[R-SIG-Finance] Interpolating/comparing two irregulartime/price sequences?

[Gabor Grothendieck]

You can also get the previous tick by using

xy <- na.locf(xy)

in place of the na.approx line in Achim's code earlier in this thread.

On Nov 8, 2007 4:33 PM, Eric Zivot <ezivot at u.washington.edu> wrote:
> Just a few quick comments on this issue
>
> The Olsen group book, Introduction to High Frequency Finance, discusses
> various interpolation schemes to align multiple irregularly spaced data. For
> realized variance modeling Peter Hansen at Stanford showed that one should
> use the "previous tick" method for aligning data to a common time clock and
> not an linear interpolation around neighboring ticks. The latter method
> leads to degenerate results as you sample more frequently since the
> quadratic variation of a line is zero.
>
> The type of alignment discussed below is handled in the timeSeries class in
> S-PLUS using the align() function. Diethelm Wuertz implemented a subset of
> this class in R and I think the align() function is there too.
>
>
>  _____
>
> From: r-sig-finance-bounces at stat.math.ethz.ch
> [mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Adrian
> Trapletti
> Sent: Thursday, November 08, 2007 3:37 AM
> To: rory.winston at gmail.com
> Cc: R-Finance
> Subject: Re: [R-SIG-Finance] Interpolating/comparing two irregulartime/price
> sequences?
>
>
> Rory,
>
> There is no best method for synchronizing high frequency data. It depends on
> the application. One of the pioneers for high frequency financial data
> modelling was http://www.olsen.ch . In the 90ies they published some
> articles where they used interpolation schemes to model irregularly spaced
> high frequency data with standard discrete time series methods. You can find
> some articles on their website. Currently, there is a lot of work on the
> topic realized variance/volatility, and when it comes to multivariate
> applications, you may find some methods there
> http://www.google.ch/search?hl=en
> <http://www.google.ch/search?hl=en&q=%22realized+covariance%22&btnG=Search&m
> eta=> &q=%22realized+covariance%22&btnG=Search&meta=
>
> Best regards
> Adrian
>
>
>
>
> Message: 1
>
> Date: Wed, 7 Nov 2007 18:31:16 +0000
>
> From: "Rory Winston"  <mailto:rory.winston at gmail.com>
> <rory.winston at gmail.com>
>
> Subject: [R-SIG-Finance] Interpolating/comparing two irregular
>
>        time/price      sequences?
>
> To: r-sig-finance at stat.math.ethz.ch
>
> Message-ID:
>
>
> <mailto:3f446aa30711071031j37936e36i933be63c90f9ce4c at mail.gmail.com>
>
> <3f446aa30711071031j37936e36i933be63c90f9ce4c at mail.gmail.com>
>
> Content-Type: text/plain; charset=ISO-8859-1
>
>
>
> Hi all
>
>
>
> I have two data frames, that both look like the following:
>
>
>
>
>
> > head(series1)
>
>
>
>     timestamp     mid   spread
>
> 1 1.194438e+12 2.10011 0.000260
>
> 2 1.194438e+12 2.10010 0.000290
>
> ...
>
>
>
> These two time sequences are sampled on price ticks, so the interval
>
> between ticks is stochastic and irregular. The time sequences are also
>
> of different lengths, i.e. one may have 8 hours worth of data, the
>
> other may have 4. My issue is that I want to compare these two series
>
> for similarity - they should be producing almost exactly the same
>
> data, although potentially at slightly different timestamps (hence the
>
> sampling irregularity). I can subset the data so that they span
>
> roughly the same time intervals, but the number of ticks in each
>
> series will be different. Basically what I am trying to achieve is
>
> some sort of constant interpolation based on a time index - so that if
>
> series A starts at 08:01, contains 10,000 ticks, and ends at 16:05,
>
> and series B starts at 08:00, contains 7,000 ticks, and ends at 16:06,
>
> I would like to be able to index from series A into series B at say,
>
> each timestamp in A. Using a simple example, for the following series
>
> A and B:
>
>
>
> A:
>
> time   tick
>
> 16:01 2.05
>
> 16:02 2.06
>
>
>
>
>
> B:
>
> time tick
>
> 16:00 2.04
>
> 16:02 2.06
>
>
>
> I would like to be able to index from A into B at each tick from A, so
>
> I would get an output series that was the value of B at each time A
>
> ticked:
>
>
>
> C
>
> time tick
>
> 16:01 2.04 <--- constant interpolation from value of B @ 16:00
>
> 16:02 2.06
>
>
>
> Has anyone done anything like this before? I'm looking at the zoo
>
> package to see if it can help me, but I havent quite figured out how
>
> to do this kind of thing yet. Is this even a good way to checking
>
> whether series B is very similar to series A at the discrete tick
>
> intervals? Any better methods?(I guess another way might be to align
>
> the two subsetted series exactly and just take differences).
>
>
>
> Thanks
>
> Rory
>
>
>
>
>
>
>
>
>
>
> --
>
> Adrian Trapletti
>
> Wildsbergstrasse 31
>
> 8610 Uster
>
> Switzerland
>
>
>
> Phone :   +41 (0) 44 9945630
>
> Mobile :  +41 (0) 76 3705631
>
>
>
> Email :   a.trapletti at swissonline.ch
>
>        [[alternative HTML version deleted]]
>
>
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