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LeastSquaresMovingAverage.cs
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LeastSquaresMovingAverage.cs
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/*
* 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.
*/
using System;
using System.Linq;
using MathNet.Numerics;
using MathNet.Numerics.LinearAlgebra;
namespace QuantConnect.Indicators
{
/// <summary>
/// The Least Squares Moving Average (LSMA) first calculates a least squares regression line
/// over the preceding time periods, and then projects it forward to the current period. In
/// essence, it calculates what the value would be if the regression line continued.
/// Source: https://rtmath.net/helpFinAnalysis/html/b3fab79c-f4b2-40fb-8709-fdba43cdb363.htm
/// </summary>
public class LeastSquaresMovingAverage : WindowIndicator<IndicatorDataPoint>
{
/// <summary>
/// Array representing the time.
/// </summary>
private readonly double[] t;
/// <summary>
/// The point where the regression line crosses the y-axis (price-axis)
/// </summary>
public IndicatorBase<IndicatorDataPoint> Intercept { get; private set; }
/// <summary>
/// The regression line slope
/// </summary>
public IndicatorBase<IndicatorDataPoint> Slope { get; private set; }
/// <summary>
/// Initializes a new instance of the <see cref="LeastSquaresMovingAverage"/> class.
/// </summary>
/// <param name="name">The name of this indicator</param>
/// <param name="period">The number of data points to hold in the window</param>
public LeastSquaresMovingAverage(string name, int period)
: base(name, period)
{
t = Vector<double>.Build.Dense(period, i => i + 1).ToArray();
Intercept = new Identity(name + "_Intercept");
Slope = new Identity(name + "_Slope");
}
/// <summary>
/// Initializes a new instance of the <see cref="LeastSquaresMovingAverage"/> class.
/// </summary>
/// <param name="period">The number of data points to hold in the window.</param>
public LeastSquaresMovingAverage(int period)
: this("LSMA" + period, period)
{
}
/// <summary>
/// Computes the next value of this indicator from the given state
/// </summary>
/// <param name="window"></param>
/// <param name="input">The input given to the indicator</param>
/// <returns>
/// A new value for this indicator
/// </returns>
protected override decimal ComputeNextValue(IReadOnlyWindow<IndicatorDataPoint> window, IndicatorDataPoint input)
{
// Until the window is ready, the indicator returns the input value.
if (window.Samples <= window.Size) return input;
// Sort the window by time, convert the observations to double and transform it to an array
var series = window
.OrderBy(i => i.Time)
.Select(i => Convert.ToDouble(i.Value))
.ToArray();
// Fit OLS
var ols = Fit.Line(x: t, y: series);
Intercept.Update(input.Time, (decimal)ols.Item1);
Slope.Update(input.Time, (decimal)ols.Item2);
// Calculate the fitted value corresponding to the input
return Intercept + Slope * Period;
}
/// <summary>
/// Resets this indicator and all sub-indicators (Intercept, Slope)
/// </summary>
public override void Reset()
{
Intercept.Reset();
Slope.Reset();
base.Reset();
}
}
}