*Indicators with optimal filtering of noise in the foreign exchange market.*Most of the indicators currently used by traders in the Forex market were created for another market - the stock market and for another time when there were sufficiently monotonous trends and quotes were not as volatile as they are now when there are no trends (as stable trends of unidirectional price movement). Moreover, the random noise of the foreign exchange market is now so great that (due to the summation of many random walks) they can even give rise to illusions of trends that will be determined by classical indicators that then give false signals. Therefore, almost the entire existing arsenal of indicators is not very suitable for trading on the Forex market and does not reflect key aspects of the state of this market.

The author has developed the number of new algorithms F ({Pi}) for recognizing and filtering random noise of market quotes and based on these algorithms he wrote indicators that, after optimizing them for the corresponding market, they allow you to enter it (the market) most profitably and close it in time open positions. Both the delay time T ({Pi}) of the filters constructed on their basis and the reliability R ({Pi}) of the signal generated by them depend on the parameters {Pi} of these algorithms. Both of these (T and R) factors influence the average profit B ({Pi}), which, therefore, depends on the {Pi} parameters. Therefore, such parameters {Pi0} filters are selected to the history of quotes of currency pairs that

**maximize the average statistical profit**max (B) = B ({Pi0}), which is the essence of

**optimal filtering**of market noise.

In addition, the author developed indicators that reveal the microstructure of the process of price changes and establish the true statistical characteristics of its regular and random components, which allowed us to develop effective algorithms for filtering market noise.

You can buy or download free indicators with optimal noise filtering on the MQL5 website at the link.

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