/*
* 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);
}
}
}