Statistics as a way of looking into the future! - page 2
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"Numbers don't lie, but numbers do."
About the mesmerising picture. I recommend you look at it more closely. If it were that simple, everyone would be a millionaire.
There are 3 kinds of lies: 1. Hidden lies 2. Blatant lies 3. Statistics :) --- -1 :-)))) alas the comparison is not appropriate --- the saying was born during socialism... when facts were falsified
It's the same under capitalism.
For example labour productivity. They say it is several times greater in the West than in Russia (5 to 12). So they work 8 hours there... They don't move at work at the speed of supermen. There are a lot of managers there whose job is to "improve performance in reports". In order to increase production (which is necessary to raise the share price of the company, managers are very interested in this, because they are stimulated with a package of stock options at the time of hiring), reporting is improved, not innovations are introduced, etc...
It's the same under capitalism.
I take it you have a lot of experience working in Western countries. Or did you get this intimate knowledge from Channel 1 programmes?
I somehow think you have no work experience there, so please delete this nonsense so you won't be ashamed of yourself.
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 is clear)
Everything is clear about the regression. But the prognosis is not clear at all.
Everything is clear about the regression. But the prediction is not clear at all.
Forecast function is written as f=T*S, here T is trend component (regression), S is seasonal component. Seasonal component is calculated in certain way, and it has 24 values. I didn't make it up, it's written in the book. It is supposed to predict one hour ahead, in the picture it is 121 hour, and then there are no necessary values X1 and X2, these values are calculated using the Prediction function in EXCEL, which means it is better to trust the prediction at 121 hour, and then there may be discrepancies
Who has an opinion on the statistics?
Suggestion.
Present the result in Cartesian coordinate system, plot the increments of the predicted value on abscissa axis and model predictions of these increments as points on ordinate axis. Ideally (100% accurate prediction) you will get a cloud of points with a 45 degree slope. In reality you will get a low-pitch cloud (which is a measure of prediction accuracy) and a very thick one (this measure is a measure of the prediction scatter). To do it you should build a series of first differences for the tool (x[i]=Open[i]-Open[i-1]) and a series of first differences for the forecast (y[i]=Predict[i]-Predict[i-1]).
That's when you can meaningfully talk about the quality of the model you built.
The forecast function is written as f=T*S, where T is the trend component (regression) and S is the seasonal component. The seasonal component is calculated in a certain way, and it has 24 values. I didn't make all that up, it's written in the book. It is supposed to predict one hour ahead, in the picture it is 121 hour and then there are no necessary values X1 and X2, these values are calculated with the Prediction function in EXCEL, it means it is better to trust 121 hour predictions and then there may be some differences
It is clear that the information is taken from a book and not sucked out of your finger. Then at least share the bibliographical reference to the book, such as: author, title, publisher.
Statistics in business. A manager's and financier's guide. A. A. Minko
"Eksmo Moscow 2008.
>> Who has an opinion about statistics?
I think we all use it when we optimise EA parameters in the tester . Well, maybe some of us don't use it.
But when such a question arises, we unwittingly have statistics ... >> or it has us :) .