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ipolate
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ipolate
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Growing a Series
I have a series with some stock data that I want to grow at a given monthly rate.
The series (STOCK) has monthly data. I've created a scalar that holds my monthly growth rate (GROWTH).
I would like to create a second calculated series (STOCK_FORECAST) that starts with the last value in STOCK and grows it forward using the monthly growth rate (GROWTH).
Any help would be greatly appreciated!
The series (STOCK) has monthly data. I've created a scalar that holds my monthly growth rate (GROWTH).
I would like to create a second calculated series (STOCK_FORECAST) that starts with the last value in STOCK and grows it forward using the monthly growth rate (GROWTH).
Any help would be greatly appreciated!
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cointegration with structural breaks
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Growing a Series
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cointegration with structural breaks
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Undated or dated panel regression?
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d(log) log interpretation
Hi all,
I am having trouble interpreting my panel estimation
I have the following output dlog(y)= 13.905.log(x1) - 2.097.log(x2) + e
How do I interpret the coefficients ?
is it: a 1% increase in x1 will yield 13.905% increase in y ?
I am not sure if this is correct since its is the difference of log(y)... do you have to multiply or divide it by a 100 to get the same level of % change?
I am desperate
please help me
Thank
David
I am having trouble interpreting my panel estimation
I have the following output dlog(y)= 13.905.log(x1) - 2.097.log(x2) + e
How do I interpret the coefficients ?
is it: a 1% increase in x1 will yield 13.905% increase in y ?
I am not sure if this is correct since its is the difference of log(y)... do you have to multiply or divide it by a 100 to get the same level of % change?
I am desperate
please help me
Thank
David
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d(log) log interpretation
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Undated or dated panel regression?
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ARCH estimation error
Hi.
I'm working on an exercise where I have to obtain daily prices for the Norwegian and the US stock market indicies for the last 20 years. I used datastream to collect the numbers. For the Norwegian market I used OSEBX and SP500 for the US market.
One question that I have to answer is: Formally test for ARCH effects in the log returns series. Before I move on I must say that I only had estimation problem when testing for ARCH effects for SP500. The error msg I got: MA estimation requires a continuous sample.
My input when estimating equation: logrsp500 c ar(1) ma(1) (see workfile attahced)
logrsp500 = log return on sp500 data collected
Did the same procedure for my osebx data and I hade no problem with that.
eviews version: Std. edition jan 7 2010 build.
Thanks!
I'm working on an exercise where I have to obtain daily prices for the Norwegian and the US stock market indicies for the last 20 years. I used datastream to collect the numbers. For the Norwegian market I used OSEBX and SP500 for the US market.
One question that I have to answer is: Formally test for ARCH effects in the log returns series. Before I move on I must say that I only had estimation problem when testing for ARCH effects for SP500. The error msg I got: MA estimation requires a continuous sample.
My input when estimating equation: logrsp500 c ar(1) ma(1) (see workfile attahced)
logrsp500 = log return on sp500 data collected
Did the same procedure for my osebx data and I hade no problem with that.
eviews version: Std. edition jan 7 2010 build.
Thanks!
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ARCH estimation error
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Create new series subject to a condition
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Time varying SVAR
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ARCH estimation error
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Save Maximum of a Series
Suppose I have a series called "maxvalue". This series contains different values for each date for each cross-section. The cross sections are identified by the series "ident". I need to access the maximum value for each cross section of the series "maxvalue". The maximum value of "maxvalue" might be at different points in time for each cross section.
If if use something like
the same value (indeed the maximum value) for a cross sections is assigned to all points in time. I require it to be the maximum value at the point in time when it is maximized and zero or NA otherwise.
Still havent figured out how to get there.
If if use something like
Code:
show@maxsby(maxvalue, ident)
the same value (indeed the maximum value) for a cross sections is assigned to all points in time. I require it to be the maximum value at the point in time when it is maximized and zero or NA otherwise.
Still havent figured out how to get there.
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Save Maximum of a Series
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Save Maximum of a Series
Gareth, If I'm interpreting correctly, I think the original question was a bit more complicated, as the poster wanted the historical max at a each point in time. (If that interpretation is correct, the answer is only a tiny bit more complicated than your answer -- if I'm wrong, you all can just ignore me).
Suppose we have a dated panel structured workfile with the series F of interest.
We are going to write a recursion to identify the historical maximum for the cross-section at a given point in time. First, we seed the recursion.
Next, for the remaining periods we compute the historical maximum by comparing the current value to the lagged historical maximum.
Note that in since this is a dated panel workfile, the by-cross-section part of the calculation is handled naturally via the sample and recursion.
Lastly, we do the recoding to NAs.
Suppose we have a dated panel structured workfile with the series F of interest.
We are going to write a recursion to identify the historical maximum for the cross-section at a given point in time. First, we seed the recursion.
Code:
smpl @first @first
series cummax = f
Next, for the remaining periods we compute the historical maximum by comparing the current value to the lagged historical maximum.
Code:
smpl @first+1 @last
cummax = @recode(f>cummax(-1), f, cummax(-1))
Note that in since this is a dated panel workfile, the by-cross-section part of the calculation is handled naturally via the sample and recursion.
Lastly, we do the recoding to NAs.
Code:
smpl @all
series mymaxes = @recode(cummax=f, cummax, na)
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Save Maximum of a Series
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Time varying SVAR
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