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Here's a picture - it looks like an ordinary quote, in fact it's a sum of sine waves. I wonder if you can tell if it's a stationary series?
show not 1500 but 15000 or more observations...should be visible to the eye...
show not 1500 but 15000 or more observations...should be visible to the eye...
The use of dynamical systems of random structure in a textbook on econometrics may be described somewhere, although I have not come across it, but usually the descriptive apparatus you are interested in is devoted to literature on statistical mechanics or statistical dynamics, another name.
dynamic systems, but describing in dynamics exactly probabilistic characteristics of processes.
p.s. I hope, the author of the topic does not mind a short remark, faa1947 will not understand that his favorite package is not designed for analysis of market series with unstable probabilistic characteristics.
That's understandable. But in this sample?
What is the point? If we tie it to a segment of quotes (say a long sluggish growth)... this model will continue this segment... i.e. it will not show a fall...
faa1947
if you don't mind showing the practical application of the econ. package !
the article is frankly unimpressive...
Here's a picture - it looks like an ordinary quote, in fact it's a sum of sine waves. I wonder if it can be identified as a stationary series?
faa1947
if you can show the practical application of the econ. package !
The question is stated somewhat incorrectly. So it is correct to say that any series can be subjected to the test the results of which will help to make conclusion about its stationarity or non-stationarity with a certain confidence. On the other hand, there is always some uncertainty in any test on any data. That is, it is not only the set of input data that plays a role here, but also the way in which the decision is made.
Looking at the picture it seems that the series is non-stationary - the usual market quotes. But by origin it is stationary - the sum of the sinusoids. How to show that intuition is wrong on the given sample interval? For example with the purpose of identifying strongly/weakly non-stationary areas in real quotes?
By the way, it would be interesting to see what this economic package would say on the given data.
Both on them and on the real data... but since econometrics uses fa data (their retrieval and durability is a problem) i dont think that there is a real result that will work (just a little bit in + if to put in TS)
faa1947 show...at least something ....
Looking at the picture it seems that the series is non-stationary - the usual market quotes. But by origin it is stationary - the sum of the sinusoids. How to show that intuition is wrong on the given sample interval? For example with the purpose of identifying strongly/weakly non-stationary areas in real quotes?
Even if you select these sections... they will change chaotically, not with a certain step... it means it won't do anything... or even if it does, its practical use will be negligible... in my opinion, of course...