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http://arks.princeton.edu/ark:/88435/dsp01jq085n58rFull metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Powell, Warren B. | - |
| dc.contributor.author | Patel, Raj | - |
| dc.date.accessioned | 2017-07-19T16:30:37Z | - |
| dc.date.available | 2017-07-19T16:30:37Z | - |
| dc.date.created | 2017-04-17 | - |
| dc.date.issued | 2017-4-17 | - |
| dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01jq085n58r | - |
| dc.description.abstract | This thesis explores the relationship between Twitter activity and stock price movement for companies. First, a novel sentiment extraction methodology is proposed to derive user sentiment regarding a company from a tweet. Public sentiment over time is used to analyze the relationship between bursts of Twitter activity and stock price movement. A hidden semi-Markov model is trained to model and simulate the joint process of Twitter sentiment, volume, and stock price, and an optimal policy for the buying and selling of stocks is found. | en_US |
| dc.language.iso | en_US | en_US |
| dc.title | Twitter Trading: Modeling Twitter Processes and Finding an Optimal Trading Policy | en_US |
| dc.type | Princeton University Senior Theses | - |
| pu.date.classyear | 2017 | en_US |
| pu.department | Operations Research and Financial Engineering | en_US |
| pu.pdf.coverpage | SeniorThesisCoverPage | - |
| pu.contributor.authorid | 960765836 | - |
| pu.contributor.advisorid | 010003590 | - |
| pu.certificate | Applications of Computing Program | en_US |
| Appears in Collections: | Operations Research and Financial Engineering, 2000-2019 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| Patel,_Raj_Final_Thesis.pdf | 3.66 MB | Adobe PDF | Request a copy |
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