/* * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ namespace QuantConnect.Indicators { /// /// Represents the traditional exponential moving average indicator (EMA). /// When the indicator is ready, the first value of the EMA is equivalent to the simple moving average. /// After the first EMA value, the EMA value is a function of the previous EMA value. /// Therefore, depending on the number of samples /// you feed into the indicator, it can provide different EMA values for a single /// security and lookback period. To make the indicator values consistent /// across time, warm up the indicator with all the trailing security price history. /// public class ExponentialMovingAverage : Indicator, IIndicatorWarmUpPeriodProvider { private readonly decimal _k; private readonly int _period; private readonly SimpleMovingAverage _initialValueSMA; /// /// Required period, in data points, for the indicator to be ready and fully initialized. /// public int WarmUpPeriod => _period; /// /// Initializes a new instance of the ExponentialMovingAverage class with the specified name and period /// /// The name of this indicator /// The period of the EMA public ExponentialMovingAverage(string name, int period) : this(name, period, SmoothingFactorDefault(period)) { } /// /// Initializes a new instance of the ExponentialMovingAverage class with the specified name and period /// /// The name of this indicator /// The period of the EMA /// The percentage of data from the previous value to be carried into the next value public ExponentialMovingAverage(string name, int period, decimal smoothingFactor) : base(name) { _period = period; _k = smoothingFactor; _initialValueSMA = new SimpleMovingAverage(period); } /// /// Initializes a new instance of the ExponentialMovingAverage class with the default name and period /// /// The period of the EMA public ExponentialMovingAverage(int period) : this($"EMA({period})", period) { } /// /// Initializes a new instance of the ExponentialMovingAverage class with the default name and period /// /// The period of the EMA /// The percentage of data from the previous value to be carried into the next value public ExponentialMovingAverage(int period, decimal smoothingFactor) : this($"EMA({period},{smoothingFactor})", period, smoothingFactor) { } /// /// Calculates the default smoothing factor for an ExponentialMovingAverage indicator /// /// The period of the EMA /// The default smoothing factor public static decimal SmoothingFactorDefault(int period) => 2.0m / (1 + period); /// /// Gets a flag indicating when this indicator is ready and fully initialized /// public override bool IsReady => Samples >= _period; /// /// Resets this indicator to its initial state /// public override void Reset() { base.Reset(); _initialValueSMA.Reset(); } /// /// Computes the next value of this indicator from the given state /// /// The input given to the indicator /// A new value for this indicator protected override decimal ComputeNextValue(IndicatorDataPoint input) { // we need to compute the initial value for the EMA, which is the SMA of the first N samples if (Samples <= _period) { _initialValueSMA.Update(input); } if (!IsReady) { return 0; } if (Samples == _period) { // first value is the SMA of the first period return _initialValueSMA.Current.Value; } return input.Value * _k + Current.Value * (1 - _k); } } }