@coleman
To compute the Stochastic Oscillator using C#, you can follow these steps:
Here's an example C# code snippet to compute the Stochastic Oscillator:
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using System;
using System.Collections.Generic;
using System.Linq;
class StochasticOscillator
{
static void Main()
{
List<double> prices = new List<double> { 100, 110, 90, 120, 130, 140, 150, 160, 150, 140, 130, 120, 110, 100 };
int period = 14;
int smoothingPeriod = 3;
List<double> kValues = new List<double>();
List<double> dValues = new List<double>();
for (int i = period; i < prices.Count; i++)
{
double close = prices[i];
List<double> periodPrices = prices.GetRange(i - period, period);
double lowestLow = periodPrices.Min();
double highestHigh = periodPrices.Max();
double k = 100 * ((close - lowestLow) / (highestHigh - lowestLow));
kValues.Add(k);
if (kValues.Count >= smoothingPeriod)
{
double d = kValues.Skip(kValues.Count - smoothingPeriod).Average();
dValues.Add(d);
}
}
Console.WriteLine("Stochastic Oscillator Values:");
for (int i = 0; i < kValues.Count; i++)
{
Console.WriteLine($"%K: {kValues[i]}, %D: {dValues[i]}");
}
}
}
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In this code snippet, we calculate the %K and %D lines for a sample price data series. We iterate over the prices list, calculate the %K value, and then compute the %D value using a simple moving average of the %K values. This example provides a basic implementation of the Stochastic Oscillator computation in C#. You can customize it further based on your requirements and the specific data you are working with.
@coleman
The provided code snippet can be used as a foundation for computing the Stochastic Oscillator in C#. It uses a simple moving average to calculate the %D value. Additionally, you can enhance the code by adding error handling when dealing with edge cases or invalid input data.
Here are some enhancements and considerations you can incorporate into the code:
By incorporating these enhancements and considering additional factors, you can create a more robust and efficient Stochastic Oscillator calculation in C#. Feel free to customize the code further based on your specific requirements and data analysis needs.