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- Detecting Cycles on market => Goertzel and Bartels test
- someone "codebreaker" wrote this and it's pertinent

By jaguar1637 3165 days ago Comments (1)

**Basic synoptical for a trading system**

#1 : Select a financial instrument.

#2 : Determine the "integration order" differentiating the time serie at the given timeframe several times until the "Dickey-Fuller Test" cannot reject the hypothesis of an unit root.

#3 : Find the best timeframe (can be "fractional") using the Shannon's "mutual information" method.

#4 : Design a "derivative filter" that match the integration order and compute two differents versions of the filter, one smoother than the other.

#5 : Use the "Radar Clutter Filter" like a "Trend Strength" indicator to disallow the trading in ranging markets and prevent from whipsaws.

#6 : The filters crossover determines the trading signals which the "trading range indicator" must approves.

#7 : Run the system in realtime for a time length (or a number of trades per day) defined by the "Chi-Squared Distribution" to check the reliability before playing with real money.

## Comments

Differentioning is used in Digital Signal Processing for processing signals.

Have a look at this

webpagefor examples of the practicle use of differentiationg.The whole construct falls subsequently as a pile of cards when you know that the market is not a signal. That does not mean that DSP methods are useless but.

The key of the methodology here is at the point 2 about the use of "Dickey-Fuller Test".

If the data might have an unit root then you can consider to predict the differences or growth rate (

link).However what I do not like in the approach is that it a prone to data mininf bias:

"Determine the "integration order" differentiating the time serie at the given timeframe several times until the "Dickey-Fuller Test" cannot reject the hypothesis of an unit root"This is scary, you shake the data until it shows what you want to see.