/// <summary>
/// Calculates the Correlation Coefficient (pearson's)
/// </summary>
/// <param name="x">independent variable</param>
/// <param name="x_avg">mean</param>
/// <param name="y">dependent variable</param>
/// <param name="y_avg">mean</param>
/// <returns>Correlation Coefficient</returns>
public static double[] CorrCoeff(Constants.RawData data, Constants.DataInfo info)
{
List <int> demquant = data.SellQuantity;
List <int> supquant = data.BuyQuantity;
List <int> demprice = data.BuyPrice;
List <int> supprice = data.SellPrice;
double demprice_avg = (double)info.BuyPriceInfo[0, 0];
double supprice_avg = (double)info.SellPriceInfo[0, 0];
double demquant_avg = (double)info.SellQuantInfo[0, 0];
double supquant_avg = (double)info.BuyQuantInfo[0, 0];
double[] Corrs = new double[2];
double nominator = 0;
double denominator = 0;
double Denomxx = 0;
double Denomyy = 0;
for (int i = 0; i < demquant.Count(); i++)
{
nominator += (demprice.ElementAt(i) - demprice_avg) * (demquant.ElementAt(i) - demquant_avg);
Denomxx += Math.Pow(demprice.ElementAt(i) - demprice_avg, 2);
Denomyy += Math.Pow(demquant.ElementAt(i) - demquant_avg, 2);
}
denominator = Math.Sqrt(Denomxx * Denomyy);
Corrs[0] = nominator / denominator;
for (int i = 0; i < demquant.Count(); i++)
{
nominator += (supprice.ElementAt(i) - supprice_avg) * (supquant.ElementAt(i) - supquant_avg);
Denomxx += Math.Pow(supprice.ElementAt(i) - supprice_avg, 2);
Denomyy += Math.Pow(supquant.ElementAt(i) - supquant_avg, 2);
}
denominator = Math.Sqrt(Denomxx * Denomyy);
Corrs[1] = nominator / denominator;
return(Corrs);
}
public static void Main(string[] args)
{
int i = 3;
Console.WriteLine("Operation on dataset: Item ({0})...", Constants.id[i]);
//get initial data from files
var RawData = DataPreparer.Splicer(i);
Console.WriteLine("Getting data from files");
//subset length, total set size is 4*n (buy/sell quant, buy/sell price)
//trim dataset to n before singleton implemented!
int n = 4000;
Console.WriteLine("trimmng datset...");
DataPreparer.Trimmer(RawData, n);
//get item specific data for raw dataset as a singleton class
Console.WriteLine("Getting item...");
Constants.Item item = Constants.Item.GetItem(RawData, n);
Constants.RawData Data = Constants.Item.GetRawData();
//standardised dataset as well as weighted and standardised weighted data
Console.WriteLine("Standardising dataset");
Constants.StrdData strdData = DataPreparer.Z_Score(Data);
//LSR fitting solutions to each set (standardised & non-standardised)
Console.WriteLine("Fitting function parameters");
double[,] FitEq = FittingFunctions.FitLin(Data, n);
double[,] StrdFitEq = FittingFunctions.StrdFitLin(strdData, n);
Constants.DataInfo Info = DataPreparer.DataInfo();
Console.WriteLine("Getting model information");
double[] Corrs = ModelInfo.CorrCoeff(Data, Info);
//Get prediction lists and convert to List<int> for StrdDev function
var _DemPreds = FittingFunctions.Predictor(Data.BuyPrice, FitEq[0, 0], FitEq[1, 0]);
List <int> DemPreds = _DemPreds.Select(x => (int)x).ToList();
var _SupPreds = FittingFunctions.Predictor(Data.SellPrice, FitEq[0, 1], FitEq[1, 1]);
List <int> SupPreds = _SupPreds.Select(x => (int)x).ToList();
//Standard deviations of data, standard deviations of predicted data & correlations
double[] FitData =
{
ModelInfo.StrdDev(Data.SellQuantity, Info.SellQuantInfo, n),
ModelInfo.StrdDev(Data.BuyQuantity, Info.BuyQuantInfo, n),
ModelInfo.StrdDev(DemPreds, Info.BuyQuantInfo, n),
ModelInfo.StrdDev(SupPreds, Info.BuyQuantInfo, n),
ModelInfo.RMSE(FitEq[2, 0], n),ModelInfo.RMSE(FitEq[2,1], n),
Corrs[0], Corrs[1]
};
Console.WriteLine("Printing results to files...");
DataWriter.FileMaker(Info, i, FitEq, StrdFitEq, FitData);
Console.Write("Check the desktop!");
Console.ReadLine();
}
/// <summary>
/// Item data, Mean, Min, Max, Median and Set Length
/// </summary>
/// <param name="rawdata">Input standard data object</param>
/// <returns>DataInfo object, Mean, Min, Max, Median and Set Length</returns>
public static Constants.DataInfo StrdDataInfo(Constants.StrdData strdData)
{
Object[,] spriceinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] squantinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] bpriceinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] bquantinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
List <double> sprice = new List <double>();
List <double> squant = new List <double>();
List <double> bprice = new List <double>();
List <double> bquant = new List <double>();
Constants.DataInfo datainfo = new Constants.DataInfo(spriceinfo, squantinfo, bpriceinfo, bquantinfo);
bpriceinfo[0, 0] = strdData._strdBuyPrice.Average();
bpriceinfo[1, 0] = strdData._strdBuyPrice.Min();
bpriceinfo[2, 0] = strdData._strdBuyPrice.Max();
bpriceinfo[4, 0] = strdData._strdBuyPrice.Count();
bprice.AddRange(strdData._strdBuyPrice);
bprice.Sort();
int i = (bprice.Count() + 1) / 2;
bpriceinfo[3, 0] = bprice.ElementAt(i);
spriceinfo[0, 0] = strdData._strdSellPrice.Average();
spriceinfo[1, 0] = strdData._strdSellPrice.Min();
spriceinfo[2, 0] = strdData._strdSellPrice.Max();
spriceinfo[4, 0] = strdData._strdSellPrice.Count();
sprice.AddRange(strdData._strdSellPrice);
sprice.Sort();
int j = (sprice.Count() + 1) / 2;
spriceinfo[3, 0] = sprice.ElementAt(j);
bquantinfo[0, 0] = strdData._strdBuyQuant.Average();
bquantinfo[1, 0] = strdData._strdBuyQuant.Min();
bquantinfo[2, 0] = strdData._strdBuyQuant.Max();
bquantinfo[4, 0] = strdData._strdBuyQuant.Count();
bquant.AddRange(strdData._strdBuyQuant);
bquant.Sort();
int k = (bquant.Count() + 1) / 2;
bquantinfo[3, 0] = bquant.ElementAt(k);
squantinfo[0, 0] = strdData._strdSellQuant.Average();
squantinfo[1, 0] = strdData._strdSellQuant.Min();
squantinfo[2, 0] = strdData._strdSellQuant.Max();
squantinfo[4, 0] = strdData._strdSellQuant.Count();
squant.AddRange(strdData._strdSellQuant);
squant.Sort();
int l = (squant.Count() + 1) / 2;
squantinfo[3, 0] = squant.ElementAt(l);
datainfo.BuyPriceInfo = bpriceinfo;
datainfo.BuyQuantInfo = bquantinfo;
datainfo.SellQuantInfo = squantinfo;
datainfo.SellPriceInfo = spriceinfo;
return(datainfo);
}
/// <summary>
/// Item data, Mean, Min, Max, Median and Set Length
/// </summary>
/// <param name="rawdata">Input data object, with four lists</param>
/// <returns>DataInfo object, Mean, Min, Max, Median and Set Length</returns>
public static Constants.DataInfo DataInfo()
{
Constants.RawData rawdata = Constants.Item.GetRawData();
Object[,] spriceinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] squantinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] bpriceinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
Object[,] bquantinfo = new Object[, ] {
{ 0, "Mean" }, { 0, "Min" }, { 0, "Max" }, { 0, "Median" }, { 0, "Set Length" }
};
List <int> sprice = new List <int>();
List <int> squant = new List <int>();
List <int> bprice = new List <int>();
List <int> bquant = new List <int>();
Constants.DataInfo datainfo = new Constants.DataInfo(spriceinfo, squantinfo, bpriceinfo, bquantinfo);
bpriceinfo[0, 0] = rawdata.BuyPrice.Average();
bpriceinfo[1, 0] = rawdata.BuyPrice.Min();
bpriceinfo[2, 0] = rawdata.BuyPrice.Max();
bpriceinfo[4, 0] = rawdata.BuyPrice.Count();
bprice.AddRange(rawdata.BuyPrice);
bprice.Sort();
int i = (bprice.Count() + 1) / 2;
bpriceinfo[3, 0] = bprice.ElementAt(i);
spriceinfo[0, 0] = rawdata.SellPrice.Average();
spriceinfo[1, 0] = rawdata.SellPrice.Min();
spriceinfo[2, 0] = rawdata.SellPrice.Max();
spriceinfo[4, 0] = rawdata.SellPrice.Count();
sprice.AddRange(rawdata.SellPrice);
sprice.Sort();
int j = (sprice.Count() + 1) / 2;
spriceinfo[3, 0] = sprice.ElementAt(j);
bquantinfo[0, 0] = rawdata.BuyQuantity.Average();
bquantinfo[1, 0] = rawdata.BuyQuantity.Min();
bquantinfo[2, 0] = rawdata.BuyQuantity.Max();
bquantinfo[4, 0] = rawdata.BuyQuantity.Count();
bquant.AddRange(rawdata.BuyQuantity);
bquant.Sort();
int k = (bquant.Count() + 1) / 2;
bquantinfo[3, 0] = bquant.ElementAt(k);
squantinfo[0, 0] = rawdata.SellQuantity.Average();
squantinfo[1, 0] = rawdata.SellQuantity.Min();
squantinfo[2, 0] = rawdata.SellQuantity.Max();
squantinfo[4, 0] = rawdata.SellQuantity.Count();
squant.AddRange(rawdata.SellQuantity);
squant.Sort();
int l = (squant.Count() + 1) / 2;
squantinfo[3, 0] = squant.ElementAt(l);
datainfo.BuyPriceInfo = bpriceinfo;
datainfo.BuyQuantInfo = bquantinfo;
datainfo.SellQuantInfo = squantinfo;
datainfo.SellPriceInfo = spriceinfo;
return(datainfo);
}
/// <summary>
/// Create a Human Readable File on the desktop. Including analysis of instances and fitted functions.
/// </summary>
/// <param name="info">RawData info object</param>
/// <param name="n">item ID</param>
/// <param name="RawFit">Fitted Parameters for rawdata</param>
/// <param name="StrdFit">Fitted Parameters for Standardised Data</param>
/// <param name="WeightedFit">Fitted Parameters for EWMA data</param>
/// <param name="WeightedFit">Fitted Parameters for standardised EWMA data</param>
public static void FileMaker(Constants.DataInfo info, int n, double[,] RawFit, double[,] StrdFit, double[] ModelInfo)
{
if (info == null)
{
throw new ArgumentNullException(nameof(info));
}
if (RawFit == null)
{
throw new ArgumentNullException(nameof(RawFit));
}
if (StrdFit == null)
{
throw new ArgumentNullException(nameof(StrdFit));
}
if (ModelInfo == null)
{
throw new ArgumentNullException(nameof(ModelInfo));
}
string FileName = @"c: \Users\iTzEinstein118Xx\Desktop\AnalysisData" + Constants.id[n] + ".txt";
try {
using (StreamWriter sw = new StreamWriter(FileName, false))
{
sw.WriteLine("Human Readable File: {0}\n", Constants.id[n]);
sw.WriteLine("Info for BuyQuant\n");
sw.WriteLine("Analysis of Instances:\n");
foreach (object inf in info.BuyQuantInfo)
{
string bqinf = Convert.ToString(inf);
sw.WriteLine(" " + bqinf + "\n");
sw.Write("\n");
}
sw.WriteLine("Info for BuyPrice");
sw.WriteLine("Analysis of Instances:\n");
foreach (object inf in info.BuyPriceInfo)
{
string binf = Convert.ToString(inf);
sw.WriteLine(" " + binf + "\n");
}
sw.WriteLine("Info for SellQuant");
sw.WriteLine("Analysis of Instances:\n");
foreach (object inf in info.SellQuantInfo)
{
string pqinfo = Convert.ToString(inf);
sw.WriteLine(" " + pqinfo + "\n");
}
sw.WriteLine("Info for SellPrice");
sw.WriteLine("Analysis of Instances:\n");
foreach (object inf in info.SellPriceInfo)
{
string sinf = Convert.ToString(inf);
sw.WriteLine(" " + sinf + "\n");
}
sw.WriteLine("Demand Function: {0} + {1}p \r R-Squared: {2}\n", RawFit[1, 0], RawFit[0, 0], RawFit[2, 0]);
sw.WriteLine("Supply Function: {0} + {1}p \r R-Squared: {2}\n", RawFit[1, 1], RawFit[0, 1], RawFit[2, 1]);
sw.WriteLine("\n");
sw.WriteLine("Standard Demand Function: {0} + {1}p \r R-Squared: {2}\n", StrdFit[1, 0], StrdFit[0, 0], StrdFit[2, 0]);
sw.WriteLine("Standard Demand Function: {0} + {1}p \r R-Squared: {2}\n", StrdFit[1, 1], StrdFit[0, 1], StrdFit[2, 1]);
sw.WriteLine("Raw Data Info: \n");
sw.WriteLine("Standard Dev, Demand: {0}", ModelInfo[0]);
sw.WriteLine("Standard Dev, Supply: {0}", ModelInfo[1]);
sw.WriteLine("Correlation, Demand: {0}", ModelInfo[6]);
sw.WriteLine("Correlation, Supply: {0}", ModelInfo[7]);
sw.WriteLine("Fitted Data Info: \n");
sw.WriteLine("Standard Dev, Fitted Demand: {0}", ModelInfo[2]);
sw.WriteLine("Standard Dev, Fitted Supply: {0}", ModelInfo[3]);
sw.WriteLine("RMSE, Demand: {0}", ModelInfo[4]);
sw.WriteLine("RMSE, Supply: {0}", ModelInfo[5]);
Console.Write("File Printed!\n");
}
}
finally
{
}
}
