven solely by order flow through mutually stimulating marked Hawkes processes. The model assumes a limit order book framework, accounting for both permanent price impact and transient market impact. Importantly, we incorporate liquidity as a hidden Markov process, influencing the intensities of the point processes governing bid and ask prices. Within this setting, we formulate the optimal liquidation problem as an impulse control problem. We elucidate the dynamics of the hidden Markov chain's filter and determine the related normalized filtering equations. We then express the value function as the limit of a sequence of auxiliary continuous functions, defined recursively. This characterization enables the use of a dynamic programming principle for optimal stopping problems and the determination of an optimal strategy. It also facilitates the development of an implementable algorithm to approximate the original liquidation problem. We enrich our analysis with numerical results and visualizations of candidate optimal strategies.
format Preprint
id arxiv_https___arxiv_org_abs_2411_04616
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal Execution under Incomplete Information
Chevalier, Etienne
Hafsi, Yadh
Vath, Vathana Ly
Mathematical Finance
Trading and Market Microstructure
We study optimal liquidation strategies under partial information for a single asset within a finite time horizon. We propose a model tailored for high-frequency trading, capturing price formation driven solely by order flow through mutually stimulating marked Hawkes processes. The model assumes a limit order book framework, accounting for both permanent price impact and transient market impact. Importantly, we incorporate liquidity as a hidden Markov process, influencing the intensities of the point processes governing bid and ask prices. Within this setting, we formulate the optimal liquidation problem as an impulse control problem. We elucidate the dynamics of the hidden Markov chain's filter and determine the related normalized filtering equations. We then express the value function as the limit of a sequence of auxiliary continuous functions, defined recursively. This characterization enables the use of a dynamic programming principle for optimal stopping problems and the determination of an optimal strategy. It also facilitates the development of an implementable algorithm to approximate the original liquidation problem. We enrich our analysis with numerical results and visualizations of candidate optimal strategies.
title Optimal Execution under Incomplete Information
topic Mathematical Finance
Trading and Market Microstructure
url https://arxiv.org/abs/2411.04616