Skip navigation
Home
Browse
Communities
& Collections
Browse Items by:
Issue Date
Author
Title
Subject
Help
Sign on to:
My DSpace
Receive email
updates
Edit Profile
FUTMinna Institutional Repository
Search
Search:
All of DSpace
Journal Articles
SCHOOL OF PHYSICAL SCIENCES (SPS)
Statistics
for
Current filters:
Title
Author
Subject
Date Issued
Has File(s)
???jsp.search.filter.original_bundle_filenames???
???jsp.search.filter.original_bundle_descriptions???
Equals
Contains
ID
Not Equals
Not Contains
Not ID
Title
Author
Subject
Date Issued
Has File(s)
???jsp.search.filter.original_bundle_filenames???
???jsp.search.filter.original_bundle_descriptions???
Equals
Contains
ID
Not Equals
Not Contains
Not ID
Title
Author
Subject
Date Issued
Has File(s)
???jsp.search.filter.original_bundle_filenames???
???jsp.search.filter.original_bundle_descriptions???
Equals
Contains
ID
Not Equals
Not Contains
Not ID
Start a new search
Add filters:
Use filters to refine the search results.
Title
Author
Subject
Date Issued
Has File(s)
???jsp.search.filter.original_bundle_filenames???
???jsp.search.filter.original_bundle_descriptions???
Equals
Contains
ID
Not Equals
Not Contains
Not ID
Results 1-1 of 1 (Search time: 0.002 seconds).
previous
1
next
Item hits:
Issue Date
Title
Author(s)
2021-10-28
Trades in stock market anywhere in the world is faced with intense volatility due to stocks prices instability in real time that is mostly driven by information and other market dynamics. This research examines two volatility models with two different error distributions innovations in modelling and forecasting the continuous compounded return series (CCRS) of Nigeria All Share Index (NGX ASI) spot prices spanning the period of January 30, 2012 to June 30, 2021. The Generalized Autoregressive Conditional Heteroscedastic (GARCH) and Asymmetric Power Autoregressive Conditional Heteroscedastic ARCH (APARCH) volatility models under Student-t Distribution (StD) and Generalized Error Distribution (GED) error innovations are utilized. The best-fitted model is determined using Akaike’s Information Criterion (AIC) while Mean Square Error (MSE) is used to evaluate forecasts performance of the fitted volatility models. The results from the analysis showed that amongst competing models, APARCH (1,1)-GED was selected to be the best fitted volatility model with better forecasting power for the CCRS-NGX-ASI spot prices. This is because it produces the smallest AIC and MSE values
Gana, Y
;
Usman, A
Discover
Author
1
Gana, Y
Date issued
1
2021
Has File(s)
1
true