mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-06 04:57:44 +00:00
Miha Kralj
92 lines
3.6 KiB
C#
92 lines
3.6 KiB
C#
using System.Linq;
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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CMO: Chande Momentum Oscillator
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Chande Momentum Oscillator (also known as CMO indicator) was developed by Tushar S. Chande
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CMO is similar to other momentum oscillators (e.g. RSI or Stochastics). Alike RSI oscillator,
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the CMO values move in the range from -100 to +100 points and its aim is to detect the
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overbought and oversold market conditions. CMO calculates the price momentum on both the up
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days as well as the down days. The CMO calculation is based on non-smoothed price values
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meaning that it can reach its extremes more frequently and the short-time swings are more visible.
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Sources:
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https://www.technicalindicators.net/indicators-technical-analysis/144-cmo-chande-momentum-oscillator
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</summary> */
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public class CMO_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buff_up = new();
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private readonly System.Collections.Generic.List<double> _buff_dn = new();
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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private double _plast_value, _last_value;
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//core constructors
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public CMO_Series(int period, bool useNaN) : base() {
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_period = period;
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_NaN = useNaN;
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Name = $"CMO({period})";
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}
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public CMO_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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public CMO_Series() : this(period: 0, useNaN: false) { }
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public CMO_Series(int period) : this(period: period, useNaN: false) { }
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public CMO_Series(TBars source) : this(source.Close, 0, false) { }
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public CMO_Series(TBars source, int period) : this(source.Close, period, false) { }
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public CMO_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public CMO_Series(TSeries source) : this(source, 0, false) { }
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public CMO_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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//////////////////
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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if (update) { _last_value = _plast_value; } else { _plast_value = _last_value; }
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BufferTrim(buffer:_buff_up, (TValue.v > _last_value) ? TValue.v - _last_value : 0, period:_period, update: update);
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BufferTrim(buffer: _buff_dn, (TValue.v < _last_value) ? _last_value - TValue.v : 0, period: _period, update: update);
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_last_value = TValue.v;
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double _cmo_up = 0;
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double _cmo_dn = 0;
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for (int i = 0; i < Math.Min(_buff_up.Count, _buff_dn.Count); i++) {
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_cmo_up += _buff_up[i];
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_cmo_dn += _buff_dn[i];
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}
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double _cmo = 100 * (_cmo_up - _cmo_dn) / (_cmo_up + _cmo_dn);
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if (_cmo_up + _cmo_dn == 0) { _cmo = 0; }
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _cmo);
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return base.Add(res, update);
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}
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public new (DateTime t, double v) Add((DateTime t, double v) TValue) {
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return Add(TValue, false);
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buff_up.Clear();
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_buff_dn.Clear();
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}
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} |