Stock market prediction utilizing central bank’s policy statements

Показати скорочений опис матеріалу

dc.contributor.author Moiseiev, Roman
dc.date.accessioned 2020-02-21T14:21:16Z
dc.date.available 2020-02-21T14:21:16Z
dc.date.issued 2020
dc.identifier.citation Moiseiev, Roman. Stock market prediction utilizing central bank’s policy statements : Master Thesis : manuscript rights / Roman Moiseiev ; Supervisor Andriy Zhovtanetskyy ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2020. – 35 p. : ill. uk
dc.identifier.uri http://er.ucu.edu.ua/handle/1/2036
dc.language.iso en uk
dc.subject Stock market prediction uk
dc.subject Policy statement classification uk
dc.subject Multinomial Logistic Regression uk
dc.title Stock market prediction utilizing central bank’s policy statements uk
dc.type Preprint uk
dc.status Публікується вперше uk
dc.description.abstracten The stock market is quite unpredictable and affected by a vast number of factors. Moreover, many central banks, banks, hedge funds, and other financial institutions target their R&D departments to try to predict probabilities of market movements, possible black swans, and other risks. In this work, I target inefficiencies in the prediction of the market reaction on central bank policy statements. Such statements have two parts: action and information. Therefore in complicated cases, automatic trading systems react to actions and may not recognize vital insights from the informational component. To improve this, I collected historical data for monetary actions and press releases by Federal Reserve, stock price data, Fed Fund futures contract prices. Based on that, I build several classification models to predict the classofpolicystatements. Afterward,preparedpipelineandtheeconometricmodel that can incorporate a class of a policy statement for stock market reaction evaluation uk


Долучені файли

Даний матеріал зустрічається у наступних зібраннях

Показати скорочений опис матеріалу

Пошук


Перегляд

Мій обліковий запис