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refactor structs to records, add new classes for financial calculations, implement EMA and SMA with circular buffer. Generate random financial data using GBM model. Also, test the SMA calculation with sample data.

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This commit is contained in:
Miha Kralj
2024-07-28 21:26:44 -07:00
parent ef534393db
commit 3455baaf6c
95 changed files with 8661 additions and 7012 deletions
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Calculations/_Updated/DWMA_Series.cs
+109 -88
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@@ -11,112 +11,133 @@ DWMA: Double Weighted Moving Average
</summary> */
public class DWMA_Series : TSeries {
private readonly List<double> _buffer = new();
private List<double> _weights;
protected readonly int _period;
protected readonly bool _NaN;
protected readonly TSeries _data;
protected int _len;
public class DWMA_Series : TSeries
{
private readonly List<double> _buffer = new();
private List<double> _weights;
protected readonly int _period;
protected readonly bool _NaN;
protected readonly TSeries _data;
protected int _len;
//core constructors
public DWMA_Series(int period, bool useNaN) {
_period = period;
_NaN = useNaN;
Name = $"DWMA({period})";
_len = 0;
_weights = CalculateWeights(_period);
}
//core constructors
public DWMA_Series(int period, bool useNaN)
{
_period = period;
_NaN = useNaN;
Name = $"DWMA({period})";
_len = 0;
_weights = CalculateWeights(_period);
}
public DWMA_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
_data = source;
Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
_data.Pub += Sub;
Add(_data);
}
public DWMA_Series(TSeries source, int period, bool useNaN) : this(period, useNaN)
{
_data = source;
Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
_data.Pub += Sub;
Add(_data);
}
public DWMA_Series() : this(0, false) {
}
public DWMA_Series() : this(0, false)
{
}
public DWMA_Series(int period) : this(period, false) {
}
public DWMA_Series(int period) : this(period, false)
{
}
public DWMA_Series(TBars source) : this(source.Close, 0, false) {
}
public DWMA_Series(TBars source) : this(source.Close, 0, false)
{
}
public DWMA_Series(TBars source, int period) : this(source.Close, period, false) {
}
public DWMA_Series(TBars source, int period) : this(source.Close, period, false)
{
}
public DWMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) {
}
public DWMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN)
{
}
public DWMA_Series(TSeries source, int period) : this(source, period, false) {
}
public DWMA_Series(TSeries source, int period) : this(source, period, false)
{
}
//////////////////
// core Add() algo
public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
BufferTrim(_buffer, TValue.v, _period, update);
if (_period == 0) {
_len++;
_weights = CalculateWeights(_len);
}
//////////////////
// core Add() algo
public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false)
{
BufferTrim(_buffer, TValue.v, _period, update);
if (_period == 0)
{
_len++;
_weights = CalculateWeights(_len);
}
double _dwma = 0, _wsum = 0;
var bufferCount = _buffer.Count;
double _dwma = 0, _wsum = 0;
var bufferCount = _buffer.Count;
var lockObj = new object();
Parallel.For(0, bufferCount, i =>
{
var temp = _buffer[i] * _weights[i];
lock (lockObj) {
_dwma += temp;
_wsum += _weights[i];
}
});
_dwma /= _wsum;
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _dwma);
return base.Add(res, update);
}
var lockObj = new object();
Parallel.For(0, bufferCount, i =>
{
var temp = _buffer[i] * _weights[i];
lock (lockObj)
{
_dwma += temp;
_wsum += _weights[i];
}
});
_dwma /= _wsum;
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _dwma);
return base.Add(res, update);
}
public override (DateTime t, double v) Add(TSeries data) {
if (data == null) {
return (DateTime.Today, double.NaN);
}
public override (DateTime t, double v) Add(TSeries data)
{
if (data == null)
{
return (DateTime.Today, double.NaN);
}
foreach (var item in data) {
Add(item, false);
}
foreach (var item in data)
{
Add(item, false);
}
return _data.Last;
}
return _data.Last;
}
public (DateTime t, double v) Add(bool update) {
return Add(_data.Last, update);
}
public (DateTime t, double v) Add(bool update)
{
return Add(_data.Last, update);
}
public (DateTime t, double v) Add() {
return Add(_data.Last, false);
}
public (DateTime t, double v) Add()
{
return Add(_data.Last, false);
}
private new void Sub(object source, TSeriesEventArgs e) {
Add(_data.Last, e.update);
}
private new void Sub(object source, TSeriesEventArgs e)
{
Add(_data.Last, e.update);
}
//calculating weights
private static List<double> CalculateWeights(int period) {
var weights = new List<double>(period);
for (var i = 0; i < period; i++) {
weights.Add((i + 1) * (i + 1));
}
//calculating weights
private static List<double> CalculateWeights(int period)
{
var weights = new List<double>(period);
for (var i = 0; i < period; i++)
{
weights.Add((i + 1) * (i + 1));
}
return weights;
}
return weights;
}
//reset calculation
public override void Reset() {
_len = 0;
_buffer.Clear();
_weights = CalculateWeights(_period);
}
//reset calculation
public override void Reset()
{
_len = 0;
_buffer.Clear();
_weights = CalculateWeights(_period);
}
}