dc.contributor.author | Nyamache, Francis M | |
dc.date.accessioned | 2020-10-28T08:30:41Z | |
dc.date.available | 2020-10-28T08:30:41Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://erepository.uonbi.ac.ke/handle/11295/153098 | |
dc.description.abstract | The purpose of this thesis is to model and forecast value-at-risk based on range-measuring
rather than the commonly acknowledged volatility models that are based on closing prices.
The use of close-to-close prices in modelling and forecasting value-at-risk might not capture
important intra-day information about the price movement. As a result, crucial price
movement information is lost and consequently the model becomes less e cient. This
thesis recommends the inclusion or range-measuring, described as the di erence between
the highest and lowest prices of an underlying stock within a time interval, a day, to compute
Value-at-Risk. The project uses data of an NSE-listed and trading company, SASN,
between November 2009 and November 2019 on which the predictability of range-based
and close-to-close estimates was established. It was observed that the values obtained
by range-based models were more accurate than when only the daily closing prices are
used. The range-based models successfully capture dynamics of the volatility and achieves
improve performance relative to the GARCH-type models. These ndings are fairly consistent
and can be extended to applications like portfolio optimization. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Nairobi | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Forecasting Value-At-Risk | en_US |
dc.title | Range-Based Approach To Volatility Modelling And Forecasting Value-At-Risk | en_US |
dc.type | Thesis | en_US |