private bool BuildPopulationMatrix()
{
bool success = true;
int i, nSize;
List <Double> eqMemberX, eqMemberY;
ClassificationKey keyX = (cbProtoAttributeX.SelectedIndex < 0) ? ClassificationKey.NULL : ClassKeyList[cbProtoAttributeX.SelectedIndex];
ClassificationKey keyY = (cbProtoAttributeY.SelectedIndex < 0) ? ClassificationKey.NULL : ClassKeyList[cbProtoAttributeY.SelectedIndex];
nSize = DataSrc.HistoricalData.Constituents.Count;
PopulationToClassify = new double[nSize, 2];
eqMemberX = null;
eqMemberY = null;
if (keyX == keyY || keyX == ClassificationKey.NULL || keyY == ClassificationKey.NULL)
{
success = false;
}
else
{
for (i = 0; i < nSize; i++)
{
eqMemberX = SelectDataComponent(keyX, DataSrc.HistoricalData.Constituents[i]);
eqMemberY = SelectDataComponent(keyY, DataSrc.HistoricalData.Constituents[i]);
if (eqMemberX != null && eqMemberY != null)
{
switch (ClassFnList[cbProtoFunction.SelectedIndex])
{
case PrototypeFunction.AVERAGE:
PopulationToClassify[i, 0] = eqMemberX.Average();
PopulationToClassify[i, 1] = eqMemberY.Average();
break;
case PrototypeFunction.STD_DEV:
PopulationToClassify[i, 0] = Helpers.StdDev(eqMemberX);
PopulationToClassify[i, 1] = Helpers.StdDev(eqMemberY);
break;
case PrototypeFunction.VARIANCE:
default:
break;
}
}
else
{
success = false;
break;
}
}
}
return(success);
}
/*****************************************************************************
* FUNCTION: PearsonProductCoefficient
*
* Description: Calculates the Pearson Product Coefficient (PPC) for each
* Equity in pInputList based on it's HistoricalPrice list, against
* every other Equity in pInputList.
*
* The intent is to find correlation between Equities whose
* HistoricalPrice values tend to move together.
* Each coefficient is a value between -1 and 1. A value of
* 1 corresponds to a high positive correlation. That is, the
* Equities tend to move in the same direction at the same time
* over the series of data provided. A value of -1 corresponds to
* a high negative correlation. That is, the Equities tend to move
* in opposite directions at the same time. A value of 0 means there
* is no identifiable correlation between the direction of movement.
*
* Parameters:
* pInputList - the input data, consisting of multiple Equity instances
*****************************************************************************/
public static Double[] PearsonProductCoefficient(List <Equity> pInputList)
{
int N, cSize, i, j, k, count, key;
Double coeff, numerator, denominator;
Double meanRange1, meanRange2;
Double[] CorrelationCoefficients;
/*Create the empty correlation table. Note that we only need to calculate the correlation between any 2 equities once.
* Ex. Given 5 inputs {a,b,c,d,e}:
* a b c d e
* --------------- cSize = (5 * (4)) / 2 = 10
* a|- C0 C1 C2 C3
* b| - C4 C5 C6
* c| - C7 C8
* d| - C9
* e| -
*/
N = pInputList.Count();
cSize = N * (N - 1) / 2;
CorrelationCoefficients = new Double[cSize];
if (N > 0)
{
count = 1;
for (i = 0; i < N; i++)
{
coeff = 0;
denominator = 0;
meanRange1 = 0;
meanRange2 = 0;
for (j = count; j < N; j++)
{
if (pInputList[i].HistoricalPrice.Count() == pInputList[j].HistoricalPrice.Count())
{
numerator = 0;
//Recalculate the average instead of using the 'avgPrice' member
// because the rounded value introduces significant inaccuracy in some transformations
meanRange1 = pInputList[i].HistoricalPrice.Average();
meanRange2 = pInputList[j].HistoricalPrice.Average();
for (k = 0; k < pInputList[j].HistoricalPrice.Count(); k++)
{
numerator += (pInputList[i].HistoricalPrice[k] * pInputList[j].HistoricalPrice[k]);
}
numerator -= (pInputList[j].HistoricalPrice.Count() * meanRange1 * meanRange2);
denominator = Helpers.StdDev(pInputList[i].HistoricalPrice) * Helpers.StdDev(pInputList[j].HistoricalPrice);
denominator *= (pInputList[j].HistoricalPrice.Count() - 1);
coeff = numerator / denominator;
}
key = getHash(i + 1, j + 1, pInputList.Count());
CorrelationCoefficients[key] = coeff;
}
count++;
}
}
return(CorrelationCoefficients);
}
/*****************************************************************************
* FUNCTION: CalculateVolatility
* Description:
* Parameters:
*****************************************************************************/
private void CalculateVolatility()
{
Volatility = Helpers.StdDev(hist_daily_change);
}
/*****************************************************************************
* FUNCTION: GetFunction
* Description: Evaluates the passed funuction on the given Equity at the
* passed index (date/price)
* Parameters: None
*****************************************************************************/
private Double GetFunction(Fn pFn, Equity pEqIn, String pFnStr, int pIndex)
{
List <double> func_inputs;
Double eval_data = 0.0;
int index1, index2, filter_index1, filter_index2;
Variable input_param;
String input_param_str, filter_str;
func_inputs = new List <double>();
index1 = pFnStr.IndexOf('[');
index2 = pFnStr.IndexOf(']');
if (index1 >= 0 && index2 > index1)
{
input_param_str = pFnStr.Substring(index1 + 1, index2 - index1 - 1);
input_param = GetParameterType(input_param_str);
//Set the input array
switch (input_param)
{
case Variable.MACD_SIG:
func_inputs = new List <double>(pEqIn.MACD_B);
break;
case Variable.MACD_DIFF:
func_inputs = new List <double>(pEqIn.MACD_C);
break;
case Variable.PRICE:
func_inputs = new List <double>(pEqIn.HistoricalPrice);
break;
case Variable.VOLUME:
func_inputs = new List <double>(pEqIn.HistoricalVolumes);
break;
case Variable.PCT:
func_inputs = new List <double>(pEqIn.HistoricalPctChange);
break;
default:
break;
}
if ((pFnStr.Length > (index2 + 1)) && pFnStr.ToCharArray()[index2 + 1] == '[')
{
index1 = index2 + 1;
index2 = pFnStr.IndexOf(']', index1);
filter_index1 = 1;
filter_index2 = 1;
if (index2 > index1)
{
filter_str = pFnStr.Substring(index1 + 1, index2 - index1 - 1);
if (Regex.Matches(filter_str, "[-][0-9][.][.][-]?[0-9]").Count > 0)
{
index1 = filter_str.IndexOf('.');
filter_index1 = int.Parse(filter_str.Substring(0, index1));
filter_index2 = int.Parse(filter_str.Substring(index1 + 2, filter_str.Length - index1 - 2));
}
}
if ((filter_index1 <= 0 && filter_index2 <= 0) &&
(pIndex + filter_index1 >= 0) &&
func_inputs.Count > pIndex)
{
func_inputs = func_inputs.GetRange(pIndex + filter_index1, filter_index2 - filter_index1 - 1);
switch (pFn)
{
case Fn.AVG:
eval_data = func_inputs.Average();
break;
case Fn.MAX:
eval_data = func_inputs.Max();
break;
case Fn.MIN:
eval_data = func_inputs.Min();
break;
case Fn.TREND:
//Need some kind of curve/line fitting algorithm
break;
case Fn.STDEV:
eval_data = Helpers.StdDev(func_inputs);
break;
default:
break;
}
}
}
else
{
//If the data to be analyzed is one of the MACD signals, ensure the passed index is valid
// The index needs to be greater than the first day for which the MACD can be calculated.
// ie. for the standard 12,26,9 series, pIndex must be greater than (26 + 9) = 35
if (input_param == Variable.MACD_DIFF || input_param == Variable.MACD_SIG)
{
if (pIndex > (pEqIn.HistoricalPrice.Count() - pEqIn.MACD_C.Count()))
{
eval_data = func_inputs[pIndex];
}
else
{
eval_data = 0.0;
}
}
else
{
eval_data = func_inputs[pIndex];
}
}
}
return(eval_data);
}
/*****************************************************************************
* FUNCTION: GetParameter
* Description:
* Parameters: None
*****************************************************************************/
private Double GetParameter(Equity pEqIn, String pKey, int pIndex)
{
double return_val = 0.0;
pKey = pKey.Trim();
int macd_i_diff;
int index1 = -1, index2 = -1, filter_index;
string IndexStr = "";
Variable get_param = 0;
index1 = pKey.IndexOf('[', 1);
if (index1 > 0)
{
index2 = pKey.IndexOf(']', index1);
}
filter_index = pIndex;
//If the parameter asks for a specific index other than pIndex
if (index2 > index1)
{
IndexStr = pKey.Substring(index1 + 1, index2 - index1 - 1).Trim();
if (Regex.Matches(IndexStr, "^[-][0-9]*$").Count > 0)
{
filter_index = pIndex + int.Parse(IndexStr);
}
else
{
throw new ArgumentException();
}
//clear the index specifier
pKey = pKey.Substring(0, index1);
}
//Ex. If the passed parameter string is "P", filter_index = pIndex
// If the passed parameter string is "P[-2], filter_index = pIndex - 2
//
// At this point, in both cases pKey will be "P"
if (filter_index < 0)
{
throw new IndexOutOfRangeException();
}
get_param = GetParameterType(pKey);
switch (get_param)
{
case Variable.MACD_SIG:
macd_i_diff = pEqIn.HistoricalPrice.Count - pEqIn.MACD_B.Count;
if (filter_index >= macd_i_diff)
{
return_val = pEqIn.MACD_B[filter_index - macd_i_diff];
}
break;
case Variable.MACD_DIFF:
macd_i_diff = pEqIn.HistoricalPrice.Count - pEqIn.MACD_C.Count;
if (filter_index >= macd_i_diff)
{
return_val = pEqIn.MACD_C[filter_index - macd_i_diff];
}
break;
case Variable.PRICE:
return_val = pEqIn.HistoricalPrice[filter_index];
break;
case Variable.PCT:
return_val = pEqIn.HistoricalPctChange[filter_index];
break;
case Variable.VOLUME:
return_val = pEqIn.HistoricalVolumes[filter_index];
break;
case Variable.VX:
return_val = Helpers.StdDev(pEqIn.HistoricalPrice.GetRange(0, filter_index));
break;
case Variable.LASTBUY:
return_val = (double)(filter_index - this.buy_history.LastIndexOf(true));
break;
case Variable.LASTSELL:
return_val = (double)(filter_index - this.sell_history.LastIndexOf(true));
break;
default:
throw new ArgumentException();
}
return(return_val);
}
/*****************************************************************************
* FUNCTION: CalculateVolatility
* Description:
* Parameters:
*****************************************************************************/
private void CalculateVolatility()
{
Volatility = Helpers.StdDev(HistoricalPctChange);
}