程序库: 日历

fxsaber 2023.09.21 09:37 #91

关于日历数据的相关性。

另一资料来源的作品可供比较。

fxsaber 2024.03.05 11:25 #92

该库已更新，允许对事件进行修改。

#include <fxsaber\Calendar\Calendar.mqh> //https://www.mql5.com/zh/code/32430

void OnStart()
{
  CALENDAR Calendar;
  
  const string Currencies[] = {SymbolInfoString(_Symbol, SYMBOL_CURRENCY_BASE),
                               SymbolInfoString(_Symbol, SYMBOL_CURRENCY_PROFIT)};
  
  // 按符号货币显示即将发生的重要事件。
  Calendar.Set(Currencies);
  
  Print(Calendar.ToString()); // 打印出来。
  
  EVENT Events[];
  
  if (Calendar.GetEvents(Events) > 0) // 获取所有内部格式的事件。
  {    
    Events[0].Importance = (ENUM_CALENDAR_EVENT_IMPORTANCE)27; // 改变了事件的重要性。

    Calendar = Events; // 把事件放到日历上。
    
    Print(Calendar.ToString()); // 打印出来。
  }
}

结果

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 |

Anatoli Kazharski 2024.03.13 13:05 #93

关于交易、自动交易系统和交易策略测试的论坛

图书馆：日历

fxsaber, 2023.04.13 00:07 pm.

看来我得到了一个与交易服务器匹配的日历校正器。

#property script_show_inputs

input ulong inEventID = 840030006; // 事件 ID
input string inName = ""; // 名称 -> 事件 ID（非农就业人数 -> 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(); // 绕过 MQL 日历的特殊性： https://www.mql5.com/ru/forum/444094/page14#comment_46213385
    
    if (inDST)
      Calendar.DST(); // 如果交易服务器与欧洲时间同步，则调用。
  
    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 // 根据名称获取事件 ID。
  {
    string Currencies[2];
    
    // 获取当前字符的货币。
    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());
  }
}

结果。

+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

与网络日历匹配。如果有人发现任何明显的不一致，请告诉我。

现在看来，使用日历进行回溯测试是正确的。

结果如下

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% |

Anatoli Kazharski 2024.03.13 13:37 #94

fxsaber #:

看来，它是一个与贸易服务器匹配的日历校正器。

结果。

与网络日历匹配。如果有人发现任何明显的差异，请告诉我。

现在看来，使用日历进行回溯测试是正确的。

不一致的地方比比皆是：

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 |

//---

也请您自己检查一下。

fxsaber 2024.03.13 13:47 #95

Anatoli Kazharski #:

全面观察到不一致之处

无法按 840200001-event 进行比较，因为它对报价的影响较弱 - 左栏时间的计算可能有误。

Anatoli Kazharski 2024.03.13 14:10 #96

fxsaber #:
您不能通过 840200001-event 进行比较，因为它对报价的影响较弱--左栏的时间可能计算错误。

谢谢，我仔细看了一下，理解了建议的方法。

我认为在某些情况下，查看某个时间范围（事件发生前后）的价格变化会更有意思。

fxsaber 2024.03.14 08:31 #97

Anatoli Kazharski #:

观察到不一致之处

更新库后，日历应与任何经纪商的报价历史同步。

检查（在欧元兑美元上运行）。

#property script_show_inputs

input ulong inEventID = 840030016; // 事件 ID（840030016 - 非农就业数据）
input datetime inFrom = D'2020.01.01';

// 时间条大小。
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);
}

// 最大条形的时间（按数组中的时间）。
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)]);
}

// 最有可能出现价格数据新闻的时间（反应强烈）。
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/zh/code/32430
#define  PRINT(A) Print(#A + " = " + (string)(A))

void OnStart()
{ 
  PRINT(AccountInfoString(ACCOUNT_SERVER));
  PRINT(TimeTradeServer());
  PRINT(DST::IsEurope());            // 欧洲 DST 条例。
  PRINT(DST::GetRollover());         // 翻转时间。
  PRINT(DST::TimeServerGMTOffset()); // GMT 服务器偏移量。
  
  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());
  }
}

结果。

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

有必要在秋季欧洲/美国不同步期间检查正确性。

现在您可以在回溯测试中使用日历（交付中的示例 EA 已更新）。

ZY 我建议您看看这位作者的作品。

amrali

www.mql5.com

Trader's profile

amrali 2024.03.14 14:03 #98

  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);
  }

我对这个函数的正确性有一种不祥的预感。

利用微积分中的极限：(x % 24) 的输出范围是 0 至 23，因此函数的输出范围是 -3 至 20。

fxsaber 2024.03.14 17:02 #99

amrali #:

我对这个函数的正确性有一种不祥的预感。

利用微积分中的极限：(x % 24) 的输出范围是 0 至 23，因此函数的输出范围是 -3 至 20。

您说得对，谢谢。

amrali 2024.03.15 11:11 #100

直接从 12:30 减去（而不是 -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));
  }

程序库: 日历 - 页 10