|Appears in Collections:||Accounting and Finance Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Does Information Help Intra-Day Volatility Forecasts?|
Garcia, Raquel Quiroga
|Citation:||McMillan D & Garcia RQ (2013) Does Information Help Intra-Day Volatility Forecasts?, Journal of Forecasting, 32 (1), pp. 1-9.|
|Abstract:||While much research related to forecasting return volatility does so in a univariate setting, this paper includes proxies for information flows to forecast intra-day volatility for the IBEX 35 futures market. The belief is that volume or the number of transactions conveys important information about the market that may be useful in forecasting. Our results suggest that augmenting a variety of GARCH-type models with these proxies lead to improved forecasts across a range of intra-day frequencies. Furthermore, our results present an interesting picture whereby the PARCH model generally performs well at the highest frequencies and shorter forecasting horizons, whereas the component model performs well at lower frequencies and longer forecast horizons. Both models attempt to capture long memory; the PARCH model allows for exponential decay in the autocorrelation function, while the component model captures trend volatility, which dominates over a longer horizon. These characteristics are likely to explain the success of each model.|
|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.|
|McMillan_2013_Does_Information_Help_Intra-Day_Volatility_Forecasts.pdf||134.52 kB||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 dependant 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 firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.