- Observations with the same time-stamps are usually aggregated using the median.
- Which price do you want to take for the sampling grid? First, last, max, min, previous, next, linear interp.?
Itraday returns/ time series creation
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Hi,
I work with the below sample of (intraday) high freequency stock data:
sample:
STOCK DATE TIME PRICE VOLUME
ETE 22082011 11301514 05.21 500
ETE 22082011 11301713 06.51 1000
ETE 22082011 11311517 07.11 500
ETE 22082011 11321514 06.31 1000
I need to create new time series of stock returns (defined as Rt= ln(Pt/Pt-1)) for multiple time scales, i.e 3-min returns, 5-min returns,..., up to 180-min returns.
However the totalsize of the data is huge ( almost 9 mil observations).
Could someone suggest a time-efficient method of create these time series.
Many Thanks in advance
Panos,
PS: The column TIME indicates hour/minute/seconds/millisecs with observations being even at the same millisecond
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Oleg Komarov
2011-8-22
Before any suggestion:
See Brownlees & Gallo 2006, Computational Statistics & Data Analysis.
I suppose you need daily grids and you're sampling in calendar time (as opposed to tick-time sampling)?
If you're trying to calculated Realised Variance measures: http://www.kevinsheppard.com/wiki/MFE_Toolbox
This toolbox takes care of most of the aspects.
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Oleg Komarov
2011-8-22
I am working on my own function but in the meantime you can check realized_price_filter from the toolbox link I posted.You can decide the frequency but the previous price interploation is used, a very common choice in literature.
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