I'm trying to write an indicator script that will plot the MACD with 2 lines in a practice trading tool.
At the moment, I'm following the formula which is using the EMA formula to calculate it.
I'm able to plot the chart. But somehow my indicator result does not have the exact same result as the one on meta trader 4 or on trading view. The indicator result on these apps is exactly the same.
I think I have missed something when I try to convert from the formula to actual code. Please help me fix it. Thank you.
Here is the part that will calculate the EMA.
/// ==================================================================
/// ======================== calculations ============================
/// ==================================================================
public void Calculate()
{
for (int i = 0; i < Bars.Length; i++){
if (i >= SlowEMA) {
MACD[i] = CalculateEMA(FastEMA, i) - CalculateEMA(SlowEMA, i);
Signal[i] = CalculateEMA_MACD(MACD, SignalEMA, i);
Histogram[i] = MACD[i] - Signal[i];
}
}
}
private double CalculateEMA(int Period, int index)
{
var currentValue = 0d;
var currentEMA = 0d;
var yesterdayEMA = 0d;
var smooth = 2d;
var multiplier = smooth / (1 + Period);
for (int i = 0; i < Period; i++){
currentValue = GetPrice(index + i - Period);
currentEMA = (currentValue * multiplier) + (yesterdayEMA * (1 - multiplier));
yesterdayEMA = currentEMA;
};
return yesterdayEMA;
}
private double CalculateEMA_MACD(double[] MACD, int Period, int index)
{
var currentValue = 0d;
var currentEMA = 0d;
var yesterdayEMA = 0d;
var smooth = 2d;
var multiplier = smooth / (1 + Period);
for (int i = 0; i < Period; i++){
currentValue = MACD[index + i - Period];
currentEMA = (currentValue * multiplier) + (yesterdayEMA * (1 - multiplier));
yesterdayEMA = currentEMA;
};
return yesterdayEMA;
}
private double GetPrice(int index)
{
Bar bar = Bars[index];
switch (Source)
{
case Sources.Close:
return bar.Close;
case Sources.Open:
return bar.Open;
case Sources.High:
return bar.High;
case Sources.Low:
return bar.Low;
case Sources.MedianPrice:
return (bar.High + bar.Low) / 2;
case Sources.TypicalPrice:
return (bar.High + bar.Low + bar.Close) / 3;
case Sources.WeightedClose:
return (bar.High + bar.Low + bar.Close + bar.Close) / 4;
}
throw new NotSupportedException("Unsupported price source type: " + Source);
}
It looks like your logic for EMA calculation is wrong. Based on your code, yesterdayEMA is always 0 and therefore right part of EMA equation is also 0.
private double CalculateEMA(int Period, int index)
{
...
var yesterdayEMA = 0D;
...
currentEMA = (currentValue * multiplier) + (yesterdayEMA * (1 - multiplier));
currentEMA = (currentValue * multiplier) + 0
...
}
You need to store yesterdayEMA outside of CalculateEMA and pass it as parameter for recursive calculation.
0 comes true in the first cycle, but yesterday EMA = current EMA; It starts to take values different from 0 in the next cycle due to its equality.
Related
I have been running this syntax with one variable successfully, but now I am trying to change it to a foeach() loop and take a range of values and show the results as a message box. My issue with the syntax is that ecll always retains the value of the first number passed, and the calculation is never updated for each subsequent number in the array.
Where did I err that is preventing this from being updated for each subsequent number in the array?
private void btnGetData_Click(object sender, EventArgs e)
{
int start = 2;
int end = 10;
int[] nums = Enumerable.Range(start, end - start).ToArray();
foreach (int n in nums)
{
float tp_x = 0, tp_y = 0;
SAP = new List<PointF>();
float fbw = m_pd.bl[m_pd.bl.Count - 1].m_Width;
float Location1_X = tp_x + fbw;
float Location1_Y = tp_y;
SAP.Add(new PointF(Location1_X, Location1_Y));
float iBH = gbh(m_pd.bl.Count - 1);
float lbw = m_pd.bl[0].m_Width;
float Location2_X = tp_x + lbw;
float Location2_Y = tp_y + (iBH) + 1.5f;
PointF rip = new PointF();
if (!Getrip(ftp, rhep, ref rip))
{
SAP = null;
return;
}
for (int iRowIndex = saii; iRowIndex < m_pd.pp.Count; iRowIndex++)
{
float Xvalue = m_pd.pp[iRowIndex].X;
float Yvalue = m_pd.pp[iRowIndex].Y;
SAP.Add(new PointF(Xvalue, Yvalue));
if (Yvalue == LeftIntersectionPoint.Y)
{
pp.X = Xvalue;
pp.Y = Yvalue;
continue;
}
if (Xvalue >= rip.X)
{
Xvalue = rip.X;
SAP[SAP.Count - 1] = new PointF(rip.X, rip.Y);
}
if (Xvalue == rip.X)
{
break;
}
pp.X = Xvalue;
pp.Y = Yvalue;
}
double ecll = Getll(Location1_X, Location1_Y, rip.X, rip.Y);
Messagebox.Show(Convert.ToString(ec11));
txtLength.Text = ll.ToString("0.00");
}
}
I feel like this is more of a comment based on what's going on here, but I kind of need the code section to explain this better I believe.
Let's simplify away from your points, widths, etc. I think we can all agree that n is never used within your function, so let's do a similar example:
So I have a function I wrote that adds 1 to 1
var newNum = 1 + 1;
It does what is expected, sets newNum to 2, but let's say I wanted to enhance it so that it adds 1 to the numbers in nums (from your original function):
int start = 2;
int end = 10;
int[] nums = Enumerable.Range(start, end - start).ToArray();
but if I try to reuse my function outright:
foreach (int n in nums)
{
var newNum = 1 + 1;
}
Every single pass, I'm always going to have newNum set at 2 because I'm not using the variable.
what I should do is write this:
foreach (int n in nums)
{
var newNum = 1 + n;
}
so based on your 2 through 10, I should see newNum set to 3 through 11 at various iterations.
Each iteration in the 'Foreach' loop assigns a new value to 'n'.
However in the loop body, that value (n) is not used anywhere in the calculations (unless I am missing something). So, of course the result of these calculations will always be the same.
As soon as you include 'n' in some of the calclations, the result will change...
I am having trouble getting a smoothed RSI. The below picture is from freestockcharts.com. The calculation uses this code.
public static double CalculateRsi(IEnumerable<double> closePrices)
{
var prices = closePrices as double[] ?? closePrices.ToArray();
double sumGain = 0;
double sumLoss = 0;
for (int i = 1; i < prices.Length; i++)
{
var difference = prices[i] - prices[i - 1];
if (difference >= 0)
{
sumGain += difference;
}
else
{
sumLoss -= difference;
}
}
if (sumGain == 0) return 0;
if (Math.Abs(sumLoss) < Tolerance) return 100;
var relativeStrength = sumGain / sumLoss;
return 100.0 - (100.0 / (1 + relativeStrength));
}
https://stackoverflow.com/questions/...th-index-using-some-programming-language-js-c
This seems to be the pure RSI with no smoothing. How does a smoothed RSI get calculated? I have tried changing it to fit the definitions of the these two sites however the output was not correct. It was barely smoothed.
(I don't have enough rep to post links)
tc2000 -> Indicators -> RSI_and_Wilder_s_RSI (Wilder's smoothing = Previous MA value + (1/n periods * (Close - Previous MA)))
priceactionlab -> wilders-cutlers-and-harris-relative-strength-index (RS = EMA(Gain(n), n)/EMA(Loss(n), n))
Can someone actually do the calculation with some sample data?
Wilder's RSI vs RSI
In order to calculate the RSI, you need a period to calculate it with. As noted on Wikipedia, 14 is used quite often.
So the calculation steps would be as follows:
Period 1 - 13, RSI = 0
Period 14:
AverageGain = TotalGain / PeriodCount;
AverageLoss = TotalLoss / PeriodCount;
RS = AverageGain / AverageLoss;
RSI = 100 - 100 / (1 + RS);
Period 15 - to period (N):
if (Period(N)Change > 0
AverageGain(N) = ((AverageGain(N - 1) * (PeriodCount - 1)) + Period(N)Change) / PeriodCount;
else
AverageGain(N) = (AverageGain(N - 1) * (PeriodCount - 1)) / PeriodCount;
if (this.Change < 0)
AverageLoss(N) = ((AverageLoss(N - 1) * (PeriodCount - 1)) + Math.Abs(Period(N)Change)) / PeriodCount;
else
AverageLoss(N) = (AverageLoss(N - 1) * (PeriodCount - 1)) / PeriodCount;
RS = AverageGain / AverageLoss;
RSI = 100 - (100 / (1 + RS));
Thereafter, to smooth the values, you need to apply a moving average of a certain period to your RSI values. To do that, traverse your RSI values from the last index to the first and calculate your average for the current period based on the preceding x smoothing periods.
Once done, just reverse the list of values to get the expected order:
List<double> SmoothedRSI(IEnumerable<double> rsiValues, int smoothingPeriod)
{
if (rsiValues.Count() <= smoothingPeriod)
throw new Exception("Smoothing period too large or too few RSI values passed.");
List<double> results = new List<double>();
List<double> reversedRSIValues = rsiValues.Reverse().ToList();
for (int i = 1; i < reversedRSIValues.Count() - smoothingPeriod - 1; i++)
results.Add(reversedRSIValues.Subset(i, i + smoothingPeriod).Average());
return results.Reverse().ToList();
}
The Subset method is just a simple extension method as follows:
public static List<double> Subset(this List<double> values, int start, int end)
{
List<double> results = new List<double>();
for (int i = start; i <= end; i++)
results.Add(values[i]);
return results;
}
Disclaimer, I did not test the code, but it should give you an idea of how the smoothing is applied.
You can't get accurate values without buffers / global variables to store data.
This is a smoothed indicator, meaning it doesn't only use 14 bars but ALL THE BARS:
Here's a step by step article with working and verified source codes generating exactly the same values if prices and number of available bars are the same, of course (you only need to load the price data from your source):
Tested and verified:
using System;
using System.Data;
using System.Globalization;
namespace YourNameSpace
{
class PriceEngine
{
public static DataTable data;
public static double[] positiveChanges;
public static double[] negativeChanges;
public static double[] averageGain;
public static double[] averageLoss;
public static double[] rsi;
public static double CalculateDifference(double current_price, double previous_price)
{
return current_price - previous_price;
}
public static double CalculatePositiveChange(double difference)
{
return difference > 0 ? difference : 0;
}
public static double CalculateNegativeChange(double difference)
{
return difference < 0 ? difference * -1 : 0;
}
public static void CalculateRSI(int rsi_period, int price_index = 5)
{
for(int i = 0; i < PriceEngine.data.Rows.Count; i++)
{
double current_difference = 0.0;
if (i > 0)
{
double previous_close = Convert.ToDouble(PriceEngine.data.Rows[i-1].Field<string>(price_index));
double current_close = Convert.ToDouble(PriceEngine.data.Rows[i].Field<string>(price_index));
current_difference = CalculateDifference(current_close, previous_close);
}
PriceEngine.positiveChanges[i] = CalculatePositiveChange(current_difference);
PriceEngine.negativeChanges[i] = CalculateNegativeChange(current_difference);
if(i == Math.Max(1,rsi_period))
{
double gain_sum = 0.0;
double loss_sum = 0.0;
for(int x = Math.Max(1,rsi_period); x > 0; x--)
{
gain_sum += PriceEngine.positiveChanges[x];
loss_sum += PriceEngine.negativeChanges[x];
}
PriceEngine.averageGain[i] = gain_sum / Math.Max(1,rsi_period);
PriceEngine.averageLoss[i] = loss_sum / Math.Max(1,rsi_period);
}else if (i > Math.Max(1,rsi_period))
{
PriceEngine.averageGain[i] = ( PriceEngine.averageGain[i-1]*(rsi_period-1) + PriceEngine.positiveChanges[i]) / Math.Max(1, rsi_period);
PriceEngine.averageLoss[i] = ( PriceEngine.averageLoss[i-1]*(rsi_period-1) + PriceEngine.negativeChanges[i]) / Math.Max(1, rsi_period);
PriceEngine.rsi[i] = PriceEngine.averageLoss[i] == 0 ? 100 : PriceEngine.averageGain[i] == 0 ? 0 : Math.Round(100 - (100 / (1 + PriceEngine.averageGain[i] / PriceEngine.averageLoss[i])), 5);
}
}
}
public static void Launch()
{
PriceEngine.data = new DataTable();
//load {date, time, open, high, low, close} values in PriceEngine.data (6th column (index #5) = close price) here
positiveChanges = new double[PriceEngine.data.Rows.Count];
negativeChanges = new double[PriceEngine.data.Rows.Count];
averageGain = new double[PriceEngine.data.Rows.Count];
averageLoss = new double[PriceEngine.data.Rows.Count];
rsi = new double[PriceEngine.data.Rows.Count];
CalculateRSI(14);
}
}
}
For detailed step-by-step instructions, I wrote a lengthy article, you can check it here: https://turmanauli.medium.com/a-step-by-step-guide-for-calculating-reliable-rsi-values-programmatically-a6a604a06b77
P.S. functions only work for simple indicators (Simple Moving Average), even Exponential Moving Average, Average True Range absolutely require global variables to store previous values.
how to find the min and max for quadratic equation using c# ??
f(x,y) = x^2 + y^2 + 25 * (sin(x)^2 + sin(y)^2) ,where (x,y) from (-2Pi, 2Pi) ??
in the manual solving I got min is = 0 , max = 8Pi^2 = 78.957 .
I tried to write the code based on liner quadratic code but something goes totally wrong
this code give the min = -4.?? and the max = 96 could you help to know where is my mistake please ??
I uploaded the code to dropbox if anyone can have look : https://www.dropbox.com/s/p7y6krk2gk29i9e/Program.cs
double[] X, Y, Result; // Range array and result array.
private void BtnRun_Click(object sender, EventArgs e)
{
//Set any Range for the function
X = setRange(-2 * Math.PI, 2 * Math.PI, 10000);
Y = setRange(-2 * Math.PI, 2 * Math.PI, 10000);
Result = getOutput_twoVariablesFunction(X, Y);
int MaxIndex = getMaxIndex(Result);
int MinIndex = getMinIndex(Result);
TxtMin.Text = Result[MinIndex].ToString();
TxtMax.Text = Result[MaxIndex].ToString();
}
private double twoVariablesFunction(double x,double y)
{
double f;
//Set any two variables function
f = Math.Pow(x, 2) + Math.Pow(y, 2) + 25 * (Math.Pow(Math.Sin(x), 2) + Math.Pow(Math.Sin(y), 2));
return f;
}
private double[] setRange(double Start, double End, int Sample)
{
double Step = (End - Start) / Sample;
double CurrentVaue = Start;
double[] Array = new double[Sample];
for (int Index = 0; Index < Sample; Index++)
{
Array[Index] = CurrentVaue;
CurrentVaue += Step;
}
return Array;
}
private double[] getOutput_twoVariablesFunction(double[] X, double[] Y)
{
int Step = X.Length;
double[] Array = new double[Step];
for (int Index = 0; Index < X.Length ; Index++)
{
Array[Index] = twoVariablesFunction(X[Index], Y[Index]);
}
return Array;
}
private int getMaxIndex(double[] ValuesArray)
{
double M = ValuesArray.Max();
int Index = ValuesArray.ToList().IndexOf(M);
return Index;
}
private int getMinIndex(double[] ValuesArray)
{
double M = ValuesArray.Min();
int Index = ValuesArray.ToList().IndexOf(M);
return Index;
}
Do you want to compute (sin(x))^2 or sin(x^2)? In your f(x,y) formula it looks like (sin(x))^2, but in your method twoVariablesFunction like sin(x^2).
I'm looking to produce a data histogram from a given dataset. I've read about different options for constructing the histogram and I'm most interested in a method based on the work of
Shimazaki, H.; Shinomoto, S. (2007). "A method for selecting the bin
size of a time histogram"
The above method uses estimation to determine the optimal bin width and distribution, which is needed in my case because the sample data will vary in distribution and hard to determine the bin count and width in advance.
Can someone recommend a good source or a starting point for writing such a function in c# or have a close enough c# histogram code.
Many thanks.
The following is a port I wrote of the Python version of this algorithm from here. I know the API could do with some work, but this should be enough to get you started. The results of this code are identical to those produced by the Python code for the same input data.
public class HistSample
{
public static void CalculateOptimalBinWidth(double[] x)
{
double xMax = x.Max(), xMin = x.Min();
int minBins = 4, maxBins = 50;
double[] N = Enumerable.Range(minBins, maxBins - minBins)
.Select(v => (double)v).ToArray();
double[] D = N.Select(v => (xMax - xMin) / v).ToArray();
double[] C = new double[D.Length];
for (int i = 0; i < N.Length; i++)
{
double[] binIntervals = LinearSpace(xMin, xMax, (int)N[i] + 1);
double[] ki = Histogram(x, binIntervals);
ki = ki.Skip(1).Take(ki.Length - 2).ToArray();
double mean = ki.Average();
double variance = ki.Select(v => Math.Pow(v - mean, 2)).Sum() / N[i];
C[i] = (2 * mean - variance) / (Math.Pow(D[i], 2));
}
double minC = C.Min();
int index = C.Select((c, ix) => new { Value = c, Index = ix })
.Where(c => c.Value == minC).First().Index;
double optimalBinWidth = D[index];
}
public static double[] Histogram(double[] data, double[] binEdges)
{
double[] counts = new double[binEdges.Length - 1];
for (int i = 0; i < binEdges.Length - 1; i++)
{
double lower = binEdges[i], upper = binEdges[i + 1];
for (int j = 0; j < data.Length; j++)
{
if (data[j] >= lower && data[j] <= upper)
{
counts[i]++;
}
}
}
return counts;
}
public static double[] LinearSpace(double a, double b, int count)
{
double[] output = new double[count];
for (int i = 0; i < count; i++)
{
output[i] = a + ((i * (b - a)) / (count - 1));
}
return output;
}
}
Run it like this:
double[] x =
{
4.37, 3.87, 4.00, 4.03, 3.50, 4.08, 2.25, 4.70, 1.73,
4.93, 1.73, 4.62, 3.43, 4.25, 1.68, 3.92, 3.68, 3.10,
4.03, 1.77, 4.08, 1.75, 3.20, 1.85, 4.62, 1.97, 4.50,
3.92, 4.35, 2.33, 3.83, 1.88, 4.60, 1.80, 4.73, 1.77,
4.57, 1.85, 3.52, 4.00, 3.70, 3.72, 4.25, 3.58, 3.80,
3.77, 3.75, 2.50, 4.50, 4.10, 3.70, 3.80, 3.43, 4.00,
2.27, 4.40, 4.05, 4.25, 3.33, 2.00, 4.33, 2.93, 4.58,
1.90, 3.58, 3.73, 3.73, 1.82, 4.63, 3.50, 4.00, 3.67,
1.67, 4.60, 1.67, 4.00, 1.80, 4.42, 1.90, 4.63, 2.93,
3.50, 1.97, 4.28, 1.83, 4.13, 1.83, 4.65, 4.20, 3.93,
4.33, 1.83, 4.53, 2.03, 4.18, 4.43, 4.07, 4.13, 3.95,
4.10, 2.27, 4.58, 1.90, 4.50, 1.95, 4.83, 4.12
};
HistSample.CalculateOptimalBinWidth(x);
Check the Histogram function. If any data elements are unlucky to be equal to a bin boundary (other than the first or last bin), they will be counted in both consecutive bins.
The code needs to check (lower <= data[j] && data[j] < upper) and handle the case that all elements equal to xMax go into the last bin.
A small update to nick_w answer.
If you actually need the bins after. Plus optimized the double loop in histogram function away, plus got rid of linspace function.
/// <summary>
/// Calculate the optimal bins for the given data
/// </summary>
/// <param name="x">The data you have</param>
/// <param name="xMin">The minimum element</param>
/// <param name="optimalBinWidth">The width between each bin</param>
/// <returns>The bins</returns>
public static int[] CalculateOptimalBinWidth(List<double> x, out double xMin, out double optimalBinWidth)
{
var xMax = x.Max();
xMin = x.Min();
optimalBinWidth = 0;
const int MIN_BINS = 1;
const int MAX_BINS = 20;
int[] minKi = null;
var minOffset = double.MaxValue;
foreach (var n in Enumerable.Range(MIN_BINS, MAX_BINS - MIN_BINS).Select(v => v*5))
{
var d = (xMax - xMin)/n;
var ki = Histogram(x, n, xMin, d);
var ki2 = ki.Skip(1).Take(ki.Length - 2).ToArray();
var mean = ki2.Average();
var variance = ki2.Select(v => Math.Pow(v - mean, 2)).Sum()/n;
var offset = (2*mean - variance)/Math.Pow(d, 2);
if (offset < minOffset)
{
minKi = ki;
minOffset = offset;
optimalBinWidth = d;
}
}
return minKi;
}
private static int[] Histogram(List<double> data, int count, double xMin, double d)
{
var histogram = new int[count];
foreach (var t in data)
{
var bucket = (int) Math.Truncate((t - xMin)/d);
if (count == bucket) //fix xMax
bucket --;
histogram[bucket]++;
}
return histogram;
}
I would recommend binary search to speed up the assignment to the class intervals.
public void Add(double element)
{
if (element < Bins.First().LeftBound || element > Bins.Last().RightBound)
return;
var min = 0;
var max = Bins.Length - 1;
var index = 0;
while (min <= max)
{
index = min + ((max - min) / 2);
if (element >= Bins[index].LeftBound && element < Bins[index].RightBound)
break;
if (element < Bins[index].LeftBound)
max = index - 1;
else
min = index + 1;
}
Bins[index].Count++;
}
"Bins" is a list of items of type "HistogramItem" which defines properties like "Leftbound", "RightBound" and "Count".
I am trying to convert a C++ class to C# and in the process learn something of C++. I had never run into a vector<> before and my understanding is this is like a List<> function in C#. During the conversion of the class I re-wrote the code using List futures_price = New List(Convert.ToInt32(no_steps) + 1);. As soon as I run the code, I get a "Index was out of range" error.
Having looked around on SOF, I believe the issue is regarding the parameter being out of index range relating to this, but I do not see a simple solution to solve this with the below code.
In particular, this is the line that is triggering the error: futures_prices[0] = spot_price * Math.Pow(d, no_steps);
Below is the full code:
public double futures_option_price_call_american_binomial(double spot_price, double option_strike, double r, double sigma, double time, double no_steps)
{
//double spot_price, // price futures contract
//double option_strike, // exercise price
//double r, // interest rate
//double sigma, // volatility
//double time, // time to maturity
//int no_steps
List<double> futures_prices = new List<double>(Convert.ToInt32(no_steps) + 1);
//(no_steps+1);
//double call_values = (no_steps+1);
List<double> call_values = new List<double>(Convert.ToInt32(no_steps) + 1);
double t_delta = time/no_steps;
double Rinv = Math.Exp(-r*(t_delta));
double u = Math.Exp(sigma * Math.Sqrt(t_delta));
double d = 1.0/u;
double uu= u*u;
double pUp = (1-d)/(u-d); // note how probability is calculated
double pDown = 1.0 - pUp;
futures_prices[0] = spot_price * Math.Pow(d, no_steps);
int i;
for (i=1; i<=no_steps; ++i) futures_prices[i] = uu*futures_prices[i-1]; // terminal tree nodes
for (i=0; i<=no_steps; ++i) call_values[i] = Math.Max(0.0, (futures_prices[i]-option_strike));
for (int step = Convert.ToInt32(no_steps) - 1; step >= 0; --step)
{
for (i = 0; i <= step; ++i)
{
futures_prices[i] = d * futures_prices[i + 1];
call_values[i] = (pDown * call_values[i] + pUp * call_values[i + 1]) * Rinv;
call_values[i] = Math.Max(call_values[i], futures_prices[i] - option_strike); // check for exercise
};
};
return call_values[0];
}
Here is the original source in C++:
double futures_option_price_call_american_binomial(const double& F, // price futures contract
const double& K, // exercise price
const double& r, // interest rate
const double& sigma, // volatility
const double& time, // time to maturity
const int& no_steps) { // number of steps
vector<double> futures_prices(no_steps+1);
vector<double> call_values (no_steps+1);
double t_delta= time/no_steps;
double Rinv = exp(-r*(t_delta));
double u = exp(sigma*sqrt(t_delta));
double d = 1.0/u;
double uu= u*u;
double pUp = (1-d)/(u-d); // note how probability is calculated
double pDown = 1.0 - pUp;
futures_prices[0] = F*pow(d, no_steps);
int i;
for (i=1; i<=no_steps; ++i) futures_prices[i] = uu*futures_prices[i-1]; // terminal tree nodes
for (i=0; i<=no_steps; ++i) call_values[i] = max(0.0, (futures_prices[i]-K));
for (int step=no_steps-1; step>=0; --step) {
for (i=0; i<=step; ++i) {
futures_prices[i] = d*futures_prices[i+1];
call_values[i] = (pDown*call_values[i]+pUp*call_values[i+1])*Rinv;
call_values[i] = max(call_values[i], futures_prices[i]-K); // check for exercise
};
};
return call_values[0];
};
A List<double> starts out empty until you add items to it. (passing the constructor argument just sets the capacity, preventing costly resizes)
You can't access [0] until you Add() it.
To use it the way you are, use an array instead.
As SLaks says, it's better to use an Array in this situation. C# lists are filled with Add method and values are removed through Remove method... this would be more complicated and memory/performance expensive as you are also replacing values.
public Double FuturesOptionPriceCallAmericanBinomial(Double spotPrice, Double optionStrike, Double r, Double sigma, Double time, Double steps)
{
// Avoid calling Convert multiple times as it can be quite performance expensive.
Int32 stepsInteger = Convert.ToInt32(steps);
Double[] futurePrices = new Double[(stepsInteger + 1)];
Double[] callValues = new Double[(stepsInteger + 1)];
Double tDelta = time / steps;
Double rInv = Math.Exp(-r * (tDelta));
Double u = Math.Exp(sigma * Math.Sqrt(tDelta));
Double d = 1.0 / u;
Double uu = u * u;
Double pUp = (1 - d) / (u - d);
Double pDown = 1.0 - pUp;
futurePrices[0] = spotPrice * Math.Pow(d, steps);
for (Int32 i = 1; i <= steps; ++i)
futurePrices[i] = uu * futurePrices[(i - 1)];
for (Int32 i = 0; i <= steps; ++i)
callValues[i] = Math.Max(0.0, (futurePrices[i] - optionStrike));
for (Int32 step = stepsInteger - 1; step >= 0; --step)
{
for (Int32 i = 0; i <= step; ++i)
{
futurePrices[i] = d * futurePrices[(i + 1)];
callValues[i] = ((pDown * callValues[i]) + (pUp * callValues[i + 1])) * rInv;
callValues[i] = Math.Max(callValues[i], (futurePrices[i] - option_strike));
}
}
return callValues[0];
}