{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Risk Assessment in Intraday Trading","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77099"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"In these days, high frequency hedge funds have developed as a new and successful category of hedge funds. Accordingly, risk management is now obliged to keep pace with this market and takes intraday-risk management into consideration.  To aim to contribute on answering questions on intraday risk management, the dissertation consists of three parts. In first part, an intraday risk assessment model incorporating long-range dependence and heavy-tailness is suggested. Fractional integrated time series model with nearly elliptical distributed innovations are used to compute more accurate intraday level value at risk. Second part investigates the market efficiency by analyzing the relation between market sentiment and price movement. A theoretical consumption-based equilibrium model and empirical analysis are employed to show various behavior under different market sentiment and cross-sectional stocks. The third parts further analyzes the long-range dependence behaviors in equity markets cross-sectionally on different sampling frequencies and various market conditions."},{"label":"dcterms.available","value":"2017-09-20T16:51:57Z"},{"label":"dcterms.contributor","value":"Rachev, Svetlozar"},{"label":"dcterms.creator","value":"Dong, Fangfei"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:51:57Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:51:57Z"},{"label":"dcterms.description","value":"Department of Applied Mathematics and Statistics"},{"label":"dcterms.extent","value":"109 pg."},{"label":"dcterms.format","value":"Application/PDF"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77099"},{"label":"dcterms.issued","value":"2016-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:51:57Z (GMT). No. of bitstreams: 1\nDong_grad.sunysb_0771E_13065.pdf: 1214662 bytes, checksum: ae4433882ab5c0ce5ccd8ab6136aa559 (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"Applied mathematics"},{"label":"dcterms.title","value":"Risk Assessment in Intraday Trading"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/16%2F28%2F08%2F162808259137240498530258729274614871608/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/16%2F28%2F08%2F162808259137240498530258729274614871608","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}