86 lines
4 KiB
MQL5
86 lines
4 KiB
MQL5
//+------------------------------------------------------------------+
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//| TestsForAsymmetry.mq5 |
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//| Copyright 2025, MetaQuotes Ltd. |
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//| https://www.mql5.com |
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//+------------------------------------------------------------------+
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#property copyright "Copyright 2025, MetaQuotes Ltd."
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#property link "https://www.mql5.com"
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#property version "1.00"
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#define __SLSQP__
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#property script_show_inputs
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#include "Arch\Univariate\tests.mqh"
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#include "Arch\Univariate\mean.mqh"
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//--- input parameters
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input ENUM_TIMEFRAMES TimeFrame = PERIOD_D1; //--- Data horizon interval
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input datetime StartDate = D'2026.01.01'; //--- Historical capture anchor start date
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input ulong HistoryLen = 2000; //--- Total historical data bars to request
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input ENUM_STAT_CONFIDENCE Statistical_Confidence=CONFIDENCE_95;//---Confidence level for p-value
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//+------------------------------------------------------------------+
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//| Script program start function |
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//+------------------------------------------------------------------+
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void OnStart()
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{
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//---
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vector prices;
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//--- --- Step 1: Historical Data Fetch ---
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//--- Pull raw close prices into a high-performance vector array
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if(!prices.CopyRates(NULL, TimeFrame, COPY_RATES_CLOSE, StartDate, HistoryLen) || HistoryLen > prices.Size())
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{
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Print(" failed to get close prices for ", _Symbol, ". Error ", GetLastError());
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return;
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}
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//--- --- Step 2: Transform Prices to Returns ---
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//--- Map closing prices to logarithmic space
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prices = log(prices);
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//--- Compute log returns: r_t = ln(P_t) - ln(P_{t-1})
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vector returns = np::diff(prices);
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//---
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Print(_Symbol, " : ",EnumToString(TimeFrame)," : ", TimeToString(StartDate), " : ", string(prices.Size()));
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LeverageCorrelationResult lcr = LeverageCorrelationTest(returns,1,Statistical_Confidence);
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Print("**** Leverage Correlation Test ****");
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PrintFormat("Corr(r_t-1, r_t^2): %.4f \n p-value: %.4f",lcr.correlation,lcr.p_value);
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Print("Leverage correlation test's assertion of asymmetric volatility is ", lcr.significant_leverage_effect);
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//---
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Print("**** Volatility Runs Test ****");
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VolatilityRunsResult vrr = VolatilityRunsAsymmetryTest(returns,Statistical_Confidence);
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PrintFormat("Probability of high volatility following a negative return %.8f",vrr.p_high_vol_prev_down);
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PrintFormat("Probability of high volatility following a positive return %.8f",vrr.p_high_vol_prev_up);
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PrintFormat("T_stat %.8f", vrr.chi2_stat);
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PrintFormat("Pvalue %.8f",vrr.p_value);
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Print("Volatility Runs test's assertion of asymmetric volatility is ", vrr.significant_asymmetry);
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//---
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ArchParameters arch_params;
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arch_params.mean_model_type = MEAN_CONSTANT;
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arch_params.vol_model_type = VOL_GARCH;
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arch_params.observations = returns*100.;
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//---
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ConstantMean ar_model;
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//---
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if(!ar_model.initialize(arch_params))
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{
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Print("Failed to initialize the model");
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return;
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}
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//---
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ArchModelResult model_result = ar_model.fit();
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//---
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if(!model_result.params.Size())
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return;
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//---
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returns = model_result.std_resid();
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//---
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EngleNgResult enr = EngleNgSignBiasTest(returns,Statistical_Confidence);
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Print("**** Engle's NG sign bias test results ****");
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string effects[4] = {"const", "sign-bias", "neg_size_bias", "pos_size_bias"};
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PrintFormat("%-15s %-15s %-15s %-15s","Effect","Coeffs", "T_Stats","Pvalues");
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//---
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for(uint i = 0; i<enr.coefficients.Size(); ++i)
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PrintFormat("%-15s %-15.8f %-15.8f %-15.8f", effects[i],enr.coefficients[i],enr.t_stats[i],enr.p_values[i]);
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//---
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PrintFormat("a2_minus_a3 %.8f \na2_vs_a3 t_stat %.8f \na2_vs_a3 pvalue %.8f", enr.a2_minus_a3,enr.a2_vs_a3_t_stat,enr.a2_vs_a3_p_value);
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Print("Engle NG sign bias test's assertion of asymmetric volatility is ", enr.significant_asymmetry);
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}
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//+------------------------------------------------------------------+
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