wehub-resource-sync
100 lines
4.5 KiB
C#
100 lines
4.5 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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namespace QuantConnect.Indicators
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{
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/// <summary>
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/// This indicator computes the Kaufman Adaptive Moving Average (KAMA).
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/// The Kaufman Adaptive Moving Average is calculated as explained here:
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/// http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:kaufman_s_adaptive_moving_average
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/// </summary>
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public class KaufmanAdaptiveMovingAverage : KaufmanEfficiencyRatio
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{
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private readonly decimal _slowSmoothingFactor;
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private readonly decimal _diffSmoothingFactor;
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private decimal _prevKama;
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/// <summary>
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/// Initializes a new instance of the <see cref="KaufmanAdaptiveMovingAverage"/> class using the specified name and period.
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/// </summary>
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/// <param name="name">The name of this indicator</param>
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/// <param name="period">The period of the Efficiency Ratio (ER)</param>
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/// <param name="fastEmaPeriod">The period of the fast EMA used to calculate the Smoothing Constant (SC)</param>
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/// <param name="slowEmaPeriod">The period of the slow EMA used to calculate the Smoothing Constant (SC)</param>
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public KaufmanAdaptiveMovingAverage(string name, int period, int fastEmaPeriod = 2, int slowEmaPeriod = 30)
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: base(name, period)
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{
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// Smoothing factor of the slow EMA
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_slowSmoothingFactor = 2m / (slowEmaPeriod + 1m);
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// Difference between the smoothing factor of the fast and slow EMA
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_diffSmoothingFactor = 2m / (fastEmaPeriod + 1m) - _slowSmoothingFactor;
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}
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/// <summary>
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/// Initializes a new instance of the <see cref="KaufmanAdaptiveMovingAverage"/> class using the specified period.
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/// </summary>
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/// <param name="period">The period of the Efficiency Ratio (ER)</param>
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/// <param name="fastEmaPeriod">The period of the fast EMA used to calculate the Smoothing Constant (SC)</param>
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/// <param name="slowEmaPeriod">The period of the slow EMA used to calculate the Smoothing Constant (SC)</param>
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public KaufmanAdaptiveMovingAverage(int period, int fastEmaPeriod = 2, int slowEmaPeriod = 30)
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: this($"KAMA({period},{fastEmaPeriod},{slowEmaPeriod})", period, fastEmaPeriod, slowEmaPeriod)
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{
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}
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/// <summary>
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/// Computes the next value of this indicator from the given state
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/// </summary>
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/// <param name="input">The input given to the indicator</param>
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/// <param name="window">The window for the input history</param>
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/// <returns>A new value for this indicator</returns>
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protected override decimal ComputeNextValue(IReadOnlyWindow<IndicatorDataPoint> window, IndicatorDataPoint input)
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{
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// Calculate the efficiency ratio
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var efficiencyRatio = base.ComputeNextValue(window, input);
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if (Samples < Period)
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{
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return input.Value;
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}
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if (Samples == Period)
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{
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// Calculate the first KAMA
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// The yesterday price is used here as the previous KAMA.
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_prevKama = window[1].Value;
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}
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// Calculate the smoothing constant
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var smoothingConstant = efficiencyRatio * _diffSmoothingFactor + _slowSmoothingFactor;
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smoothingConstant *= smoothingConstant;
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// Calculate the KAMA like an EMA, using the
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// smoothing constant as the adaptive factor.
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_prevKama = (input.Value - _prevKama) * smoothingConstant + _prevKama;
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return _prevKama;
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}
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/// <summary>
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/// Resets this indicator to its initial state
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/// </summary>
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public override void Reset()
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{
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_prevKama = 0;
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base.Reset();
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}
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}
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}
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