Universal features of price formation in financial markets: perspectives from deep learning
type: Item
instance of: scholarly article
title: Universal features of price formation in financial markets: perspectives from deep learning
zbMATH Open document ID: 1420.91433
DOI: 10.1080/14697688.2019.1622295
author: Justin A. Sirignano
author: Rama Cont
published in: Quantitative Finance
publication date: 2019-09-26T00:00:00Z
full work available at URL: https://arxiv.org/abs/1803.06917
Mathematics Subject Classification ID: 91G10
Mathematics Subject Classification ID: 91-08
zbMATH DE Number: 7110489
zbMATH Keywords: financial econometrics
zbMATH Keywords: high-frequency data
zbMATH Keywords: machine learning
zbMATH Keywords: deep learning
zbMATH Keywords: price formation
zbMATH Keywords: market microstructure
zbMATH Keywords: intraday data
zbMATH Keywords: limit order book
MaRDI profile type: Publication
OpenAlex ID: W2790822776
arXiv ID: 1803.06917
cites work: Continuous cascade models for asset returns
cites work: Fluctuations and response in financial markets: the subtle nature of ‘random’ price changes
cites work: Empirical properties of asset returns: stylized facts and statistical issues
cites work: Price dynamics in a Markovian limit order market
cites work: A Stochastic Model for Order Book Dynamics
cites work: Automated trading with boosting and expert weighting
cites work: A one-level limit order book model with memory and variable spread
cites work: Q5270493
cites work: Multilayer feedforward networks are universal approximators
cites work: Market Microstructure Invariance: Empirical Hypotheses
cites work: The Long Memory of the Efficient Market
cites work: Nonlinear price impact from linear models
cites work: Deep learning for limit order books
Wikidata QID: Q127547692
description: scientific article; zbMATH DE number 7110489