Decided to do a bit of statistical work. I bought a book and built a multiplicative model :) using Excel. I have built regression, defined seasonal component (1 season - 24 hours, one hour archive of quotes was used) and built forecasting function.
Regression equation has the following form: Y=b0+b1*t+b2*t^2+b3*X1+b4*X2, где
Yi=CLOSEi-1(gold), t-time, X1=CLOSEi-1(gold)/CLOSEi-1(usd), X2=CLOSEi-1(gold), b0...b4- regression coefficients. (I hope it's clear)
So I got the following picture
Personally I'm fascinated by it, when you "see" what will happen. I want to write an indicator.
What is your opinion about it?
What is Close[i-1]USD ?
What is Close[i-1]USD ?
is the previous close for the dollar index
Simple autoregressive (AR) models like this one are good for modelling stationary processes. This says it all about price forecasting. There are more advanced models that work well with some types of non-stationarity, e.g. GARCH, EGARCH. The latter ones are often used for volatility prediction.
Well, actually, even under capitalism they shuffle them around so badly. First, the fundamental is announced, which leads to a jump in exchange rates, and then, after a month or a quarter, it is revised. It turns out to be another means of manipulation.
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Decided to do a bit of statistical work. I bought a book and built a multiplicative model :) using Excel. I have built regression, defined seasonal component (1 season - 24 hours, one hour archive of quotes was used) and built prediction function.
Regression equation has the following form: Y=b0+b1*t+b2*t^2+b3*X1+b4*X2, где
Yi=CLOSEi-1(gold), t-time, X1=CLOSEi-1(gold)/CLOSEi-1(usd), X2=CLOSEi-1(gold), b0...b4- regression coefficients. (I hope it's clear)
So I got the following picture
Personally I'm fascinated by it, when you "see" what will happen. I want to write an indicator.
Who has an opinion on the statistics?