We use a deep neural network to generate controllers for optimal trading on high-frequency
data. For the first time, a neural network learns the mapping between the preferences of the …

Full article: The inelastic market hypothesis: a microstructural interpretation Skip to Main Content
Taylor and Francis Online homepage Taylor and Francis Online homepage Log in | Register Cart …

This paper is devoted to the important yet unexplored subject of crowding effects on market
impact, that we call 'co-impact'. Our analysis is based on a large database of metaorders by …

Dealers in over-the-counter financial markets provide liquidity to customers on a principal
basis and manage the risk position that arises out of this activity in one of two ways. They …

Trading pressure from one asset can move the price of another, a phenomenon referred to
as cross impact. Using tick-by-tick data spanning 5 years for 500 assets listed in the United …

Thanks to the access to labeled orders on the CAC 40 index future provided by Euronext, we
are able to quantify market participants contributions to the volatility in the diffusive limit. To …

Equity auctions display several distinctive characteristics in contrast to continuous trading.
As the auction time approaches, the rate of events accelerates causing a substantial liquidity …

Full article: From zero-intelligence to queue-reactive: limit-order-book modeling for high-frequency
volatility estimation and optimal execution Skip to Main Content Taylor and Francis Online …

This paper studies optimal market making for large-tick assets in the presence of latency. We
consider a random walk model for the asset price and formulate the market maker's …

We revisit the trading invariance hypothesis recently proposed by Kyle, AS and Obizhaeva,
AA ['Market microstructure invariance: Empirical hypotheses.'Econometrica, 2016, 84 (4) …