Files
QuanTAlib/lib/trends/vidya/Vidya.Validation.Tests.cs
T

86 lines
2.5 KiB
C#

using QuanTAlib;
using Xunit;
namespace Trends;
public class VidyaValidationTests
{
[Fact]
public void ValidateAgainstReference()
{
// Note: Tulip's VIDYA implementation uses Standard Deviation ratio (1992 version),
// while QuanTAlib uses Chande Momentum Oscillator (1994 version).
// Therefore, we cannot validate against Tulip.
// We validate against a simple, readable reference implementation of the CMO-based VIDYA.
var feed = new GBM();
var data = feed.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var period = 14;
// QuanTAlib
var vidya = new Vidya(period);
var qResults = new List<double>();
foreach (var item in data)
{
qResults.Add(vidya.Update(new TValue(item.Time, item.Close)).Value);
}
// Reference Implementation
var refResults = CalculateVidyaReference(data, period);
// Compare
for (int i = 0; i < data.Count; i++)
{
Assert.Equal(refResults[i], qResults[i], 1e-9);
}
}
private static List<double> CalculateVidyaReference(TBarSeries data, int period)
{
var results = new List<double>();
var prices = data.Select(x => x.Close).ToList();
double alpha = 2.0 / (period + 1);
double prevVidya = 0;
for (int i = 0; i < prices.Count; i++)
{
if (i == 0)
{
results.Add(prices[i]);
prevVidya = prices[i];
continue;
}
double sumUp = 0;
double sumDown = 0;
var changes = new List<double>();
for (int j = 1; j <= i; j++)
{
changes.Add(prices[j] - prices[j-1]);
}
var recentChanges = changes.TakeLast(period).ToList();
sumUp = recentChanges.Where(x => x > 0).Sum();
sumDown = recentChanges.Where(x => x < 0).Select(x => -x).Sum();
double sum = sumUp + sumDown;
double vi = 0;
if (sum > 0)
{
vi = Math.Abs(sumUp - sumDown) / sum;
}
double dynamicAlpha = alpha * vi;
double currentVidya = dynamicAlpha * prices[i] + (1 - dynamicAlpha) * prevVidya;
results.Add(currentVidya);
prevVidya = currentVidya;
}
return results;
}
}