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/

Zendy Plus

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

Zendy Tools

Zendy Open

Market impact is a key concept in the study of financial markets and severalmodels have been proposed in the literature so far. The Transient Impact Model(TIM) posits that the price at high frequency time scales is a linearcombination of the signs of the past executed market orders, weighted by aso-called propagator function. An alternative description -- the HistoryDependent Impact Model (HDIM) -- assumes that the deviation between therealised order sign and its expected level impacts the price linearly andpermanently. The two models, however, should be extended since prices are apriori influenced not only by the past order flow, but also by the pastrealisation of returns themselves. In this paper, we propose a two-eventframework, where price-changing and non price-changing events are consideredseparately. Two-event propagator models provide a remarkable improvement of thedescription of the market impact, especially for large tick stocks, where theevents of price changes are very rare and very informative. Specifically theextended approach captures the excess anti-correlation between past returns andsubsequent order flow which is missing in one-event models. Our resultsdocument the superior performances of the HDIMs even though only in minorrelative terms compared to TIMs. This is somewhat surprising, because HDIMs arewell grounded theoretically, while TIMs are, strictly speaking, inconsistent.

Linear models for the impact of order flow on prices I. Propagators: Transient vs. History Dependent Impact