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Librerie: Calendario - pagina 10

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Sulla rilevanza dei dati del calendario.


Per un confronto il lavoro di un'altra fonte.

La libreria è stata aggiornata per consentire la modifica degli eventi. 
#include <fxsaber\Calendar\Calendar.mqh> // https://www.mql5.com/it/code/32430

void OnStart()
{
  CALENDAR Calendar;
  
  const string Currencies[] = {SymbolInfoString(_Symbol, SYMBOL_CURRENCY_BASE),
                               SymbolInfoString(_Symbol, SYMBOL_CURRENCY_PROFIT)};
  
  // Ha selezionato i prossimi eventi importanti in base alle valute simbolo.
  Calendar.Set(Currencies);
  
  Print(Calendar.ToString()); // Stampateli.
  
  EVENT Events[];
  
  if (Calendar.GetEvents(Events) > 0) // Ho ottenuto tutti gli eventi in formato interno.
  {    
    Events[0].Importance = (ENUM_CALENDAR_EVENT_IMPORTANCE)27; // Ha cambiato l'importanza dell'evento.

    Calendar = Events; // Inserire gli eventi nel calendario.
    
    Print(Calendar.ToString()); // Stampateli.
  }
}


Risultato.

2024.03.06 16:45 CAD 3 BoC Interest Rate Decision (boc-interest-rate-decision), Canada (CA) |  |  | 5.0% | 
2024.03.06 17:00 CAD 3 Ivey PMI (ivey-pmi), Canada (CA) |  | 56.4 | 56.5 | 
2024.03.08 15:30 CAD 3 Employment Change (employment-change), Canada (CA) |  | 33.3 K | 37.3 K | 

2024.03.06 16:45 CAD 27 BoC Interest Rate Decision (boc-interest-rate-decision), Canada (CA) |  |  | 5.0% | 
2024.03.06 17:00 CAD 3 Ivey PMI (ivey-pmi), Canada (CA) |  | 56.4 | 56.5 | 
2024.03.08 15:30 CAD 3 Employment Change (employment-change), Canada (CA) |  | 33.3 K | 37.3 K |

Forum sul trading, sui sistemi di trading automatizzati e sulla verifica delle strategie di trading

Biblioteche: Calendario

fxsaber, 2023.04.13 00:07 pm.

Sembra che io abbia un correttore di calendario che corrisponde al server di trading.

#property script_show_inputs

input ulong inEventID = 840030006; // EventID
input string inName = ""; // Nome -> EventID (Nonfarm Payrolls -> 840030016)
input datetime inFrom = D'2020.01.01';
input bool inDST = true;

void OnStart()
{
  CALENDAR Calendar;
    
  if (inName == "")
  {
    Calendar.Set(inEventID);
    Calendar.FilterByTime(inFrom, TimeCurrent());
    
    Calendar.CorrectTime(); // Bypassare le peculiarità di MQL-calendario: https://www.mql5.com/ru/forum/444094/page14#comment_46213385
    
    if (inDST)
      Calendar.DST(); // Chiamata se il server commerciale è sincronizzato con l'ora europea.
  
    for (int i = Calendar.GetAmount() - 1; i >= 0; i--)
    {
      const EVENT Event = Calendar[i];    
      const datetime ChartNews = ChartNewsTime(Event.time); // https://www.mql5.com/ru/forum/357793/page5#comment_44225999
      
      if (Event.time != ChartNews)    
        Print("-" + (string)Event.EventID + ": " + TimeToString(ChartNews) + " != " + Event.ToString());
      else
        Print("+" + (string)Event.EventID + ": " + TimeToString(ChartNews) + " == " + Event.ToString());
    }
  }
  else // Ottenere l'ID evento per nome.
  {
    string Currencies[2];
    
    // Ottenere le valute del carattere corrente.
    Currencies[0] = ::SymbolInfoString(_Symbol, SYMBOL_CURRENCY_BASE);
    Currencies[1] = ::SymbolInfoString(_Symbol, SYMBOL_CURRENCY_PROFIT);
    
    if (Calendar.Set(Currencies, CALENDAR_IMPORTANCE_MODERATE, inFrom) && Calendar.FilterByName(inName))
      for (int i = Calendar.GetAmount() - 1; i >= 0; i--)
        Print((string)Calendar[i].EventID + ": " + Calendar[i].ToString());
  }
}


Risultato.

+840030016: 2023.04.07 15:30 == 2023.04.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 236 K | -8 K | 311 K | 326 K
+840030016: 2023.03.10 15:30 == 2023.03.10 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 311 K | -35 K | 517 K | 504 K
+840030016: 2023.02.03 15:30 == 2023.02.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 517 K | 16 K | 223 K | 260 K
+840030016: 2023.01.06 15:30 == 2023.01.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 223 K | 57 K | 263 K | 256 K
+840030016: 2022.12.02 15:30 == 2022.12.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | -30 K | 261 K | 284 K
+840030016: 2022.11.04 14:30 == 2022.11.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 261 K | -97 K | 263 K | 315 K
+840030016: 2022.10.07 15:30 == 2022.10.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 33 K | 315 K | 
+840030016: 2022.09.02 15:30 == 2022.09.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 315 K | 156 K | 528 K | 526 K

Corrisponde al calendario web. Se qualcuno vede qualche evidente incongruenza, me lo faccia sapere.

Ora sembra che sia corretto utilizzare il calendario per i backtest.

Ho ottenuto questo risultato:

OnStart > DST: false
+840030006: 2024.03.12 14:30 == 2024.03.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.3% | 0.4% | 
-840030006: 2024.02.13 15:30 != 2024.02.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.2% | 0.3% | 
-840030006: 2024.01.11 15:30 != 2024.01.11 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.3% | 0.3% | 
-840030006: 2023.12.12 15:30 != 2023.12.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.3% | 0.2% | 
-840030006: 2023.11.14 15:30 != 2023.11.14 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.3% | 0.3% | 
-840030006: 2023.10.12 15:30 != 2023.10.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.4% | 0.3% | 
-840030006: 2023.09.13 15:30 != 2023.09.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.4% | 0.2% | 
-840030006: 2023.08.10 15:30 != 2023.08.10 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.4% | 0.2% | 
-840030006: 2023.07.12 15:30 != 2023.07.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.4% | 0.4% | 
-840030006: 2023.06.13 15:30 != 2023.06.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.4% | 0.4% | 
-840030006: 2023.05.10 15:30 != 2023.05.10 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.4% | 
-840030006: 2023.04.12 15:30 != 2023.04.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.5% | 
+840030006: 2023.03.14 14:30 == 2023.03.14 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.5% | 0.5% | 0.4% | 
-840030006: 2023.02.14 15:30 != 2023.02.14 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.3% | 0.4%
-840030006: 2023.01.12 15:30 != 2023.01.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.5% | 0.2% | 

OnStart > DST: true
-840030006: 2024.03.12 14:30 != 2024.03.12 13:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.3% | 0.4% | 
-840030006: 2024.02.13 15:30 != 2024.02.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.2% | 0.3% | 
-840030006: 2024.01.11 15:30 != 2024.01.11 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.3% | 0.3% | 
-840030006: 2023.12.12 15:30 != 2023.12.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.3% | 0.2% | 
-840030006: 2023.11.14 15:30 != 2023.11.14 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.3% | 0.3% | 
-840030006: 2023.10.12 15:30 != 2023.10.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.4% | 0.3% | 
-840030006: 2023.09.13 15:30 != 2023.09.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.4% | 0.2% | 
-840030006: 2023.08.10 15:30 != 2023.08.10 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.4% | 0.2% | 
-840030006: 2023.07.12 15:30 != 2023.07.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.2% | 0.4% | 0.4% | 
-840030006: 2023.06.13 15:30 != 2023.06.13 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.4% | 0.4% | 
-840030006: 2023.05.10 15:30 != 2023.05.10 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.4% | 
-840030006: 2023.04.12 15:30 != 2023.04.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.5% | 
-840030006: 2023.03.14 14:30 != 2023.03.14 13:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.5% | 0.5% | 0.4% | 
-840030006: 2023.02.14 15:30 != 2023.02.14 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.4% | 0.5% | 0.3% | 0.4%
-840030006: 2023.01.12 15:30 != 2023.01.12 14:30 USD 2 Core CPI m/m (consumer-price-index-ex-food-energy-mm), United States (US) | 0.3% | 0.5% | 0.2% |
fxsaber #:

Sembra che si tratti di un correttore di calendario che corrisponde al server commerciale.

Risultato.

Corrisponde al calendario Web. Se qualcuno vede delle discrepanze evidenti, me lo faccia sapere.

Ora sembra che sia corretto utilizzare il calendario per i backtest.

Leincongruenze sono visibili ovunque:

OnStart > DST: false
-840200001: 2024.03.06 15:30 != 2024.03.06 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.367 M | 4.491 M | 4.199 M | 
-840200001: 2024.02.28 15:30 != 2024.02.28 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 4.199 M | 3.930 M | 3.514 M | 
+840200001: 2024.02.22 17:00 == 2024.02.22 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 3.514 M | 6.807 M | 12.018 M | 
+840200001: 2024.02.14 16:30 == 2024.02.14 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 12.018 M | 3.392 M | 5.520 M | 
-840200001: 2024.02.07 17:30 != 2024.02.07 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 5.520 M | -3.716 M | 1.234 M | 
-840200001: 2024.01.31 15:30 != 2024.01.31 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.234 M | -6.860 M | -9.233 M | 
+840200001: 2024.01.24 16:30 == 2024.01.24 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -9.233 M | -0.744 M | -2.492 M | 
+840200001: 2024.01.18 17:00 == 2024.01.18 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -2.492 M | 4.112 M | 1.338 M | 
-840200001: 2024.01.10 17:30 != 2024.01.10 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.338 M | -2.280 M | -5.503 M | 
+840200001: 2024.01.04 17:00 == 2024.01.04 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -5.503 M | -2.499 M | -7.114 M | 

OnStart > DST: true
-840200001: 2024.03.06 15:30 != 2024.03.06 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.367 M | 4.491 M | 4.199 M | 
-840200001: 2024.02.28 15:30 != 2024.02.28 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 4.199 M | 3.930 M | 3.514 M | 
+840200001: 2024.02.22 17:00 == 2024.02.22 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 3.514 M | 6.807 M | 12.018 M | 
+840200001: 2024.02.14 16:30 == 2024.02.14 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 12.018 M | 3.392 M | 5.520 M | 
-840200001: 2024.02.07 17:30 != 2024.02.07 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 5.520 M | -3.716 M | 1.234 M | 
-840200001: 2024.01.31 15:30 != 2024.01.31 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.234 M | -6.860 M | -9.233 M | 
+840200001: 2024.01.24 16:30 == 2024.01.24 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -9.233 M | -0.744 M | -2.492 M | 
+840200001: 2024.01.18 17:00 == 2024.01.18 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -2.492 M | 4.112 M | 1.338 M | 
-840200001: 2024.01.10 17:30 != 2024.01.10 16:30 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | 1.338 M | -2.280 M | -5.503 M | 
+840200001: 2024.01.04 17:00 == 2024.01.04 17:00 USD 3 EIA Crude Oil Stocks Change (eia-crude-oil-stocks-change), United States (US) | -5.503 M | -2.499 M | -7.114 M |

//---

Verificate anche voi.

Anatoli Kazharski #:

Si osservanoincoerenze su tutta la linea

Non è possibile effettuare un confronto in base a 840200001-event, poiché ha una debole influenza sulle quotazioni - il tempo della colonna di sinistra potrebbe essere calcolato in modo errato.
fxsaber #:
Non è possibile effettuare un confronto in base a 840200001-event, perché ha una debole influenza sulle quotazioni - il tempo della colonna di sinistra potrebbe essere calcolato in modo errato.

Grazie, ho dato un'occhiata più da vicino e ho capito il metodo proposto.

Penso che in alcuni casi sarebbe più interessante esaminare un certo intervallo di tempo (prima e dopo l'evento) per vedere quanto è cambiato il prezzo.

Anatoli Kazharski #:

Si osservanoincoerenze

Dopo l'aggiornamento della libreria, il Calendario deve essere sincronizzato con la cronologia delle quotazioni di qualsiasi broker.


Controllo (eseguito su EURUSD).

#property script_show_inputs

input ulong inEventID = 840030016; // EventID (840030016 - Nonfarm Payrolls)
input datetime inFrom = D'2020.01.01';

// Dimensione della barra del tempo.
double GetBarSize( const datetime Time )
{
  MqlRates Rates[];
  
  return(CopyRates(_Symbol, PERIOD_M1, iBarShift(_Symbol, PERIOD_M1, Time), 1, Rates) != 1 ? 0 : Rates[0].high - Rates[0].low);
}

// Tempo della barra più grande per dimensione (in base al tempo dell'array).
datetime GetMaxBarSizeTime( const datetime &Times[] )
{
  double Values[];
  
  for (int i = ArrayResize(Values, ArraySize(Times)) - 1; i >= 0; i--)
    Values[i] = GetBarSize(Times[i]);
  
  return(Times[ArrayMaximum(Values)]);
}

// Momento più probabile di notizie sui dati di prezzo (forte reazione).
datetime ChartNewsTime( const datetime &Time )
{
  datetime Times[3];
      
  Times[0] = Time;
  Times[1] = Times[0] - 3600;
  Times[2] = Times[0] + 3600;
  
  return(GetMaxBarSizeTime(Times));
}

#include <fxsaber\Calendar\Calendar.mqh> // https://www.mql5.com/it/code/32430
#define  PRINT(A) Print(#A + " = " + (string)(A))

void OnStart()
{ 
  PRINT(AccountInfoString(ACCOUNT_SERVER));
  PRINT(TimeTradeServer());
  PRINT(DST::IsEurope());            // Regolamento europeo DST.
  PRINT(DST::GetRollover());         // Tempo di rollover.
  PRINT(DST::TimeServerGMTOffset()); // offset del server GMT.
  
  CALENDAR Calendar;
    
  Calendar.Set(inEventID);
  Calendar.FilterByTime(inFrom, TimeCurrent());
  
  Calendar.AutoDST();

  for (int i = Calendar.GetAmount() - 1; i >= 0; i--)
  {
    const EVENT Event = Calendar[i];    
    const datetime ChartNews = ChartNewsTime(Event.time);
    
    if (Event.time != ChartNews)    
      Print("-" + (string)Event.EventID + ": " + TimeToString(ChartNews) + " != " + Event.ToString());
    else
      Print("+" + (string)Event.EventID + ": " + TimeToString(ChartNews) + " == " + Event.ToString());
  }
}


Risultato.

AccountInfoString(ACCOUNT_SERVER) = RannForex-Server
TimeTradeServer() = 2024.03.14 09:26:54
DST::IsEurope() = 1
DST::GetRollover() = 2024.03.13 23:00:00
DST::TimeServerGMTOffset() = -7200
+840030016: 2024.03.08 15:30 == 2024.03.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 275 K | 220 K | 353 K | 229 K
+840030016: 2024.02.02 15:30 == 2024.02.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 353 K | 186 K | 216 K | 333 K
+840030016: 2024.01.05 15:30 == 2024.01.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 216 K | 1 K | 199 K | 173 K
+840030016: 2023.12.08 15:30 == 2023.12.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 199 K | -3 K | 150 K | 
+840030016: 2023.11.03 14:30 == 2023.11.03 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 150 K | -8 K | 336 K | 297 K
+840030016: 2023.10.06 15:30 == 2023.10.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 336 K | 1 K | 187 K | 227 K
+840030016: 2023.09.01 15:30 == 2023.09.01 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 187 K | 12 K | 187 K | 157 K
+840030016: 2023.08.04 15:30 == 2023.08.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 187 K | -1 K | 209 K | 185 K
+840030016: 2023.07.07 15:30 == 2023.07.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 209 K | -19 K | 339 K | 306 K
+840030016: 2023.06.02 15:30 == 2023.06.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 339 K | 1 K | 253 K | 294 K
+840030016: 2023.05.05 15:30 == 2023.05.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 253 K | 23 K | 236 K | 165 K
+840030016: 2023.04.07 15:30 == 2023.04.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 236 K | -8 K | 311 K | 326 K
+840030016: 2023.03.10 15:30 == 2023.03.10 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 311 K | -35 K | 517 K | 504 K
+840030016: 2023.02.03 15:30 == 2023.02.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 517 K | 16 K | 223 K | 260 K
+840030016: 2023.01.06 15:30 == 2023.01.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 223 K | 57 K | 263 K | 256 K
+840030016: 2022.12.02 15:30 == 2022.12.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | -30 K | 261 K | 284 K
+840030016: 2022.11.04 14:30 == 2022.11.04 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 261 K | -97 K | 263 K | 315 K
+840030016: 2022.10.07 15:30 == 2022.10.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 263 K | 33 K | 315 K | 
+840030016: 2022.09.02 15:30 == 2022.09.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 315 K | 156 K | 528 K | 526 K
+840030016: 2022.08.05 15:30 == 2022.08.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 528 K | -19 K | 372 K | 398 K
+840030016: 2022.07.08 15:30 == 2022.07.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 372 K | -229 K | 390 K | 384 K
+840030016: 2022.06.03 15:30 == 2022.06.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 390 K | -19 K | 428 K | 436 K
+840030016: 2022.05.06 15:30 == 2022.05.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 428 K | 317 K | 431 K | 428 K
+840030016: 2022.04.01 15:30 == 2022.04.01 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 431 K | 80 K | 678 K | 750 K
+840030016: 2022.03.04 15:30 == 2022.03.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 678 K | -413 K | 467 K | 481 K
+840030016: 2022.02.04 15:30 == 2022.02.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 467 K | -192 K | 199 K | 510 K
+840030016: 2022.01.07 15:30 == 2022.01.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 199 K | 379 K | 210 K | 249 K
+840030016: 2021.12.03 15:30 == 2021.12.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 210 K | 330 K | 531 K | 546 K
+840030016: 2021.11.05 14:30 == 2021.11.05 14:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 531 K | -54 K | 194 K | 312 K
+840030016: 2021.10.08 15:30 == 2021.10.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 194 K | -302 K | 235 K | 366 K
+840030016: 2021.09.03 15:30 == 2021.09.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 235 K | 23 K | 943 K | 1053 K
+840030016: 2021.08.06 15:30 == 2021.08.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 943 K | 381 K | 850 K | 938 K
+840030016: 2021.07.02 15:30 == 2021.07.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 850 K | 3 K | 559 K | 583 K
+840030016: 2021.06.04 15:30 == 2021.06.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 559 K | -396 K | 266 K | 278 K
+840030016: 2021.05.07 15:30 == 2021.05.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 266 K | -1 K | 916 K | 770 K
+840030016: 2021.04.02 15:30 == 2021.04.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 916 K | 409 K | 379 K | 468 K
+840030016: 2021.03.05 15:30 == 2021.03.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 379 K | -137 K | 49 K | 166 K
+840030016: 2021.02.05 15:30 == 2021.02.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 49 K | -497 K | -140 K | -227 K
+840030016: 2021.01.08 15:30 == 2021.01.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -140 K | 207 K | 245 K | 336 K
+840030016: 2020.12.04 15:30 == 2020.12.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 245 K | 528 K | 638 K | 610 K
+840030016: 2020.11.06 15:30 == 2020.11.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 638 K | -76324 K | 661 K | 672 K
-840030016: 2020.10.02 16:30 != 2020.10.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 661 K | 78356 K | 1371 K | 1489 K
+840030016: 2020.09.04 15:30 == 2020.09.04 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1371 K | -74433 K | 1763 K | 1734 K
+840030016: 2020.08.07 15:30 == 2020.08.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 1763 K | 4511 K | 4800 K | 4791 K
+840030016: 2020.07.02 15:30 == 2020.07.02 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 4800 K | -12034 K | 2509 K | 2699 K
+840030016: 2020.06.05 15:30 == 2020.06.05 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 2509 K | -10000 K | -20500 K | -20687 K
+840030016: 2020.05.08 15:30 == 2020.05.08 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -20500 K | 139 K | -701 K | -870 K
+840030016: 2020.04.03 15:30 == 2020.04.03 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | -701 K | 163 K | 273 K | 275 K
+840030016: 2020.03.06 15:30 == 2020.03.06 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 273 K | 161 K | 225 K | 273 K
+840030016: 2020.02.07 15:30 == 2020.02.07 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 225 K | 161 K | 145 K | 147 K
+840030016: 2020.01.10 15:30 == 2020.01.10 15:30 USD 3 Nonfarm Payrolls (nonfarm-payrolls), United States (US) | 145 K | 168 K | 266 K | 256 K


Sarà necessario verificare la correttezza durante la mancata sincronizzazione autunnale Europa/USA.

Ora è possibile utilizzare il calendario nei backtest (l'EA di esempio in dotazione è stato aggiornato).


ZY Vi consiglio di dare un'occhiata ai lavori di questo autore.

amrali
amrali
  • www.mql5.com
Trader's profile 
  static int TimeServerGMTOffset( void )
  {
    MqlCalendarValue Value[1];

    ::CalendarValueHistoryByEvent(840030016, Value, D'2023.09.01', D'2023.09.02');

    // EVENT::CorrectTime(Value[0].time);

    return((-3 + (24 - DST::GetHour(Value[0].time - 31 * HOUR / 2)) % 24) * HOUR);
  }

Ho un brutto presentimento sulla correttezza di questa funzione.

Utilizzando i limiti del calcolo: l'intervallo di uscita per (x % 24) è da 0 a 23, quindi l'intervallo di uscita della funzione è da -3 a 20. Pertanto un server di -5 non può essere rappresentato.

amrali #:

Ho un brutto presentimento sulla correttezza di questa funzione.

Utilizzando i limiti del calcolo: l'intervallo di uscita per (x % 24) è da 0 a 23, quindi l'intervallo di uscita della funzione è da -3 a 20. Pertanto un server di -5 non può essere rappresentato.

Avete ragione, grazie.

sottrarre direttamente da 12:30 (invece di -3 + 31*/2):

int TimeServerGMTOffset(void)
  {
   MqlCalendarValue Value[1];

   ::CalendarValueHistoryByEvent(840030016, Value, D'2023.09.01', D'2023.09.02');

   return((int)(D'2023.09.01 12:30' - Value[0].time));
  }
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