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