FórumSeções

Bibliotecas: Calendário - página 10

Novo comentário

Sobre a relevância dos dados do calendário.


Para comparação, o trabalho de outra fonte.

A biblioteca foi atualizada para permitir a modificação de eventos. 
#include <fxsaber\Calendar\Calendar.mqh> // https://www.mql5.com/pt/code/32430

void OnStart()
{
  CALENDAR Calendar;
  
  const string Currencies[] = {SymbolInfoString(_Symbol, SYMBOL_CURRENCY_BASE),
                               SymbolInfoString(_Symbol, SYMBOL_CURRENCY_PROFIT)};
  
  // Anotou os próximos eventos importantes por moedas de símbolo.
  Calendar.Set(Currencies);
  
  Print(Calendar.ToString()); // Imprimiu-os.
  
  EVENT Events[];
  
  if (Calendar.GetEvents(Events) > 0) // Obteve todos os eventos em formato interno.
  {    
    Events[0].Importance = (ENUM_CALENDAR_EVENT_IMPORTANCE)27; // Alterou a importância do evento.

    Calendar = Events; // Colocar eventos no calendário.
    
    Print(Calendar.ToString()); // Imprimiu-os.
  }
}


Resultado.

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 |

Fórum sobre negociação, sistemas de negociação automatizados e teste de estratégias de negociação

Bibliotecas: Calendário

fxsaber, 2023.04.13 00:07 pm.

Parece que consegui um corretor de calendário que corresponde ao servidor de negociação.

#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(); // Ignorar as peculiaridades do calendário MQL: https://www.mql5.com/ru/forum/444094/page14#comment_46213385
    
    if (inDST)
      Calendar.DST(); // Chamada se o servidor de negociação estiver sincronizado com o horário europeu.
  
    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 // Obter EventID por nome.
  {
    string Currencies[2];
    
    // Obter as moedas do caractere atual.
    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());
  }
}


Resultado.

+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

Corresponde ao calendário da Web. Se alguém vir alguma inconsistência óbvia, me avise.

Agora parece ser correto usar o calendário para backtests.

Obtive este resultado:

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 #:

Parece que se trata de um corretor de calendário que corresponde ao servidor de comércio.

Resultado.

Corresponde ao calendário da Web. Se alguém vir alguma discrepância óbvia, me avise.

Agora parece ser correto usar o calendário para backtests.

As inconsistências são vistas em todos os lugares:

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 |

//---

Verifique isso você também.

Anatoli Kazharski #:

Inconsistências são observadas em toda a linha

Não é possível comparar por 840200001-event, pois ele tem uma influência fraca nas cotações - o tempo da coluna esquerda pode estar sendo calculado incorretamente.
fxsaber #:
Você não pode comparar por 840200001-event, porque ele tem uma influência fraca nas cotações - o tempo da coluna da esquerda pode ser calculado incorretamente.

Obrigado, dei uma olhada mais de perto e entendi o método proposto.

Acho que, em alguns casos, seria mais interessante observar um determinado intervalo de tempo (antes e depois do evento) para ver o quanto o preço mudou.

Anatoli Kazharski #:

São observadasinconsistências

Após a atualização da biblioteca, o Calendar deve ser sincronizado com o histórico de cotações em qualquer corretora.


Verificação (execução em EURUSD).

#property script_show_inputs

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

// Tamanho da barra de 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 da maior barra por tamanho (por tempo da matriz).
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)]);
}

// Tempo mais provável de notícias sobre dados de preços (forte reação).
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/pt/code/32430
#define  PRINT(A) Print(#A + " = " + (string)(A))

void OnStart()
{ 
  PRINT(AccountInfoString(ACCOUNT_SERVER));
  PRINT(TimeTradeServer());
  PRINT(DST::IsEurope());            // Regulamento europeu de DST.
  PRINT(DST::GetRollover());         // Tempo de rolagem.
  PRINT(DST::TimeServerGMTOffset()); // Deslocamento do servidor 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());
  }
}


Resultado.

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


Será necessário verificar a exatidão durante a dessincronização da Europa/EUA no outono.

Agora você pode usar o calendário em backtests (o exemplo de EA na entrega foi atualizado).


ZY, recomendo que você dê uma olhada nos trabalhos desse autor.

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);
  }

Tenho um mau pressentimento sobre a exatidão dessa função.

Usando os limites do cálculo: o intervalo de saída de (x % 24) é de 0 a 23, portanto, o intervalo de saída da função é de -3 a 20. Portanto, um servidor de -5 não pode ser representado.

amrali #:

Tenho um mau pressentimento sobre a exatidão dessa função.

Usando os limites do cálculo: o intervalo de saída de (x % 24) é de 0 a 23, portanto, o intervalo de saída da função é de -3 a 20. Portanto, um servidor de -5 não pode ser representado.

Você está certo, obrigado.

subtrair diretamente de 12:30 (em vez de -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));
  }
1...3456789101112131415
Novo comentário