forked from Lerooy/pbo-cscv-engine
140 lines
6 KiB
MQL5
140 lines
6 KiB
MQL5
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//+------------------------------------------------------------------+
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//| TestCSCVEngine.mq5 |
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//| Validation of the CSCV engine - Astralys LLC |
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//| |
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//| Before running the engine on real data, it has to be checked |
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//| against cases whose answer is known in advance. Otherwise there |
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//| is no way to tell a bug from a discovery, which is precisely the |
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//| failure mode the article is about. |
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//| |
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//| Two brackets, both stated by Bailey et al. (2015): |
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//| |
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//| CASE A - pure noise, no skill anywhere. |
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//| "if the relative ranks are distributed close to uniformly, |
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//| the distribution of the logits will approximate the standard |
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//| Normal distribution with a 0 mean and a standard deviation |
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//| of 1. This is the case when the backtest lacks information" |
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//| Expected: PBO close to 50%, logit mean close to 0. |
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//| |
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//| CASE B - one genuinely superior strategy, present in every |
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//| partition. The in-sample winner is also the out-of-sample |
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//| winner every time. |
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//| Expected: PBO close to 0%, logits large and positive. |
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//| |
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//| If the engine passes both, its arithmetic is sound. |
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//+------------------------------------------------------------------+
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#property copyright "Astralys LLC"
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#property link "https://pulsar-terminal.com"
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#property version "1.00"
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#property script_show_inputs
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#include <PBO/CSCVEngine.mqh>
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input int InpRows = 1600; // bars
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input int InpCols = 200; // parameter combinations
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input int InpPartitions = 16; // S
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input int InpSeed = 20260815;
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//+------------------------------------------------------------------+
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//| Standard normal deviate, Box-Muller. MathRand is seeded by the |
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//| caller so the whole test is reproducible. |
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//+------------------------------------------------------------------+
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double Gauss(void)
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{
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double u1 = (MathRand() + 1.0) / 32768.0; // (0,1], never exactly 0
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double u2 = (MathRand() + 0.5) / 32768.0;
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return(MathSqrt(-2.0 * MathLog(u1)) * MathCos(2.0 * M_PI * u2));
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}
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//+------------------------------------------------------------------+
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//| Mean and standard deviation of an array. |
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//+------------------------------------------------------------------+
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void MeanSd(const double &v[], double &mean, double &sd)
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{
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const int n = ArraySize(v);
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mean = 0.0; sd = 0.0;
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if(n < 2) return;
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for(int i = 0; i < n; i++) mean += v[i];
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mean /= n;
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for(int i = 0; i < n; i++) { const double d = v[i] - mean; sd += d * d; }
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sd = MathSqrt(sd / (n - 1));
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}
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//+------------------------------------------------------------------+
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//| Fill a T x N matrix of log returns. |
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//| |
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//| edge > 0 gives column `star` a constant per-bar drift, which |
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//| makes it dominate in every partition. |
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//+------------------------------------------------------------------+
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void BuildMatrix(double &m[], const int rows, const int cols,
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const double edge, const int star)
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{
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const double vol = 0.01;
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for(int t = 0; t < rows; t++)
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{
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const int base = t * cols;
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for(int n = 0; n < cols; n++)
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m[base + n] = vol * Gauss() + ((n == star) ? edge : 0.0);
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}
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}
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//+------------------------------------------------------------------+
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//| Run one case and report. |
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//+------------------------------------------------------------------+
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void RunCase(const string label, const double edge, const int star,
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const double pboLow, const double pboHigh)
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{
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double m[];
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if(ArrayResize(m, InpRows * InpCols) != InpRows * InpCols)
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{
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Print("cannot allocate matrix");
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return;
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}
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MathSrand(InpSeed);
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BuildMatrix(m, InpRows, InpCols, edge, star);
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CCSCVEngine engine;
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if(!engine.SetPartitions(InpPartitions)) return;
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if(!engine.SetReturns(m, InpRows, InpCols)) return;
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if(!engine.Run()) return;
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double logits[];
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engine.GetLogits(logits);
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double mean, sd;
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MeanSd(logits, mean, sd);
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const double pbo = engine.PBO();
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const bool passed = (pbo >= pboLow && pbo <= pboHigh);
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PrintFormat("--- %s", label);
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PrintFormat(" PBO = %6.2f%% (expected %.0f%% to %.0f%%) %s",
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pbo, pboLow, pboHigh, passed ? "PASS" : "FAIL");
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PrintFormat(" probability of loss = %6.2f%%", engine.ProbabilityOfLoss());
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PrintFormat(" logits: mean %+.3f, sd %.3f, count %d",
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mean, sd, engine.CombinationCount());
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}
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//+------------------------------------------------------------------+
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//| Script entry point |
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//+------------------------------------------------------------------+
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void OnStart(void)
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{
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PrintFormat("CSCV validation: %d bars, %d trials, S = %d, seed %d",
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InpRows, InpCols, InpPartitions, InpSeed);
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// No skill anywhere. The in-sample winner is a coin toss out of sample,
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// so roughly half the combinations should land below the median.
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RunCase("CASE A - pure noise", 0.0, -1, 40.0, 60.0);
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// One strategy is genuinely better, in every partition.
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// The engine must recognise it and report almost no overfitting.
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RunCase("CASE B - one persistent winner", 0.004, 7, 0.0, 2.0);
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Print("--- done. Case A near 50% and case B near 0% means the arithmetic holds.");
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}
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//+------------------------------------------------------------------+
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