DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이민영 | - |
dc.contributor.author | JUNG, WOO SUNG | - |
dc.contributor.author | Oh, Gabjin | - |
dc.date.accessioned | 2020-06-23T09:56:21Z | - |
dc.date.available | 2020-06-23T09:56:21Z | - |
dc.date.created | 2020-05-26 | - |
dc.date.issued | 2020-05 | - |
dc.identifier.issn | 1932-6203 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/103785 | - |
dc.description.abstract | We investigate the dynamics of aggressive order in the financial market to further understand volatility. To analyze aggressive order, market orders in the order book are scrutinized. The market orders have different degrees of aggressiveness; therefore, we categorize market orders into four types: types Zero, One, A, and B, of which type B is the most aggressive. To examine the dynamics and impacts of each type of order, we use both macro- and micro-level approaches. From the macroscopic perspective, the burstiness and memory of type B is highly correlated with volatility. When traders face a financial crisis, they place bursty aggressive orders, and the orders are more predictable than usual. From the microscopic perspective, we additionally focus on the influence of the orders, particularly the price impact and resilience. The aggressive order has a greater impact than others, even when the price change of the aggressive order is smaller. Moreover, the aggressive order delivers more information on price because the aggressive order has a higher price impact than the execution cost. | - |
dc.language | English | - |
dc.publisher | PUBLIC LIBRARY SCIENCE | - |
dc.relation.isPartOf | PLOS ONE | - |
dc.title | The dynamics of the aggressive order during a crisis | - |
dc.type | Article | - |
dc.identifier.doi | 10.1371/journal.pone.0232820 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | PLOS ONE, v.15, no.5 | - |
dc.identifier.wosid | 000537525900012 | - |
dc.citation.number | 5 | - |
dc.citation.title | PLOS ONE | - |
dc.citation.volume | 15 | - |
dc.contributor.affiliatedAuthor | 이민영 | - |
dc.contributor.affiliatedAuthor | JUNG, WOO SUNG | - |
dc.identifier.scopusid | 2-s2.0-85085265273 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | EMPIRICAL-EVIDENCE | - |
dc.subject.keywordPlus | LINEAR-MODELS | - |
dc.subject.keywordPlus | PRICE-IMPACT | - |
dc.subject.keywordPlus | BOOK | - |
dc.subject.keywordPlus | MARKET | - |
dc.subject.keywordPlus | FLOW | - |
dc.subject.keywordPlus | FLUCTUATIONS | - |
dc.subject.keywordPlus | ORIGIN | - |
dc.subject.keywordPlus | TAILS | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
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