Article-20589-Volatility-Modeling-Part-1/Scripts/ArGarchModel_Demo.mq5

//+------------------------------------------------------------------+
//|                                            ArGarchModel_Demo.mq5 |
//|                                  Copyright 2025, MetaQuotes Ltd. |
//|                                             https://www.mql5.com |
//+------------------------------------------------------------------+
#property copyright "Copyright 2025, MetaQuotes Ltd."
#property link      "https://www.mql5.com"
#property version   "1.00"
#property script_show_inputs
#include<Arch\Univariate\mean.mqh>
//--- input parameters
input string   Symbol_="AUDUSD";
input ENUM_TIMEFRAMES   TimeFrame=PERIOD_D1;
input datetime StartDate=D'2025.01.01';
input ulong HistoryLen = 1504;
input double ScaleFactor=100.;
input ENUM_MEAN_MODEL MeanModel = MEAN_ARX;
input bool MeanConstant = true;
input string MeanLags ="";
input ENUM_VOLATILITY_MODEL VolatilityModel = VOL_CONST;
input ulong _P_ = 1;
input ulong _Q_ = 1;
input double Power = 2.0;
input int Volatility_Seed = 0;
input int Distribution_Seed = 0;
input ulong HoldBack = 0;
input bool UseRotated = false;
input ulong ArchLM_Lags = 30;
input bool Standardize = false;
//+------------------------------------------------------------------+
//| Script program start function                                    |
//+------------------------------------------------------------------+
void OnStart()
  {
//---download data
   vector prices;
   if(!prices.CopyRates(Symbol_,TimeFrame,COPY_RATES_CLOSE,StartDate,HistoryLen))
     {
      Print(" failed to get close prices for ", Symbol_,". Error ", GetLastError());
      return;
     }
//---
   prices = log(prices);
//---
   vector returns = np::diff(prices);
//---
   string lag_info[];
//---
   vector lags=vector::Zeros(0);
//---
   int nlags = StringSplit(MeanLags,StringGetCharacter(",",0),lag_info);
//---
   double atod;
   if(nlags>0)
     {
      for(uint i = 0; i<uint(nlags); ++i)
        {
         if(StringLen(lag_info[i])>0)
           {
            atod = StringToDouble(lag_info[i]);
            if(atod>0 && ulong(atod)<returns.Size()-1)
               if(lags.Resize(lags.Size()+1,3))
                  lags[lags.Size()-1] = atod;
           }
        }
     }
//---
   if(lags.Size())
      np::sort(lags);
//---specify the model
   ArchParameters model_spec;
   model_spec.observations = ScaleFactor*returns;
   model_spec.include_constant = MeanConstant;
   model_spec.use_har_rotation = UseRotated;
   model_spec.mean_model_type = MeanModel;
   model_spec.mean_lags = lags;
   model_spec.holdout_size = HoldBack;
   model_spec.vol_model_type = VolatilityModel;
   model_spec.garch_p = _P_;
   model_spec.garch_q = _Q_;
   model_spec.vol_power = Power;
   model_spec.vol_rng_seed = Volatility_Seed;
   model_spec.dist_rng_seed = Distribution_Seed;
//---
   HARX* ar_garch = arch_model(model_spec);
   if(!ar_garch)
      return;
//---
   ArchModelResult model = ar_garch.fit(ScaleFactor);
   delete ar_garch;
//---
   if(model.params.Size())
     {
      Print("Estimated model parameters\n ", model.params);
      Print(" Loglikelihood : ", model.loglikelihood);
      Print(" parameter pvalues\n ", model.pvalues());
      Print(" parameter tvalues\n ", model.tvalues());
      Print(" 95% conf intervals\n ", model.conf_int());
     }
//---
   WaldTestStatistic wts = archlmtest(model.resid,model.conditional_volatility,ArchLM_Lags,Standardize);
//---
   Print(" ArchLM test pvalue ", wts.pvalue());
   Print(" ArchLM test statistic ", wts.stat);
   Print(" ArchLM test critical values \n", wts.critical_values());
//---
  }
//+------------------------------------------------------------------+
HARX* arch_model(ArchParameters &archparameters)
  {
   HARX* out = NULL;
   switch(archparameters.mean_model_type)
     {
      case MEAN_CONSTANT:
         out = new ConstantMean();
         break;
      case MEAN_AR:
         out = new AR();
         break;
      case MEAN_ARX:
         out = new ARX();
         break;
      case MEAN_HAR:
         out = new HAR();
         break;
      case MEAN_HARX:
         out = new HARX();
         break;
      case MEAN_ZERO:
         out = new ZeroMean();
         break;
      default:
         out = new ConstantMean();
         break;
     }

   if(CheckPointer(out)==POINTER_DYNAMIC)
     {
      if(out.initialize(archparameters))
         return out;
      else
        {
         delete out;
         return NULL;
        }
     }
   else
      return out;
  }
//+------------------------------------------------------------------+