private static void BuildHtmlTableRow(string p_tableTitle, string p_rowTitle, bool p_isRowEven, ref MaskItem p_maskItem, StringBuilder p_sb)
{
string aMeanPerYearRowId = "id" + (p_tableTitle + p_rowTitle).Replace(' ', '_').Replace(',', '_');
string aMeanPerYearCSV = String.Join(", ", p_maskItem.AMeanPerYear.Select(r => r.Item1 + ":" + r.Item2.ToString("#0.000%")));
p_sb.AppendFormat("<tr{0}><td>" + p_rowTitle + "</td>", (p_isRowEven)? " class='even'":"");
p_sb.Append("<td>" + p_maskItem.Samples.Count() + "</td>");
p_sb.Append("<td>" + p_maskItem.WinPct.ToString("#0.0%") + "</td>");
//p_sb.AppendFormat(@"<td onclick=""document.getElementById('{0}').style.color = 'red'"">" + p_maskItem.AMean.ToString("#0.000%") + "</td>", aMeanPerYearRowId);
//p_sb.AppendFormat(@"<td onclick=""document.getElementById('{0}').style.display = 'table-row'"">" + p_maskItem.AMean.ToString("#0.000%") + @"<button onclick=""document.getElementById('{0}').style.display = 'table-row'"">*</button></td>", aMeanPerYearRowId);
//p_sb.AppendFormat(@"<td onclick=""document.getElementById('{0}').style.display = 'table-row'"">" + p_maskItem.AMean.ToString("#0.000%") + @"</td>", aMeanPerYearRowId);
//p_sb.AppendFormat(@"<td>" + p_maskItem.AMean.ToString("#0.000%") + @"<a href="""" onclick=""document.getElementById('{0}').style.display = 'table-row'"">*</a></td>", aMeanPerYearRowId);
//p_sb.AppendFormat(@"<td onclick=""document.getElementById('{0}').style.display = 'table-row'"">" + p_maskItem.AMean.ToString("#0.000%") + @"<span style=""color: #2581cc; font-size: x-small; vertical-align:super;"">i</span></td>", aMeanPerYearRowId);
p_sb.AppendFormat(@"<td{0} onclick=""InvertVisibilityOfTableRow('{1}')"">" + p_maskItem.AMean.ToString("#0.000%") + @"<span style=""color: #2581cc; font-size: x-small; vertical-align:super;"">i</span></td>", (p_maskItem.AMean > 0.0) ? " class='green'" : " class='red'", aMeanPerYearRowId);
p_sb.Append("<td>" + p_maskItem.GMean.ToString("#0.000%") + "</td>");
p_sb.Append("<td>" + p_maskItem.Median.ToString("#0.000%") + "</td>");
p_sb.Append("<td>" + p_maskItem.CorrectedStDev.ToString("#0.000%") + "</td>");
p_sb.Append("<td>" + p_maskItem.StandardError.ToString("#0.000%") + "</td>");
p_sb.AppendFormat("<td{0} >" + p_maskItem.TvalueToZero.ToString("#0.00") + "</td>", (p_maskItem.TvalueToZero >= 1.0) ? " class='green'" : ((p_maskItem.TvalueToZero <= -1.0) ? " class='red'" : ""));
p_sb.Append("<td>" + p_maskItem.PvalueToZero.ToString("#0.00%") + "</td>");
p_sb.Append("<td>" + ((p_maskItem.PvalueToZero < 0.05)?"Yes":"") + "</td>");
p_sb.Append("<td>" + p_maskItem.TvalueToAMean.ToString("#0.00") + "</td>");
p_sb.Append("<td>" + p_maskItem.PvalueToAMean.ToString("#0.00%") + "</td>");
p_sb.Append("<td>" + ((p_maskItem.PvalueToAMean < 0.05) ? "Yes" : "") + "</td>");
p_sb.Append("</tr>");
p_sb.AppendFormat(@"<tr{0} ID=""{1}"" style=""display:none;""><td colspan=""14"">{2} aMean:{3}</td>",
(p_isRowEven) ? " class='even'" : "", aMeanPerYearRowId, p_rowTitle, aMeanPerYearCSV);
p_sb.Append("</tr>");
}
private static void CreateBoolMasks(string p_dailyMarketDirectionMaskTotM, string p_dailyMarketDirectionMaskTotMM, out MaskItem[] totMForwardMask, out MaskItem[] totMBackwardMask, out MaskItem[] totMMForwardMask, out MaskItem[] totMMBackwardMask)
{
totMForwardMask = new MaskItem[30]; // (initialized to null: Neutral, not bullish, not bearish) // trading days; max. 25 is expected.
totMBackwardMask = new MaskItem[30];
totMMForwardMask = new MaskItem[30];
totMMBackwardMask = new MaskItem[30];
for (int k = 0; k < 30; k++)
{
totMForwardMask[k].Samples = new List<Tuple<DateTime, double>>();
totMBackwardMask[k].Samples = new List<Tuple<DateTime, double>>();
totMMForwardMask[k].Samples = new List<Tuple<DateTime, double>>();
totMMBackwardMask[k].Samples = new List<Tuple<DateTime, double>>();
}
int iInd = p_dailyMarketDirectionMaskTotM.IndexOf('.');
if (iInd != -1)
{
for (int i = iInd + 1; i < p_dailyMarketDirectionMaskTotM.Length; i++)
{
Utils.StrongAssert(i - (iInd + 1) < 30, "Mask half-length length should be less than 30: " + p_dailyMarketDirectionMaskTotM);
switch (p_dailyMarketDirectionMaskTotM[i])
{
case 'U':
totMForwardMask[i - (iInd + 1)].IsBullish = true;
break;
case 'D':
totMForwardMask[i - (iInd + 1)].IsBullish = false;
break;
case '0':
totMForwardMask[i - (iInd + 1)].IsBullish = null;
break;
default:
throw new Exception("Cannot interpret p_dailyMarketDirectionMaskTotM: " + p_dailyMarketDirectionMaskTotM);
//break;
}
}
for (int i = iInd - 1; i >= 0; i--)
{
Utils.StrongAssert((iInd - 1) - i < 30, "Mask half-length length should be less than 30: " + p_dailyMarketDirectionMaskTotM);
switch (p_dailyMarketDirectionMaskTotM[i])
{
case 'U':
totMBackwardMask[(iInd - 1) - i].IsBullish = true;
break;
case 'D':
totMBackwardMask[(iInd - 1) - i].IsBullish = false;
break;
case '0':
totMBackwardMask[(iInd - 1) - i].IsBullish = null;
break;
default:
throw new Exception("Cannot interpret p_dailyMarketDirectionMaskTotM: " + p_dailyMarketDirectionMaskTotM);
//break;
}
}
}
iInd = p_dailyMarketDirectionMaskTotMM.IndexOf('.');
if (iInd != -1)
{
for (int i = iInd + 1; i < p_dailyMarketDirectionMaskTotMM.Length; i++)
{
Utils.StrongAssert(i - (iInd + 1) < 30, "Mask half-length length should be less than 30: " + p_dailyMarketDirectionMaskTotMM);
switch (p_dailyMarketDirectionMaskTotMM[i])
{
case 'U':
totMMForwardMask[i - (iInd + 1)].IsBullish = true;
break;
case 'D':
totMMForwardMask[i - (iInd + 1)].IsBullish = false;
break;
case '0':
totMMForwardMask[i - (iInd + 1)].IsBullish = null;
break;
default:
throw new Exception("Cannot interpret p_dailyMarketDirectionMaskTotMM: " + p_dailyMarketDirectionMaskTotMM);
//break;
}
}
for (int i = iInd - 1; i >= 0; i--)
{
Utils.StrongAssert((iInd - 1) - i < 30, "Mask half-length length should be less than 30: " + p_dailyMarketDirectionMaskTotMM);
switch (p_dailyMarketDirectionMaskTotMM[i])
{
case 'U':
totMMBackwardMask[(iInd - 1) - i].IsBullish = true;
break;
case 'D':
totMMBackwardMask[(iInd - 1) - i].IsBullish = false;
break;
case '0':
totMMBackwardMask[(iInd - 1) - i].IsBullish = null;
break;
default:
throw new Exception("Cannot interpret p_dailyMarketDirectionMaskTotMM: " + p_dailyMarketDirectionMaskTotMM);
//break;
}
}
}
}
// http://www.danielsoper.com/statcalc3/calc.aspx?id=8
// http://en.wikipedia.org/wiki/Student's_t-test
// http://hu.wikipedia.org/wiki/Egymint%C3%A1s_t-pr%C3%B3ba
//H0: assumption: real population Mean = 0 // == real daily %change on day T is 0
//H1: real population Mean >0 // because I chose ">", I will use the one-tailed (not two tailed test); I want to know this.
//calculate P-value. (with one-tailed Student-distribution)
//If P-value <
//The decision rule is: Reject H0 if T > 1.645, which is equivalent that P < 5%.
//So, I reject H0.
//That says. The Population Mean cannot be = 0 (+- Epsilon), because that would be too unlikely that the sample mean is the value that I have for the sample.
//Becuse the sample mean is positive. (assume), and we rejected H0, therefore think the real population mean != 0 => it is event less likely that the population mean is negative.
//Therefore "the real population mean (of the daily%changes on day T) should be Positive (statistically with 95% probability), so populationMean is significantly > 0" // put this into Tooltip of Significant
// Tooltip: "With at least 1-P=95% probability: the real population mean (of the daily%changes on day T) > 0"
// "With at least 1-P=95% probability: the real population mean (of the daily%changes on day T) > allDayMean"
private static void CalculateSampleStats(ref MaskItem p_maskItem, double p_pctChgTotalAMean)
{
int nInt = p_maskItem.Samples.Count();
double n = (double)nInt;
List<double> samples = p_maskItem.Samples.Select(r => r.Item2).ToList();
double aMean = samples.Average();
double correctedStDev = Math.Sqrt(samples.Sum(r => (r - aMean) * (r - aMean)) / (n - 1.0));
double standardError = correctedStDev / Math.Sqrt(n);
p_maskItem.WinPct = (double)samples.Count(r => r > 0) / n;
p_maskItem.AMean = aMean;
p_maskItem.GMean = samples.GMeanExtendingWithOne();
p_maskItem.Median = samples.Median();
p_maskItem.CorrectedStDev = correctedStDev;
p_maskItem.StandardError = standardError;
p_maskItem.TvalueToZero = (p_maskItem.AMean - 0.0) / standardError;
p_maskItem.TvalueToAMean = (p_maskItem.AMean - p_pctChgTotalAMean) / standardError;
if (!Double.IsNaN(p_maskItem.TvalueToZero))
p_maskItem.PvalueToZero = g_statTool.TDistribution(p_maskItem.TvalueToZero, nInt - 1, true);
else
p_maskItem.PvalueToZero = Double.NaN;
if (!Double.IsNaN(p_maskItem.TvalueToAMean))
p_maskItem.PvalueToAMean = g_statTool.TDistribution(p_maskItem.TvalueToAMean, nInt - 1, true);
else
p_maskItem.PvalueToAMean = Double.NaN;
// PvalueToZero = P = probability that the observed aMean result is due to chance
p_maskItem.AMeanPerYear = new List<Tuple<string, double>>();
var years = p_maskItem.Samples.Select(r => r.Item1.Year).Distinct().OrderBy(r => r).ToList();
int nYears = years.Count();
int[] nSamplesPerYear = new int[nYears];
double[] aMeanPerYear = new double[nYears];
for (int i = 0; i < n; i++)
{
int iYears = years.IndexOf(p_maskItem.Samples[i].Item1.Year);
nSamplesPerYear[iYears]++;
aMeanPerYear[iYears] += p_maskItem.Samples[i].Item2;
}
for (int i = 0; i < nYears; i++)
{
aMeanPerYear[i] /= (double)nSamplesPerYear[i];
p_maskItem.AMeanPerYear.Add(new Tuple<string, double>(years[i].ToString() + "(" + nSamplesPerYear[i] + ")", aMeanPerYear[i]));
}
}