mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-15 09:08:04 +00:00
GitVersion
GitVersion
This commit is contained in:
Miha Kralj
@@ -1,43 +1,43 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ADL: Chaikin Accumulation/Distribution Line
|
||||
ADL is a volume-based indicator that measures the cumulative Money Flow Volume:
|
||||
|
||||
1. Money Flow Multiplier = [(Close - Low) - (High - Close)] /(High - Low)
|
||||
2. Money Flow Volume = Money Flow Multiplier x Volume for the Period
|
||||
3. ADL = Previous ADL + Current Period's Money Flow Volume
|
||||
|
||||
Sources:
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:accumulation_distribution_line
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ADL_Series : Single_TBars_Indicator
|
||||
{
|
||||
private double _lastadl, _lastlastadl;
|
||||
|
||||
public ADL_Series(TBars source, bool useNaN = false) : base(source, 0, useNaN)
|
||||
{
|
||||
this._lastadl = this._lastlastadl = 0;
|
||||
if (_bars.Count > 0)
|
||||
{ base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ this._lastadl = this._lastlastadl; }
|
||||
|
||||
double _mfm = ((TBar.c - TBar.l) - (TBar.h - TBar.c)) / (TBar.h - TBar.l);
|
||||
double _mfv = _mfm * TBar.v;
|
||||
double _adl = this._lastadl + _mfv;
|
||||
|
||||
this._lastlastadl = this._lastadl;
|
||||
this._lastadl = _adl;
|
||||
|
||||
var ret = (TBar.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _adl);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ADL: Chaikin Accumulation/Distribution Line
|
||||
ADL is a volume-based indicator that measures the cumulative Money Flow Volume:
|
||||
|
||||
1. Money Flow Multiplier = [(Close - Low) - (High - Close)] /(High - Low)
|
||||
2. Money Flow Volume = Money Flow Multiplier x Volume for the Period
|
||||
3. ADL = Previous ADL + Current Period's Money Flow Volume
|
||||
|
||||
Sources:
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:accumulation_distribution_line
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ADL_Series : Single_TBars_Indicator
|
||||
{
|
||||
private double _lastadl, _lastlastadl;
|
||||
|
||||
public ADL_Series(TBars source, bool useNaN = false) : base(source, 0, useNaN)
|
||||
{
|
||||
this._lastadl = this._lastlastadl = 0;
|
||||
if (_bars.Count > 0)
|
||||
{ base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ this._lastadl = this._lastlastadl; }
|
||||
|
||||
double _mfm = ((TBar.c - TBar.l) - (TBar.h - TBar.c)) / (TBar.h - TBar.l);
|
||||
double _mfv = _mfm * TBar.v;
|
||||
double _adl = this._lastadl + _mfv;
|
||||
|
||||
this._lastlastadl = this._lastadl;
|
||||
this._lastadl = _adl;
|
||||
|
||||
var ret = (TBar.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _adl);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
}
|
||||
@@ -1,45 +1,45 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ADO: Chaikin Accumulation/Distribution Oscillator
|
||||
ADO measures the momentum of ADL using the difference between slow (10-day) EMA(ADL)
|
||||
and fast (3-day) EMA(ADL):
|
||||
|
||||
Chaikin A/D Oscillator = (3-day EMA of ADL) - (10-day EMA of ADL)
|
||||
|
||||
Sources:
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:chaikin_oscillator
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ADOSC_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly ADL_Series _TSadl;
|
||||
|
||||
private readonly EMA_Series _TSslow;
|
||||
private readonly EMA_Series _TSfast;
|
||||
private readonly SUB_Series _TSado;
|
||||
|
||||
public ADOSC_Series(TBars source, bool useNaN = false) : base(source, period: 0, useNaN)
|
||||
{
|
||||
_TSadl = new(source: source, useNaN: false);
|
||||
_TSslow = new(source: _TSadl, period: 10, useNaN: false);
|
||||
_TSfast = new(source: _TSadl, period: 3, useNaN: false);
|
||||
_TSado = new(_TSfast, _TSslow);
|
||||
|
||||
if (source.Count > 0)
|
||||
{ base.Add(_TSado); }
|
||||
Console.WriteLine(base.Count);
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ _TSadl.Add(TBar, true); }
|
||||
|
||||
double _ado = this._TSado[(this.Count < this._TSado.Count) ? this.Count : this._TSado.Count - 1].v;
|
||||
var result = (TBar.t, _ado);
|
||||
base.Add(result, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ADO: Chaikin Accumulation/Distribution Oscillator
|
||||
ADO measures the momentum of ADL using the difference between slow (10-day) EMA(ADL)
|
||||
and fast (3-day) EMA(ADL):
|
||||
|
||||
Chaikin A/D Oscillator = (3-day EMA of ADL) - (10-day EMA of ADL)
|
||||
|
||||
Sources:
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:chaikin_oscillator
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ADOSC_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly ADL_Series _TSadl;
|
||||
|
||||
private readonly EMA_Series _TSslow;
|
||||
private readonly EMA_Series _TSfast;
|
||||
private readonly SUB_Series _TSado;
|
||||
|
||||
public ADOSC_Series(TBars source, bool useNaN = false) : base(source, period: 0, useNaN)
|
||||
{
|
||||
_TSadl = new(source: source, useNaN: false);
|
||||
_TSslow = new(source: _TSadl, period: 10, useNaN: false);
|
||||
_TSfast = new(source: _TSadl, period: 3, useNaN: false);
|
||||
_TSado = new(_TSfast, _TSslow);
|
||||
|
||||
if (source.Count > 0)
|
||||
{ base.Add(_TSado); }
|
||||
Console.WriteLine(base.Count);
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update)
|
||||
{ _TSadl.Add(TBar, true); }
|
||||
|
||||
double _ado = this._TSado[(this.Count < this._TSado.Count) ? this.Count : this._TSado.Count - 1].v;
|
||||
var result = (TBar.t, _ado);
|
||||
base.Add(result, update);
|
||||
}
|
||||
}
|
||||
@@ -1,63 +1,63 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ATRP: Average True Range Percent
|
||||
Average True Range Percent is (ATR/Close Price)*100.
|
||||
This normalizes so it can be compared to other stocks.
|
||||
|
||||
Sources:
|
||||
https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/atrp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ATRP_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private double _lastema, _lastlastema, _lastcm1;
|
||||
private double _cm1 = double.NaN;
|
||||
|
||||
public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 1.0 / (double)(this._p);
|
||||
this._k1m = 1.0 - this._k;
|
||||
this._lastema = this._lastlastema = double.NaN;
|
||||
if (_bars.Count > 0) { base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update) {
|
||||
this._lastema = this._lastlastema;
|
||||
this._cm1 = this._lastcm1;
|
||||
}
|
||||
|
||||
if (_cm1 is double.NaN) { _cm1 = TBar.c; }
|
||||
double d1 = Math.Abs(TBar.h - TBar.l);
|
||||
double d2 = Math.Abs(_cm1 - TBar.h);
|
||||
double d3 = Math.Abs(_cm1 - TBar.l);
|
||||
(DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); //TR value for RMA below
|
||||
_lastcm1 = _cm1;
|
||||
_cm1 = TBar.c;
|
||||
|
||||
double _ema = 0;
|
||||
if (this.Count < this._p)
|
||||
{
|
||||
if (update) { _buffer[_buffer.Count - 1] = d.v; }
|
||||
else { _buffer.Add(d.v); }
|
||||
if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
|
||||
for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
|
||||
_ema /= this._buffer.Count;
|
||||
}
|
||||
else { _ema = (d.v * _k) + (_lastema * _k1m); }
|
||||
|
||||
this._lastlastema = this._lastema;
|
||||
this._lastema = _ema;
|
||||
|
||||
double _atrp = 100 * (_ema / TBar.c);
|
||||
|
||||
var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ATRP: Average True Range Percent
|
||||
Average True Range Percent is (ATR/Close Price)*100.
|
||||
This normalizes so it can be compared to other stocks.
|
||||
|
||||
Sources:
|
||||
https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/atrp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ATRP_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private double _lastema, _lastlastema, _lastcm1;
|
||||
private double _cm1 = double.NaN;
|
||||
|
||||
public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 1.0 / (double)(this._p);
|
||||
this._k1m = 1.0 - this._k;
|
||||
this._lastema = this._lastlastema = double.NaN;
|
||||
if (_bars.Count > 0) { base.Add(_bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update) {
|
||||
this._lastema = this._lastlastema;
|
||||
this._cm1 = this._lastcm1;
|
||||
}
|
||||
|
||||
if (_cm1 is double.NaN) { _cm1 = TBar.c; }
|
||||
double d1 = Math.Abs(TBar.h - TBar.l);
|
||||
double d2 = Math.Abs(_cm1 - TBar.h);
|
||||
double d3 = Math.Abs(_cm1 - TBar.l);
|
||||
(DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); //TR value for RMA below
|
||||
_lastcm1 = _cm1;
|
||||
_cm1 = TBar.c;
|
||||
|
||||
double _ema = 0;
|
||||
if (this.Count < this._p)
|
||||
{
|
||||
if (update) { _buffer[_buffer.Count - 1] = d.v; }
|
||||
else { _buffer.Add(d.v); }
|
||||
if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
|
||||
for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
|
||||
_ema /= this._buffer.Count;
|
||||
}
|
||||
else { _ema = (d.v * _k) + (_lastema * _k1m); }
|
||||
|
||||
this._lastlastema = this._lastema;
|
||||
this._lastema = _ema;
|
||||
|
||||
double _atrp = 100 * (_ema / TBar.c);
|
||||
|
||||
var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
}
|
||||
@@ -1,63 +1,63 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ATR: wildeR Moving Average
|
||||
The average true range (ATR) is a price volatility indicator
|
||||
showing the average price variation of assets within a given time period.
|
||||
|
||||
Sources:
|
||||
https://en.wikipedia.org/wiki/Average_true_range
|
||||
https://www.tradingview.com/wiki/Average_True_Range_(ATR)
|
||||
https://www.investopedia.com/terms/a/atr.asp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ATR_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private double _lastema, _lastlastema, _lastcm1;
|
||||
private double _cm1 = double.NaN;
|
||||
|
||||
public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 1.0 / (double)(this._p);
|
||||
this._k1m = 1.0 - this._k;
|
||||
this._lastema = this._lastlastema = double.NaN;
|
||||
if (this._bars.Count > 0) { base.Add(this._bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update) {
|
||||
this._lastema = this._lastlastema;
|
||||
this._cm1 = this._lastcm1;
|
||||
}
|
||||
|
||||
if (this._cm1 is double.NaN) { this._cm1 = TBar.c; }
|
||||
double d1 = Math.Abs(TBar.h - TBar.l);
|
||||
double d2 = Math.Abs(_cm1 - TBar.h);
|
||||
double d3 = Math.Abs(_cm1 - TBar.l);
|
||||
(DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); //TR value for RMA below
|
||||
_lastcm1 = _cm1;
|
||||
_cm1 = TBar.c;
|
||||
|
||||
double _ema = 0;
|
||||
if (this.Count < this._p)
|
||||
{
|
||||
if (update) { _buffer[_buffer.Count - 1] = d.v; }
|
||||
else { _buffer.Add(d.v); }
|
||||
if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
|
||||
for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
|
||||
_ema /= this._buffer.Count;
|
||||
}
|
||||
else { _ema = (d.v * _k) + (_lastema * _k1m); }
|
||||
|
||||
this._lastlastema = this._lastema;
|
||||
this._lastema = _ema;
|
||||
|
||||
var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
ATR: wildeR Moving Average
|
||||
The average true range (ATR) is a price volatility indicator
|
||||
showing the average price variation of assets within a given time period.
|
||||
|
||||
Sources:
|
||||
https://en.wikipedia.org/wiki/Average_true_range
|
||||
https://www.tradingview.com/wiki/Average_True_Range_(ATR)
|
||||
https://www.investopedia.com/terms/a/atr.asp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ATR_Series : Single_TBars_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly double _k, _k1m;
|
||||
private double _lastema, _lastlastema, _lastcm1;
|
||||
private double _cm1 = double.NaN;
|
||||
|
||||
public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
|
||||
{
|
||||
this._k = 1.0 / (double)(this._p);
|
||||
this._k1m = 1.0 - this._k;
|
||||
this._lastema = this._lastlastema = double.NaN;
|
||||
if (this._bars.Count > 0) { base.Add(this._bars); }
|
||||
}
|
||||
|
||||
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
|
||||
{
|
||||
if (update) {
|
||||
this._lastema = this._lastlastema;
|
||||
this._cm1 = this._lastcm1;
|
||||
}
|
||||
|
||||
if (this._cm1 is double.NaN) { this._cm1 = TBar.c; }
|
||||
double d1 = Math.Abs(TBar.h - TBar.l);
|
||||
double d2 = Math.Abs(_cm1 - TBar.h);
|
||||
double d3 = Math.Abs(_cm1 - TBar.l);
|
||||
(DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); //TR value for RMA below
|
||||
_lastcm1 = _cm1;
|
||||
_cm1 = TBar.c;
|
||||
|
||||
double _ema = 0;
|
||||
if (this.Count < this._p)
|
||||
{
|
||||
if (update) { _buffer[_buffer.Count - 1] = d.v; }
|
||||
else { _buffer.Add(d.v); }
|
||||
if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
|
||||
for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
|
||||
_ema /= this._buffer.Count;
|
||||
}
|
||||
else { _ema = (d.v * _k) + (_lastema * _k1m); }
|
||||
|
||||
this._lastlastema = this._lastema;
|
||||
this._lastema = _ema;
|
||||
|
||||
var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
|
||||
base.Add(ret, update);
|
||||
}
|
||||
}
|
||||
@@ -1,73 +1,73 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
BBANDS: Bollinger Bands®
|
||||
Price channels created by John Bollinger, depict volatility as standard deviation boundary
|
||||
line range from a moving average of price. The bands automatically widen when volatility
|
||||
increases and contract when volatility decreases. Their dynamic nature allows them to be
|
||||
used on different securities with the standard settings.
|
||||
|
||||
Mid Band = simple moving average (SMA)
|
||||
Upper Band = SMA + (standard deviation of price x multiplier)
|
||||
Lower Band = SMA - (standard deviation of price x multiplier)
|
||||
Bandwidth = Width of the channel: (Upper-Lower)/SMA
|
||||
%B = The location of the data point within the channel: (Price-Lower)/(Upper/Lower)
|
||||
Z-Score = number of standard deviations of the data point from SMA
|
||||
|
||||
Sources:
|
||||
https://www.investopedia.com/terms/b/bollingerbands.asp
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:bollinger_bands
|
||||
|
||||
Note:
|
||||
Bollinger Bands® is a registered trademark of John A. Bollinger.
|
||||
|
||||
</summary> */
|
||||
|
||||
public class BBANDS_Series : Single_TSeries_Indicator
|
||||
{
|
||||
public SMA_Series Mid { get; }
|
||||
public ADD_Series Upper { get; }
|
||||
public SUB_Series Lower { get; }
|
||||
public DIV_Series PercentB { get; }
|
||||
public DIV_Series Bandwidth { get; }
|
||||
public DIV_Series Zscore { get; }
|
||||
|
||||
private readonly SDEV_Series _sdev;
|
||||
private readonly MUL_Series _mulsdev;
|
||||
private readonly SUB_Series _pbdnd;
|
||||
private readonly SUB_Series _pbdvr;
|
||||
private readonly SUB_Series _zdnd;
|
||||
|
||||
public BBANDS_Series(TSeries source, int period = 26, double multiplier = 2.0, bool useNaN = false)
|
||||
: base(source, period: 0, useNaN)
|
||||
{
|
||||
this.Mid = new(source: source, period: period, useNaN: useNaN);
|
||||
|
||||
_sdev = new(source, period, useNaN: useNaN);
|
||||
_mulsdev = new(_sdev, multiplier);
|
||||
this.Upper = new(Mid, _mulsdev);
|
||||
this.Lower = new(Mid, _mulsdev);
|
||||
|
||||
_pbdnd = new(source, Lower);
|
||||
_pbdvr = new(Upper, Lower);
|
||||
|
||||
this.PercentB = new(_pbdnd, _pbdvr);
|
||||
this.Bandwidth = new(_pbdvr, Mid);
|
||||
|
||||
_zdnd = new(source, Mid);
|
||||
this.Zscore = new(_zdnd, _sdev);
|
||||
|
||||
if (source.Count > 0)
|
||||
{ base.Add(this.Bandwidth); }
|
||||
}
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
double _bbandwidth;
|
||||
if (update)
|
||||
{ _sdev.Add(TValue, true); }
|
||||
_bbandwidth = this.Bandwidth[(this.Count < this.Bandwidth.Count) ? this.Count : this.Bandwidth.Count - 1].v;
|
||||
var result = (TValue.t, _bbandwidth);
|
||||
base.Add(result, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
BBANDS: Bollinger Bands®
|
||||
Price channels created by John Bollinger, depict volatility as standard deviation boundary
|
||||
line range from a moving average of price. The bands automatically widen when volatility
|
||||
increases and contract when volatility decreases. Their dynamic nature allows them to be
|
||||
used on different securities with the standard settings.
|
||||
|
||||
Mid Band = simple moving average (SMA)
|
||||
Upper Band = SMA + (standard deviation of price x multiplier)
|
||||
Lower Band = SMA - (standard deviation of price x multiplier)
|
||||
Bandwidth = Width of the channel: (Upper-Lower)/SMA
|
||||
%B = The location of the data point within the channel: (Price-Lower)/(Upper/Lower)
|
||||
Z-Score = number of standard deviations of the data point from SMA
|
||||
|
||||
Sources:
|
||||
https://www.investopedia.com/terms/b/bollingerbands.asp
|
||||
https://school.stockcharts.com/doku.php?id=technical_indicators:bollinger_bands
|
||||
|
||||
Note:
|
||||
Bollinger Bands® is a registered trademark of John A. Bollinger.
|
||||
|
||||
</summary> */
|
||||
|
||||
public class BBANDS_Series : Single_TSeries_Indicator
|
||||
{
|
||||
public SMA_Series Mid { get; }
|
||||
public ADD_Series Upper { get; }
|
||||
public SUB_Series Lower { get; }
|
||||
public DIV_Series PercentB { get; }
|
||||
public DIV_Series Bandwidth { get; }
|
||||
public DIV_Series Zscore { get; }
|
||||
|
||||
private readonly SDEV_Series _sdev;
|
||||
private readonly MUL_Series _mulsdev;
|
||||
private readonly SUB_Series _pbdnd;
|
||||
private readonly SUB_Series _pbdvr;
|
||||
private readonly SUB_Series _zdnd;
|
||||
|
||||
public BBANDS_Series(TSeries source, int period = 26, double multiplier = 2.0, bool useNaN = false)
|
||||
: base(source, period: 0, useNaN)
|
||||
{
|
||||
this.Mid = new(source: source, period: period, useNaN: useNaN);
|
||||
|
||||
_sdev = new(source, period, useNaN: useNaN);
|
||||
_mulsdev = new(_sdev, multiplier);
|
||||
this.Upper = new(Mid, _mulsdev);
|
||||
this.Lower = new(Mid, _mulsdev);
|
||||
|
||||
_pbdnd = new(source, Lower);
|
||||
_pbdvr = new(Upper, Lower);
|
||||
|
||||
this.PercentB = new(_pbdnd, _pbdvr);
|
||||
this.Bandwidth = new(_pbdvr, Mid);
|
||||
|
||||
_zdnd = new(source, Mid);
|
||||
this.Zscore = new(_zdnd, _sdev);
|
||||
|
||||
if (source.Count > 0)
|
||||
{ base.Add(this.Bandwidth); }
|
||||
}
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
double _bbandwidth;
|
||||
if (update)
|
||||
{ _sdev.Add(TValue, true); }
|
||||
_bbandwidth = this.Bandwidth[(this.Count < this.Bandwidth.Count) ? this.Count : this.Bandwidth.Count - 1].v;
|
||||
var result = (TValue.t, _bbandwidth);
|
||||
base.Add(result, update);
|
||||
}
|
||||
}
|
||||
@@ -1,73 +1,73 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
RSI: Relative Strength Index
|
||||
Created by J. Welles Wilder, the Relative Strength Index measures strength
|
||||
of the winning/losing streak over N lookback periods on a scale of 0 to 100,
|
||||
to depict overbought and oversold conditions.
|
||||
|
||||
Sources:
|
||||
https://www.investopedia.com/terms/r/rsi.asp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class RSI_Series : Single_TSeries_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _gain = new();
|
||||
private readonly System.Collections.Generic.List<double> _loss = new();
|
||||
private double _avgGain;
|
||||
private double _avgLoss;
|
||||
private double _lastValue;
|
||||
private double _lastlastValue;
|
||||
|
||||
public RSI_Series(TSeries source, int period = 10, bool useNaN = false) : base(source, period: period, useNaN: useNaN)
|
||||
{ if (source.Count > 0) { base.Add(source); } }
|
||||
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
int i = this.Count;
|
||||
double _rsi = 0;
|
||||
if (update) { _lastValue = _lastlastValue; }
|
||||
if (i == 0) { _lastValue = TValue.v; }
|
||||
|
||||
double _gainval = (TValue.v > _lastValue) ? TValue.v - _lastValue : 0;
|
||||
if (update) { _gain[_gain.Count - 1] = _gainval; } else { _gain.Add(_gainval); }
|
||||
if (_gain.Count > this._p) { _gain.RemoveAt(0); }
|
||||
|
||||
double _lossval = (TValue.v < _lastValue) ? _lastValue - TValue.v : 0;
|
||||
if (update) { _loss[_loss.Count - 1] = _lossval; } else { _loss.Add(_lossval); }
|
||||
if (_loss.Count > this._p) { _loss.RemoveAt(0); }
|
||||
|
||||
_lastlastValue = _lastValue;
|
||||
_lastValue = TValue.v;
|
||||
|
||||
// calculate RSI
|
||||
if (i > _p)
|
||||
{
|
||||
_avgGain = ((_avgGain * (_p - 1)) + _gain[_gain.Count - 1]) / _p;
|
||||
_avgLoss = ((_avgLoss * (_p - 1)) + _loss[_loss.Count - 1]) / _p;
|
||||
if (_avgLoss > 0) {
|
||||
double rs = _avgGain / _avgLoss;
|
||||
_rsi = 100 - (100 / (1 + rs));
|
||||
}
|
||||
else { _rsi = 100; }
|
||||
}
|
||||
// initialize average gain
|
||||
else
|
||||
{
|
||||
double _sumGain = 0;
|
||||
for (int p = 0; p < _gain.Count; p++) { _sumGain += _gain[p]; }
|
||||
double _sumLoss = 0;
|
||||
for (int p = 0; p < _loss.Count; p++) { _sumLoss += _loss[p]; }
|
||||
|
||||
_avgGain = _sumGain / _gain.Count;
|
||||
_avgLoss = _sumLoss / _loss.Count;
|
||||
|
||||
_rsi = (_avgLoss > 0) ? 100 - (100 / (1 + (_avgGain / _avgLoss))) : 100;
|
||||
}
|
||||
|
||||
var result = (TValue.t, (this.Count < this._p && this._NaN) ? double.NaN : _rsi);
|
||||
base.Add(result, update);
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
|
||||
/* <summary>
|
||||
RSI: Relative Strength Index
|
||||
Created by J. Welles Wilder, the Relative Strength Index measures strength
|
||||
of the winning/losing streak over N lookback periods on a scale of 0 to 100,
|
||||
to depict overbought and oversold conditions.
|
||||
|
||||
Sources:
|
||||
https://www.investopedia.com/terms/r/rsi.asp
|
||||
|
||||
</summary> */
|
||||
|
||||
public class RSI_Series : Single_TSeries_Indicator
|
||||
{
|
||||
private readonly System.Collections.Generic.List<double> _gain = new();
|
||||
private readonly System.Collections.Generic.List<double> _loss = new();
|
||||
private double _avgGain;
|
||||
private double _avgLoss;
|
||||
private double _lastValue;
|
||||
private double _lastlastValue;
|
||||
|
||||
public RSI_Series(TSeries source, int period = 10, bool useNaN = false) : base(source, period: period, useNaN: useNaN)
|
||||
{ if (source.Count > 0) { base.Add(source); } }
|
||||
|
||||
public override void Add((System.DateTime t, double v) TValue, bool update)
|
||||
{
|
||||
int i = this.Count;
|
||||
double _rsi = 0;
|
||||
if (update) { _lastValue = _lastlastValue; }
|
||||
if (i == 0) { _lastValue = TValue.v; }
|
||||
|
||||
double _gainval = (TValue.v > _lastValue) ? TValue.v - _lastValue : 0;
|
||||
if (update) { _gain[_gain.Count - 1] = _gainval; } else { _gain.Add(_gainval); }
|
||||
if (_gain.Count > this._p) { _gain.RemoveAt(0); }
|
||||
|
||||
double _lossval = (TValue.v < _lastValue) ? _lastValue - TValue.v : 0;
|
||||
if (update) { _loss[_loss.Count - 1] = _lossval; } else { _loss.Add(_lossval); }
|
||||
if (_loss.Count > this._p) { _loss.RemoveAt(0); }
|
||||
|
||||
_lastlastValue = _lastValue;
|
||||
_lastValue = TValue.v;
|
||||
|
||||
// calculate RSI
|
||||
if (i > _p)
|
||||
{
|
||||
_avgGain = ((_avgGain * (_p - 1)) + _gain[_gain.Count - 1]) / _p;
|
||||
_avgLoss = ((_avgLoss * (_p - 1)) + _loss[_loss.Count - 1]) / _p;
|
||||
if (_avgLoss > 0) {
|
||||
double rs = _avgGain / _avgLoss;
|
||||
_rsi = 100 - (100 / (1 + rs));
|
||||
}
|
||||
else { _rsi = 100; }
|
||||
}
|
||||
// initialize average gain
|
||||
else
|
||||
{
|
||||
double _sumGain = 0;
|
||||
for (int p = 0; p < _gain.Count; p++) { _sumGain += _gain[p]; }
|
||||
double _sumLoss = 0;
|
||||
for (int p = 0; p < _loss.Count; p++) { _sumLoss += _loss[p]; }
|
||||
|
||||
_avgGain = _sumGain / _gain.Count;
|
||||
_avgLoss = _sumLoss / _loss.Count;
|
||||
|
||||
_rsi = (_avgLoss > 0) ? 100 - (100 / (1 + (_avgGain / _avgLoss))) : 100;
|
||||
}
|
||||
|
||||
var result = (TValue.t, (this.Count < this._p && this._NaN) ? double.NaN : _rsi);
|
||||
base.Add(result, update);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user