English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper extends the analysis of Muni Toke and Yoshida (2020) to the caseof marked point processes. We consider multiple marked point processes withintensities defined by three multiplicative components, namely a commonbaseline intensity, a state-dependent component specific to each process, and astate-dependent component specific to each mark within each process. We showthat for specific mark distributions, this model is a combination of the ratiomodels defined in Muni Toke and Yoshida (2020). We prove convergence resultsfor the quasi-maximum and quasi-Bayesian likelihood estimators of this modeland provide numerical illustrations of the asymptotic variances. We use theseratio processes in order to model transactions occuring in a limit order book.Model flexibility allows us to investigate both state-dependency (emphasizingthe role of imbalance and spread as significant signals) and clustering.Calibration, model selection and prediction results are reported forhigh-frequency trading data on multiple stocks traded on Euronext Paris. Weshow that the marked ratio model outperforms other intensity-based methods(such as "pure" Hawkes-based methods) in predicting the sign and aggressivenessof market orders on financial markets.

Marked point processes and intensity ratios for limit order book modeling