103 lines
4.1 KiB
MQL5
103 lines
4.1 KiB
MQL5
//+------------------------------------------------------------------+
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//| news.mq5 |
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//| Copyright 2000-2026, MetaQuotes Ltd. |
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//| www.mql5.com |
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//+------------------------------------------------------------------+
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#property copyright "Copyright 2000-2026, MetaQuotes Ltd."
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#property link "https://www.mql5.com"
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//---
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#property script_show_inputs
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//---
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input string symbol = "EURUSD"; // Market symbol for analysis
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input datetime from_t = D'2025.10.15'; // Start of quotes analysis time interval
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input datetime to_t = D'2026.04.15'; // End of quotes analysis time interval
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input ENUM_TIMEFRAMES tf = PERIOD_M5; // Time frame
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input string nsource = "US"; // News source
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input double ntau = 3000.0; // Time normalization parameter
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//---
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#include "EconometricsM.mqh" // Header file with regression_Newey_West() function
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//---
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//+------------------------------------------------------------------+
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//| to get full list events ids for country use events2file.mq5 |
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//+------------------------------------------------------------------+
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ulong events_ids[]= {840010007,840020001,840030006,840030015,840050014};
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//---
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void OnStart()
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{
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//--- quotes downloading
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MqlRates rates[];
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int n_rates = CopyRates(symbol, tf, from_t, to_t, rates);
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PrintFormat("Number of downloaded quotes for symbol %s: %d", symbol, n_rates);
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if(n_rates<3)
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return;
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//--- Data set creation
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ulong n=(ulong)n_rates;
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datetime ntime[];
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news_time(from_t-24*60*60,to_t+24*60*60,nsource,events_ids,ntime);
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if(ArraySize(ntime)<1)
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{Print("No news"); return;}
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Print(ArraySize(ntime)," news");
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vector y(n);
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matrix X=matrix::Ones(n,2);
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for(ulong i=0;i<n;++i)
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{
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y[i]=MathLog(rates[i].high/rates[i].low);
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X[i][1]=tnorm(rates[i].time-ntime[ArrayBsearch(ntime,rates[i].time)]);
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}
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//--- Target scaling by standaard deviation
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y/=y.Std();
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//--- Coefficient statistics and prognose for both methods
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CoefficientStats stat[];
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// Forecast for the time of news release
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SPrognose prog;
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prog.xnew.Resize(2);
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prog.xnew[0]=1.0;
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prog.xnew[1]=1.0;
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//--- Newey-West method
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regression_Newey_West(y,X,stat,prog);
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ArrayPrint(stat);
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Print("===================================");
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prog.print();
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Print("===================================");
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//--- Standard OLS method
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regression_Newey_West(y,X,stat,prog,false);
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Print("===================================");
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ArrayPrint(stat);
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Print("===================================");
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prog.print();
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}
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//+------------------------------------------------------------------+
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//+------------------------------------------------------------------+
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//| function for getting news times |
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//+------------------------------------------------------------------+
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void news_time(datetime from,datetime to,string country,ulong& event_ids[],datetime& ntime[])
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{
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ArrayResize(ntime,0);
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MqlCalendarValue values[];
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if(CalendarValueHistory(values,from,to,country)<=0)
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{Print("CalendarValueHistory() error #",GetLastError()); return;}
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ArraySort(event_ids);
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ulong event_id;
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int nt=0;
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for(int i=0;i<ArraySize(values);++i)
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{
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event_id=event_ids[ArrayBsearch(event_ids,values[i].event_id)];
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if(event_id!=values[i].event_id)
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continue;
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++nt;
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ArrayResize(ntime,nt,100);
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ntime[nt-1]=values[i].time;
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}
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if(nt>0)
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ArraySort(ntime);
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}
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//+------------------------------------------------------------------+
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//+------------------------------------------------------------------+
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//| function for time normalization |
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//+------------------------------------------------------------------+
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double tnorm(datetime t)
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{
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double dt=t/ntau;
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return MathExp(-dt*dt);
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}
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//+------------------------------------------------------------------+
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