chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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 QuantConnect.Data.Market;
+using System;
+using System.Linq;
+
+namespace QuantConnect.Indicators
+{
+    /// <summary>
+    /// The Fractal Adaptive Moving Average (FRAMA) by John Ehlers
+    /// </summary>
+    public class FractalAdaptiveMovingAverage : BarIndicator, IIndicatorWarmUpPeriodProvider
+    {
+        private readonly int _n = 16;
+        private readonly double _w = -4.6;
+        private readonly RollingWindow<double> _high;
+        private readonly RollingWindow<double> _low;
+
+        /// <summary>
+        /// Initializes a new instance of the average class
+        /// </summary>
+        /// <param name="name">The name of the indicator instance</param>
+        /// <param name="n">The window period (must be even). Example value: 16</param>
+        /// <param name="longPeriod">The average period. Example value: 198</param>
+        public FractalAdaptiveMovingAverage(string name, int n, int longPeriod)
+            : base(name)
+        {
+            if (n % 2 > 0)
+            {
+                throw new ArgumentException($"{name}: N must be even, N = {n}", nameof(n));
+            }
+            _n = n;
+            _w = Math.Log(2d / (1 + longPeriod));
+            _high = new RollingWindow<double>(n);
+            _low = new RollingWindow<double>(n);
+        }
+
+        /// <summary>
+        /// Initializes a new instance of the average class
+        /// </summary>
+        /// <param name="n">The window period (must be even). Example value: 16</param>
+        /// <param name="longPeriod">The average period. Example value: 198</param>
+        public FractalAdaptiveMovingAverage(int n, int longPeriod)
+            : this($"FRAMA({n},{longPeriod})", n, longPeriod)
+        {
+
+        }
+
+        /// <summary>
+        /// Initializes a new instance of the average class
+        /// </summary>
+        /// <param name="n">The window period (must be even). Example value: 16</param>
+        public FractalAdaptiveMovingAverage(int n)
+            : this(n, 198)
+        {
+        }
+
+        /// <summary>
+        /// Computes the average value
+        /// </summary>
+        /// <param name="input">The data for the calculation</param>
+        /// <returns>The average value</returns>
+        protected override decimal ComputeNextValue(IBaseDataBar input)
+        {
+            var price = (input.High + input.Low) / 2;
+            _high.Add((double)input.High);
+            _low.Add((double)input.Low);
+
+            // our first data point just return identity
+            if (_high.Samples <= _high.Size)
+            {
+                return price;
+            }
+
+            var hh = _high.Take(_n / 2).Max();
+            var ll = _low.Take(_n / 2).Min();
+            var n1 = (hh - ll) / (_n / 2);
+
+            hh = _high.Skip(_n / 2).Take(_n / 2).Max();
+            ll = _low.Skip(_n / 2).Take(_n / 2).Min();
+
+            var n2 = (hh - ll) / (_n / 2);
+            var n3 = (_high.Max() - _low.Min()) / _n;
+
+            double dimen = 0;
+
+            if (n1 + n2 > 0 && n3 > 0)
+            {
+                var log = Math.Log((n1 + n2) / n3);
+                dimen = (double.IsNaN(log) ? 0 : log) / Math.Log(2);
+            }
+
+            var alpha = Math.Exp(_w * (dimen - 1));
+
+            if (alpha < .01)
+            {
+                alpha = .01;
+            }
+            if (alpha > 1)
+            {
+                alpha = 1;
+            }
+
+            return (decimal)alpha * price + (1 - (decimal)alpha) * Current.Value;
+        }
+
+        /// <summary>
+        /// Returns whether the indicator will return valid results
+        /// </summary>
+        public override bool IsReady => _high.IsReady;
+
+        /// <summary>
+        /// Required period, in data points, for the indicator to be ready and fully initialized.
+        /// </summary>
+        public int WarmUpPeriod => _high.Size;
+
+        /// <summary>
+        /// Resets the average to its initial state
+        /// </summary>
+        public override void Reset()
+        {
+            _high.Reset();
+            _low.Reset();
+            base.Reset();
+        }
+    }
+}