|Appears in Collections:||Accounting and Finance Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Is there an ideal in-sample length for forecasting volatility?|
|Authors:||Kambouroudis, Dimos S|
|Citation:||Kambouroudis DS & McMillan D (2015) Is there an ideal in-sample length for forecasting volatility?, Journal of International Financial Markets, Institutions and Money, 37, pp. 114-137.|
|Abstract:||There is limited research carried out to date in the academic literature addressing the issue of the ideal in-sample size when forecasting volatility. This paper therefore considers how much data is required in order to produce accurate forecasts. Broadly speaking, two views exist between practitioners/investors who typically prefer a small in-sample to minimise data holding requirements and researchers/academics who typically chose large in-sample periods. Using a process of expanding window regressions where the in-sample start period expands (backward recursion) we conduct forecasts over twenty-three international markets, including both developed and emerging. Our findings, which demonstrate a degree of homogeneity, show that for the majority of the markets large in-sample periods are not necessary in order to produce the most accurate forecasts supporting the practitioners’/investors’ view.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|Kambouroudis and McMillan_JIFMIM_2015.pdf||4.7 MB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.