311 lines
9.2 KiB
MQL5
311 lines
9.2 KiB
MQL5
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//+------------------------------------------------------------------+
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//| VolatilityModelParameterComparison.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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#property script_show_inputs
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#property description "The script downloads data from the terminal"
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"to build a conditional volatility model using"
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"the MQL5 library then Pythons ARCH module. By"
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"default MQL5 lib uses minNLC. To use the SLSQP "
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"solver define __SLSQP__ before including"
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"the arch library and compile"
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#define __SLSQP__
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#include<slsqp_article\Arch\Univariate\mean.mqh>
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#include<slsqp_article\win32_utils.mqh>
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#include<slsqp_article\JAson.mqh>
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#include<Files\FileTxt.mqh>
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//---
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#define FILENAME "arch.json"
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#define SPACE " "
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#define PYFILE "\\MQL5\\Scripts\\slsqp_article\\mt5_volatility_processor.py"
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//---
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input string Symbol_="AUDUSD";
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input ENUM_TIMEFRAMES TimeFrame=PERIOD_D1;
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input datetime StartDate=D'2025.01.01';
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input ulong HistoryLength = 1000;
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input double ScaleFactor=100.;
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input ENUM_MEAN_MODEL MeanModel = MEAN_CONSTANT;
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input bool MeanConstant = true;
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input string MeanLags ="";
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input ENUM_VOLATILITY_MODEL VolatilityModel = VOL_GJR_GARCH;
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input ENUM_DISTRIBUTION_MODEL ErrorDistribution = DIST_NORMAL;
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input ulong _P_ = 1;
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input ulong _O_ = 1;
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input ulong _Q_ = 1;
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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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#ifdef __SLSQP__
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Print("USING SLSQP");
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#else
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Print("USING minNLC");
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#endif
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Print(EnumToString(MeanModel));
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Print(EnumToString(VolatilityModel));
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Print(EnumToString(ErrorDistribution));
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//---
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string pstring = EnumToString(TimeFrame);
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if(StringFind(pstring,"CURRENT")>=0)
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{
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Print("Invalid parameter setting. Please do not use PERIOD_CURRENT option, be explicit.");
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return;
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}
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//---
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ArchParameters spec;
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spec.mean_model_type = MeanModel;
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//---
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string lag_info[];
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int nlags = StringSplit(MeanLags,StringGetCharacter(",",0),lag_info);
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if(nlags>0)
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{
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for(uint i = 0; i<uint(nlags); ++i)
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{
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if(StringLen(lag_info[i])>0)
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{
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if(spec.mean_lags.Resize(spec.mean_lags.Size()+1,3))
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spec.mean_lags[spec.mean_lags.Size()-1] = StringToDouble(lag_info[i]);
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else
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{
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Print(" error ", GetLastError());
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return;
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}
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}
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}
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}
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//---
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spec.vol_model_type = VolatilityModel;
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spec.garch_o = _O_;
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spec.garch_p = _P_;
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spec.garch_q = _Q_;
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spec.dist_type = ErrorDistribution;
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//---download data
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vector prices;
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if(!prices.CopyRates(Symbol_,TimeFrame,COPY_RATES_CLOSE,StartDate,HistoryLength))
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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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//---
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prices = log(prices);
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//---get returns
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vector returns = np::diff(prices);
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//---
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if(ScaleFactor>1)
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returns*=ScaleFactor;
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//---
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spec.observations = returns;
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//---
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HARX* arma_garch = arch_model(spec);
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if(!arma_garch)
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return;
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//---
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ArchParameters final_spec = arma_garch.get_specification();
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Print("GARCH spec");
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PrintFormat("P(%d) O(%d) Q(%d) Power(%f)",final_spec.garch_p,final_spec.garch_o,final_spec.garch_q,final_spec.vol_power);
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//---
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#ifdef __SLSQP__
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ArchModelResult mt5_result = arma_garch.fit();
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#else
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ArchModelResult mt5_result = arma_garch.fit(ScaleFactor);
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#endif
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//---
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if(mt5_result.params.Size())
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{
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Print("MT5 model parameters: ", mt5_result.params);
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Print("MT5 model LogLikelihood: ", -1.*mt5_result.loglikelihood);
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}
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else
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Print("Fitting model failed");
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delete arma_garch;
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//---
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string cmdLine = StringFormat("%s %s%s%s","python ",TerminalInfoString(TERMINAL_DATA_PATH),PYFILE,cmd_builder(Symbol_,
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StartDate,TimeFrame,HistoryLength,VolatilityModel,
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ScaleFactor,MeanModel,MeanConstant,MeanLags,
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ErrorDistribution,final_spec.garch_p,final_spec.garch_o,final_spec.garch_q));
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//Print(cmdLine);
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//---
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PROCESS_INFORMATION piProcInfo;
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STARTUPINFOW siStartInfo;
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BOOL process_run = false;
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//---
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ZeroMemory(piProcInfo);
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ZeroMemory(siStartInfo);
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siStartInfo.cb = sizeof(STARTUPINFOW);
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vector parameters;
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//---
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if(CreateProcessW(NULL,cmdLine,NULL,NULL,0,DETACHED_PROCESS,NULL,NULL,siStartInfo,piProcInfo))
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{
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WaitForSingleObject(piProcInfo.hProcess,INFINITE);
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uint exitcode;
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GetExitCodeProcess(piProcInfo.hProcess,exitcode);
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if(!exitcode)
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{
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CFileTxt jfile;
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if(jfile.Open(FILENAME,FILE_READ|FILE_COMMON) != INVALID_HANDLE)
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{
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CJAVal js;
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if(js.Deserialize(jfile.ReadString()))
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{
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int jsize = js["x"].Size();
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parameters = vector::Zeros(jsize);
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for(int i = 0; i<jsize; ++i)
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parameters[i] = js["x"][i].ToDbl();
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Print("Python's Model Parameters ", parameters);
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Print("Python's LogLikelihood: ", js["fun"].ToDbl());
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}
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else
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Print("Failed to deserialize the model");
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jfile.Delete(FILENAME,FILE_COMMON);
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}
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else
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Print("File open error ", GetLastError());
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}
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else
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Print("Python process failed to execute successfully.");
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}
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else
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printf("CreateProcess failed with error %d\n", kernel32::GetLastError());
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//---
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CloseHandle(piProcInfo.hProcess);
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CloseHandle(piProcInfo.hThread);
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}
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//+------------------------------------------------------------------+
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HARX* arch_model(ArchParameters &archparameters)
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{
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HARX* out = NULL;
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switch(archparameters.mean_model_type)
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{
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case MEAN_CONSTANT:
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out = new ConstantMean();
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break;
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case MEAN_AR:
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out = new AR();
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break;
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case MEAN_ARX:
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out = new ARX();
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break;
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case MEAN_HAR:
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out = new HAR();
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break;
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case MEAN_HARX:
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out = new HARX();
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break;
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case MEAN_ZERO:
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out = new ZeroMean();
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break;
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default:
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out = new ConstantMean();
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break;
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}
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if(CheckPointer(out)==POINTER_DYNAMIC)
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{
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if(out.initialize(archparameters))
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return out;
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else
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{
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delete out;
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return NULL;
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}
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}
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else
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return out;
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}
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//+------------------------------------------------------------------+
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//| parse model options |
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//+------------------------------------------------------------------+
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string cmd_builder(string symb, datetime sdate, ENUM_TIMEFRAMES tf, ulong hist,ENUM_VOLATILITY_MODEL vmod, double scalef, ENUM_MEAN_MODEL mmod, bool mconst, string mlags, ENUM_DISTRIBUTION_MODEL edist, ulong P, ulong O, ulong Q)
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{
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string stime = TimeToString(sdate, TIME_DATE|TIME_MINUTES);
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StringReplace(stime, " ", "_");
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string tf_str = EnumToString(tf);
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tf_str = StringSubstr(tf_str, 7);
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string mmod_str = "";
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switch(mmod)
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{
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case MEAN_CONSTANT:
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mmod_str = "constant";
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break;
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case MEAN_ZERO:
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mmod_str = "zero";
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break;
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case MEAN_AR:
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mmod_str = "ar";
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break;
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case MEAN_ARX:
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mmod_str = "arx";
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break;
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case MEAN_HAR:
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mmod_str = "har";
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break;
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case MEAN_HARX:
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mmod_str = "harx";
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break;
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default:
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mmod_str = "constant";
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break;
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}
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string vmod_str = "garch";
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switch(vmod)
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{
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case VOL_ARCH:
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vmod_str = "arch";
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break;
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case VOL_CONST:
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vmod_str = "constant";
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break;
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case VOL_AVARCH:
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vmod_str = "avarch";
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break;
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case VOL_AVGARCH:
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vmod_str = "avgarch";
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break;
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case VOL_TARCH:
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vmod_str = "tarch";
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break;
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case VOL_GJR_GARCH:
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vmod_str = "gjr-garch";
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break;
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default:
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vmod_str = "garch";
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break;
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}
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string edist_str = "";
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switch(edist)
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{
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case DIST_NORMAL:
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edist_str = "normal";
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break;
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case DIST_GEN_ERROR:
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edist_str = "gen-error";
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break;
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case DIST_SKEW_STUDENT:
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edist_str = "skewed-student";
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break;
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case DIST_STUDENT:
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edist_str = "student";
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break;
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default:
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edist_str = "normal";
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break;
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}
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string final_lags = (StringLen(mlags) > 0) ? mlags : "0";
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string out = StringFormat("%s %s %s %s %s %G %I64u %I64u %I64u %I64u %s %d %s %s %s",
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SPACE, FILENAME, stime, symb, tf_str,
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scalef, hist, P, O, Q,
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mmod_str, (mconst ? 1 : 0), vmod_str, edist_str, final_lags);
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return out;
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}
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//+------------------------------------------------------------------+
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