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# Antwort: Re: Re: st: Re: Lagged price

 From Justina Fischer <[email protected]> To [email protected] Subject Antwort: Re: Re: st: Re: Lagged price Date Sat, 29 Jan 2011 20:19:55 +0100

Good that we both agree on what the nature of her problem is. I proposed a way of resolving it with a hands-on technique, but I am sure that there are more sophisticated methods around, as you said.

Justina

[email protected] schrieb: -----

An: [email protected]
Von: Nick Cox <[email protected]>
Gesendet von: [email protected]
Datum: 29.01.2011 08:08PM
Thema: Re: Re: st: Re: Lagged price

Sounds plausible. In that case, you would have to arrange that
different observations can see each other. The thread on handling
siblings recently shows pertinent technique.

Nick

On Sat, Jan 29, 2011 at 6:55 PM, Justina Fischer <[email protected]> wrote:
> Hi Nick,
> I had the impression she wanted to calculate the difference between Q and T
> if both are avaible for a certain combination of day-time.
> Both Q and T are both available for 03-Jan-00 93203.
>
> But I agree she has to resolve some duplicates issue. Are different goods
> sold ? Then the identifier would be day-time-good.
>
> Justina
>
>
> [email protected] schrieb: -----
>
> An: [email protected]
> Von: Nick Cox <[email protected]>
> Gesendet von: [email protected]
> Datum: 29.01.2011 07:45PM
> Thema: Re: st: Re: Lagged price
>
> Sorry, you've lost me completely. There is no code here to show what
> you did. Perhaps it will be obvious to someone working with this kind
> of data who will answer. Otherwise, you may need to provide much more
> explanation.
>
> In any case, this example shows that you have some duplicates with
> exactly the same date and time. You need to think through the
> implications of that for the calculations I suggested, particular if
> there is instantaneous variation in prices.
>
> Nick
>
> On Sat, Jan 29, 2011 at 5:58 PM, Beatrice Crozza
> <[email protected]> wrote:
>> Dear Nick,
>>
>> thank you very much for your help.
>>
>> I have another question, concerning matching quotes (Q) with trades
>> (T) and doing the difference (diff) between the price and the midpoint
>> for trades and quotes that happen at the same time.
>>
>> Here, there is an example:
>>
>> date            time    type            midpoint        price        diff
>> 03-Jan-00       93158   Q       148.1563                       .
>> 03-Jan-00       93158   Q       148.1719                        .
>> 03-Jan-00       93159   Q       148.1563                        .
>> 03-Jan-00       93200   T                      148.25   .
>> 03-Jan-00       93201   T                      148.25   .
>> 03-Jan-00       93202   T                      148.25   .
>> 03-Jan-00       93203   Q       148.125                 .
>> 03-Jan-00       93203   T                     148.25            .
>>
>> Why the result is a missing value, also for the last observation? The
>> result should be 0.125
>> What I am doing wrong?
>>
>> Thank you very much for your help.
>>
>> Bea
>>
>> 2011/1/29 Nick Cox <[email protected]>:
>>> I disagree.
>>>
>>> Time series operators are not needed here. Other machinery will
>>> suffice. Indeed, time in the example data here is not regularly spaced,
>>> so lag operators would make some things more difficult.
>>>
>>> Nor is any looping required.
>>>
>>> -by:-, including subscripts under -by:-, remains one of the most
>>> underused tools in Stata.
>>>
>>> The previous price when different is found when the price changes
>>>
>>> gen previous = price[_n-1] if price != price[_n-1]
>>>
>>> That works too for previous[1], which will be price[0], namely missing.
>>>
>>> Then the previous price will remain so until the next change:
>>>
>>> replace previous = previous[_n-1] if missing(previous)
>>>
>>> This cascading to replace missings is an old Stata trick:
>>>
>>> FAQ     . . . . . . . . . . . . . . . . . . . . . . . Replacing missing
>>> values
>>>        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J.
>>> Cox
>>>        2/03    How can I replace missing values with previous or
>>>                following nonmissing values?
>>>                http://www.stata.com/support/faqs/data/missing.html
>>>
>>> That leaves a block of missings before the first price change (all
>>> observations if the price never changes).
>>>
>>> If this is desired, it may well be desired in a panel context:
>>>
>>> bysort id (time) : gen previous = price[_n-1] if price != price[_n-1]
>>> by id: replace previous = previous[_n-1] if missing(previous)
>>>
>>> If there are missings in -price-, they would be better filled in first
>>> in a clone of -price- using the device explained in the FAQ.
>>>
>>> Difference from previous different price is then simply
>>>
>>> gen diff = price - previous
>>>
>>> regardless of panel context.
>>>
>>> Nick
>>>
>>> On Fri, Jan 28, 2011 at 10:21 PM, Brad Wright <[email protected]> wrote:
>>>
>>>> I don't know of a formula per se, but you should definitely take
>>>> of Stata's time-series operators for lagging variables.
>>>>
>>>> You must first use tsset or xtset to tell Stata what format your data
>>>> are
>>>> in, and then creating lags is very simply done by using "L.varname" for
>>>> 1
>>>> lag or "2L.varname" for 2 periods and so on.
>>>>
>>>> Then you can write a piece of code that will automate this for you so
>>>> that
>>>> you can loop through all the combinations, stopping when you find the
>>>> first
>>>> "non-matching" period.
>>>
>>> "Beatrice Crozza"
>>>
>>>>> I want to infer the trade direction with a tick test, comparing two
>>>>> consecutive prices.
>>>>> I have a problem with Stata in order to construct the lagged price.
>>>>> When two consecutive prices are the same, I should go back one more
>>>>> lag, however, often I need to compare my price with a price of three
>>>>> or more previous periods.
>>>>>
>>>>> Here there is an example of my dataset:
>>>>>
>>>>> date          time         price
>>>>> 03jan2000 93157 148.25
>>>>> 03jan2000 93200 148.25
>>>>> 03jan2000 93201 148.27
>>>>> 03jan2000 93202 148.25
>>>>> 03jan2000 93203 148.25
>>>>> 03jan2000 93208 148.25
>>>>> 03jan2000 93211 148.25
>>>>> 03jan2000 93212 148.25
>>>>> 03jan2000 93215 148.15625
>>>>> 03jan2000 93225 148.25
>>>>>
>>>>> if I compare price at 93212 with the previous one, it is the same and
>>>>> also if I compare it with the price at 93208, so I should go further
>>>>> until I reach the price of 93201 which is different.
>>>>>
>>>>> If I want to do the difference for two consecutive prices I can write:
>>>>> price[_n]-price[n-1]
>>>>> a lag further:
>>>>> price[_n]-price[_n-2]
>>>>> and so on
>>>>>
>>>>> However, I would like to know if there is a formula to do the
>>>>> difference between to prices, until I find a price which is different
>>>>> from the one in consideration.

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