The indicator refers back to the technique of probabilistic evaluation.
Prediction is carried out by the Monte Carlo methodology along with a mathematical mannequin of a neuron.
However, the modeling of samples for the tactic shouldn’t be made artificially, however comes from the unique “nature”, that’s, from historical past.
The variety of samples and the element of their modeling is achieved utilizing the bottom (relative present) timeframe.
The algorithm of the indicator :
Basically phrases, the algorithm boils all the way down to the truth that the indicator is skilled on the historical past of cause-samples and effect-samples, forming a type of cumulative effect-image, that’s, a forecast.
Additional, the generated forecast is checked for its pronounced pattern, and if it satisfies, then this forecast could be taken into consideration.
On the identical time, the forecast candlesticks are repainted in a distinct colour, and the value ranges beneficial for setting cease loss and take revenue additionally seem.
As an anticipated consequence within the case of an accurate forecast, a worthwhile transaction brings a number of shares of revenue.
As an anticipated consequence within the case of an incorrect forecast – a loss-making transaction brings just one share of the loss.
The frequency of full recalculation /retraining is the same as the frequency of the decrease timeframe, which is assigned mechanically, or could be chosen arbitrarily by means of an enter variable.
The length of the training historical past can also be set through an enter variable, and the very limitation of this length excludes the impact of overfitting.
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Basically phrases, the algorithm boils all the way down to the truth that the indicator is skilled on the historical past of cause-samples and effect-samples, forming a type of cumulative effect-image, that’s, a forecast.
Additional, the generated forecast is checked for its pronounced pattern, and if it satisfies, then this forecast could be taken into consideration.
On the identical time, the forecast candlesticks are repainted in a distinct colour, and the value ranges beneficial for setting cease loss and take revenue additionally seem.
As an anticipated consequence within the case of an accurate forecast, a worthwhile transaction brings a number of shares of revenue.
As an anticipated consequence within the case of an incorrect forecast – a loss-making transaction brings just one share of the loss.
The frequency of full recalculation /retraining is the same as the frequency of the decrease timeframe, which is assigned mechanically, or could be chosen arbitrarily by means of an enter variable.
The length of the training historical past can also be set through an enter variable, and the very limitation of this length excludes the impact of overfitting.
Basically phrases, the algorithm boils all the way down to the truth that the indicator is skilled on the historical past of cause-samples and effect-samples, forming a type of cumulative effect-image, that’s, a forecast.
Additional, the generated forecast is checked for its pronounced pattern, and if it satisfies, then this forecast could be taken into consideration.
On the identical time, the forecast candlesticks are repainted in a distinct colour, and the value ranges beneficial for setting cease loss and take revenue additionally seem.
As an anticipated consequence within the case of an accurate forecast, a worthwhile transaction brings a number of shares of revenue.
As an anticipated consequence within the case of an incorrect forecast – a loss-making transaction brings just one share of the loss.
The frequency of full recalculation /retraining is the same as the frequency of the decrease timeframe, which is assigned mechanically, or could be chosen arbitrarily by means of an enter variable.
The length of the training historical past can also be set through an enter variable, and the very limitation of this length excludes the impact of overfitting.
Description of enter variables :
HistoryDuration – the space of the training historical past, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
MovingSampleDuration – the scale (length) of the samples, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastDuration – the scale (length) of the forecast, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastRangeMultiplier – multiplier for the forecast amplitude.
ForecastAcceptableTendency – the worth of the satisfying pattern of the forecast, set in ATR-s.
AverageRangeDuration – the interval for calculating the ATR worth is about by the variety of candles of the present timeframe, with a price equal to zero, it’s mechanically assigned to HistoryDuration.
AverageRangeMultiplier – multiplier for the ATR worth.
ChartMessage – permits/disables the message within the chart window.
AlertMessage – permits/disables the alert in regards to the suitability of the forecast.
PushMessage – enabling/disabling push messages in regards to the suitability of the forecast.
LowerTimeframe – the decrease timeframe.
VolumesType – quantity sort.
HistoryDuration – the space of the training historical past, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
MovingSampleDuration – the scale (length) of the samples, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastDuration – the scale (length) of the forecast, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastRangeMultiplier – multiplier for the forecast amplitude.
ForecastAcceptableTendency – the worth of the satisfying pattern of the forecast, set in ATR-s.
AverageRangeDuration – the interval for calculating the ATR worth is about by the variety of candles of the present timeframe, with a price equal to zero, it’s mechanically assigned to HistoryDuration.
AverageRangeMultiplier – multiplier for the ATR worth.
ChartMessage – permits/disables the message within the chart window.
AlertMessage – permits/disables the alert in regards to the suitability of the forecast.
PushMessage – enabling/disabling push messages in regards to the suitability of the forecast.
LowerTimeframe – the decrease timeframe.
VolumesType – quantity sort.
HistoryDuration – the space of the training historical past, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
MovingSampleDuration – the scale (length) of the samples, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastDuration – the scale (length) of the forecast, set by the variety of candles of the present timeframe, when the worth is zero, it’s assigned mechanically.
ForecastRangeMultiplier – multiplier for the forecast amplitude.
ForecastAcceptableTendency – the worth of the satisfying pattern of the forecast, set in ATR-s.
AverageRangeDuration – the interval for calculating the ATR worth is about by the variety of candles of the present timeframe, with a price equal to zero, it’s mechanically assigned to HistoryDuration.
AverageRangeMultiplier – multiplier for the ATR worth.
ChartMessage – permits/disables the message within the chart window.
AlertMessage – permits/disables the alert in regards to the suitability of the forecast.
PushMessage – enabling/disabling push messages in regards to the suitability of the forecast.
LowerTimeframe – the decrease timeframe.
VolumesType – quantity sort.
The opposite enter variables relate to the colour settings and their objective is obvious from their identify.
Indicator buffers :
PredictedHighValues – the Excessive values of the forecast candlesticks.
PredictedLowValues – the Low values of the forecast candlesticks.
PredictedOpenValues – values of the Open candlesticks of the forecast.
PredictedCloseValues – Shut values of forecast candlesticks.
PredictedVolumeValues – the Quantity values of the forecast candlesticks.
The indicator buffers aren’t displayed on the chart (the default colour is None), as a result of they’re supposed solely when the indicator is known as from the skin.
An instance code for calling the indicator and checking the suitability of the forecast pattern worth is hooked up on the “Dialogue” tab.
Be aware :
The screenshots present the engineering model of the product within the type of an indicator within the subwindow of the graph.
The ultimate model of the product is made within the type of an indicator in the principle chart window and shows solely forecast candles.
The ultimate model of the product is made within the type of an indicator in the principle chart window and shows solely forecast candles.
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