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Analyzing & predicting the impact of news on the ASI return of Colombo stock exchange through black-litterman model

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dc.contributor.advisor Ranasinghe L
dc.contributor.author Perera PRSG
dc.date.accessioned 2022
dc.date.available 2022
dc.date.issued 2022
dc.identifier.citation Perera, P.R.S..G. (2022). Analyzing & predicting the impact of news on the ASI return of Colombo stock exchange through black-litterman mode [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa.lhttp://dhttp://dl.lib.uom.lk/handle/123/22499
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22499
dc.description.abstract Considering the historical data, we can conclude that news on attacks, international political problems, natural disasters, and protests have a negative impact on the stock market return while changes in Government Acts and Election period have a positive impact on stock market return. Further, Monetary & Fiscal policy changes and news on major investments have a neutral impact on the return. The significance of the news has been tested using the t-distribution method. It concludes that Monetary & Fiscal policy changes and news on major investments don't have a significant impact on index returns while other selected events have a significant impact on the index returns. By applying the Black-Litterman model together with hypothetical views, one can develop a P matrix to derive/ predict the return of the index movement. Therefore, an investor/analyst can consider the significance level of the news items (t-distribution results) and the type of impact (negative/positive) when assigning numbers and views for the P matrix. en_US
dc.language.iso en en_US
dc.subject ASI RETURN en_US
dc.subject COLOMBO STOCK EXCHANGE en_US
dc.subject BLACK-LITTERMAN MODEL en_US
dc.subject MATHEMATICS- Dissertation en_US
dc.subject FINANCIAL MATHEMATICS - Dissertation en_US
dc.title Analyzing & predicting the impact of news on the ASI return of Colombo stock exchange through black-litterman model en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MSc in Financial Mathematics en_US
dc.identifier.department Department of Mathematics en_US
dc.date.accept 2022
dc.identifier.accno TH4876 en_US


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