// Stochastic RSI
public static void CalculateStochasticRSI(out string key, StockPoints data, Dictionary<DateTime, Dictionary<string, double>> indicators, int period, out int offset, bool leverage = true)
{
key = string.Format("StocRSI({0})", period.ToString("00"));
ExponentialMovingAverage gains = new ExponentialMovingAverage(period);
ExponentialMovingAverage losses = new ExponentialMovingAverage(period);
offset = period * 2;
double rsi;
double stochRSI;
double highestRSI;
double lowestRSI;
Queue<double> rsiQueue = new Queue<double>();
StockPoint previousPoint = data[0];
int i = 0;
foreach (StockPoint point in data.Skip(1))
{
if (previousPoint.Close > point.Close)
{
losses.AddValue(previousPoint.Close - point.Close);
gains.AddValue(0);
}
else if (previousPoint.Close < point.Close)
{
gains.AddValue(point.Close - previousPoint.Close);
losses.AddValue(0);
}
if (i < period - 1)
{
i++;
}
else
{
rsi = 100 - (100 / (1 + (gains.MovingAverage / losses.MovingAverage)));
rsiQueue.Enqueue(rsi);
if (rsiQueue.Count > period)
{
rsiQueue.Dequeue();
}
if (rsiQueue.Count == period)
{
highestRSI = rsiQueue.Max();
lowestRSI = rsiQueue.Min();
stochRSI = (rsi - lowestRSI) / (highestRSI - lowestRSI) * (leverage ? 100 : 1);
AddValue(point.PointDateTime, key, stochRSI, indicators);
}
}
previousPoint = point;
}
}
// RSI
/// <summary>
/// Calculates the Relative Strength Index and fills indicators with the data needed to graph it.
/// </summary>
/// <param name="key">Name of the set to put in the graph key</param>
/// <param name="data">StockPoints to calculate the Relative Strength Index with.</param>
/// <param name="indicators">The mfvvalues needed to graph the RSI.</param>
/// <param name="period">The number of days gained/lost to consider.</param>
/// <param name="offset">Where to start the graph.</param>
public static void CalculateRsi(out string key, StockPoints data, Dictionary<DateTime, Dictionary<string, double>> indicators, int period, out int offset)
{
key = "RSI(" + period.ToString("00") + ")";
ExponentialMovingAverage gains = new ExponentialMovingAverage(period);
ExponentialMovingAverage losses = new ExponentialMovingAverage(period);
offset = period;
int i = 0;
StockPoint previousPoint = data[0];
foreach (StockPoint point in data.Skip(1))
{
if (previousPoint.Close > point.Close)
{
losses.AddValue(previousPoint.Close - point.Close);
gains.AddValue(0);
}
else if (previousPoint.Close < point.Close)
{
gains.AddValue(point.Close - previousPoint.Close);
losses.AddValue(0);
}
if (i < period - 1)
{
i++;
}
else
{
double rsi = 100 - (100 / (1 + (gains.MovingAverage / losses.MovingAverage)));
AddValue(point.PointDateTime, key, rsi, indicators);
}
previousPoint = point;
}
}
// Full Stochastic
/// <summary>
/// Calculates the Full Stochastic Oscillator and fills indicators with the data needed to graph it.
/// </summary>
/// <param name="key">Name of the first set to put in the graph key</param>
/// <param name="key2">Name of the second set to put in the graph key</param>
/// <param name="data">StockPoints to calculate the Full Stochastic with.</param>
/// <param name="indicators">The mfvvalues needed to graph the Full Stochastic.</param>
/// <param name="period1">The number of period to calculate Fast Stochastic.</param>
/// <param name="period2">The number of period to calculate SMA of Fast Stochastic.</param>
/// <param name="period3">The number of period to calculate SMA of calculated SMA of Fast Stochastic.</param>
/// <param name="offset">Where to start the graph.</param>
public static void CalculateStochastic(out string key, out string key2, StockPoints data, Dictionary<DateTime, Dictionary<string, double>> indicators, int period1, int period2, int period3, out int offset)
{
key = string.Format("Full STO %K({0}:{1})", period1.ToString("00"), period2.ToString("00"));
key2 = string.Format("Full STO %D({0})", period3.ToString("00"));
offset = period1 - 1;
SimpleMovingAverage ksma = new SimpleMovingAverage(period2);
SimpleMovingAverage dsma = new SimpleMovingAverage(period3);
// lowest among the lowest for the chosen period
double lowestLow;
// highest among the highest for the chosen period
double highestHigh;
// Lowest Low = lowest low for the look-back period
// Highest High = highest high for the look-back period
// fastk = (Current Close - Lowest Low)/(Highest High - Lowest Low) * 100
double fastk;
// fullk smoothed with X-period SMA
double fullk;
// X-period SMA of Full fullk
double fulld;
int i = 0;
// loop through each stockpoint skipping the
foreach (StockPoint point in data)
{
lowestLow = data.Skip(data.IndexOf(point) - (period1 - 1)).Take(period1).OrderBy(sp => sp.Low).FirstOrDefault().Low;
highestHigh = data.Skip(data.IndexOf(point) - (period1 - 1)).Take(period1).OrderByDescending(sp => sp.High).FirstOrDefault().High;
fastk = (point.Close - lowestLow) / (highestHigh - lowestLow == 0 ? 1 : highestHigh - lowestLow) * 100;
ksma.AddValue(fastk);
fullk = ksma.MovingAverage();
dsma.AddValue(fullk);
fulld = dsma.MovingAverage();
if (i < period1 - 1)
{
i++;
}
else
{
AddValue(point.PointDateTime, key, fullk, indicators);
AddValue(point.PointDateTime, key2, fulld, indicators);
}
}
}
// Money Flow Index
public static void CalculateMFI(out string key, StockPoints data, Dictionary<DateTime, Dictionary<string, double>> indicators, int period, out int offset)
{
key = string.Format("MFI({0})", period.ToString("00"));
offset = period;
// Typical Price = (High + Low + Close)/3
double typicalPrice;
// Raw Money Flow = Typical Price x Volume
double rawMoneyFlow;
// Money Flow Ratio = (x-period Positive Money Flow)/(x-period Negative Money Flow)
double moneyFlowRatio;
// Money Flow Index = 100 - 100/(1 + Money Flow Ratio)
double moneyFlowIndex;
double positiveMoneyFlow = 0D;
double negativeMoneyFLow = 0D;
Queue<double> moneyFlow = new Queue<double>();
double previousTipycalPrice = (data[0].Low + data[0].High + data[0].Close) / 3;
int i = 0;
foreach (StockPoint point in data.Skip(1))
{
typicalPrice = (point.Low + point.High + point.Close) / 3;
rawMoneyFlow = typicalPrice * point.Volume;
moneyFlow.Enqueue(rawMoneyFlow * (typicalPrice >= previousTipycalPrice ? 1 : -1));
if(moneyFlow.Count > period)
{
moneyFlow.Dequeue();
}
if (i < period - 1)
{
i++;
}
else
{
positiveMoneyFlow = moneyFlow.Where(v => v >= 0).Sum();
negativeMoneyFLow = Math.Abs(moneyFlow.Where(v => v < 0).Sum());
moneyFlowRatio = positiveMoneyFlow / negativeMoneyFLow;
moneyFlowIndex = 100 - (100 / (1 + moneyFlowRatio));
AddValue(point.PointDateTime, key, moneyFlowIndex, indicators);
}
previousTipycalPrice = typicalPrice;
}
}