Where is the line between fitting and actual patterns? - page 16
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Regularisation algorithms are algorithms that prevent the over-learning effect of NS. If you google it, you can find quite a few implemented and working.
Thus with these algorithms, the very topic as 'the line between fit and regularity' simply disappears.
Although the question of network architecture remains open.
And don't confuse normalisation and regularisation.
Normalisation is about bringing differently scaled data to the same scale.
And lastly, not all types of NS work well in financial markets.
"Where is the line between fitting and real patterns?"
For myself, I have solved this question very simply: the same TS settings are bound to give approximately the same profitability, of course,
corrected for the volatility of the currency pair, while working on multiple currencies, at least 3-4 major pairs. If this condition
it is possible to fulfill this condition - the adjustment is excluded.
"Where is the line between fitting and real patterns?"
For myself, I have solved this question very simply: the same TS settings are bound to give approximately the same profitability, of course,
corrected for the volatility of the currency pair, while working on multiple currencies, at least 3-4 major pairs. If this condition
it is possible to fulfill this condition - the adjustment is excluded.
I think that if the code works according to real patterns, it will work profitably without any tweaking (tester optimization of ranges of using code parameters). This is probably what makes the difference.
Financial instruments are non-stationary and therefore do not have stable patterns
Isn't non-stationarity a stable pattern? :)
For the very gifted: non-stationarity is the absence of statistical regularities such as expectation and variance.
Put Bollinger envelopes on the chart and you can see what the "patterns" of nonstationarity are, because the centre of the indicator is expectation, and the distance from the centre to the envelopes is dispersion.
Of course, non-stationarity is also a kind of regularity. But you can't make any money from it ))))
Of course, non-stationarity is also a kind of regularity. But you can't make any money from it ))))
Of course, non-stationarity is also a kind of regularity. But you can't make money on it ))))