diff --git a/core/trade/__pycache__/ma_break_statistics.cpython-312.pyc b/core/trade/__pycache__/ma_break_statistics.cpython-312.pyc index ad1c914..a61593f 100644 Binary files a/core/trade/__pycache__/ma_break_statistics.cpython-312.pyc and b/core/trade/__pycache__/ma_break_statistics.cpython-312.pyc differ diff --git a/core/trade/__pycache__/orb_trade.cpython-313.pyc b/core/trade/__pycache__/orb_trade.cpython-313.pyc new file mode 100644 index 0000000..dc103f0 Binary files /dev/null and b/core/trade/__pycache__/orb_trade.cpython-313.pyc differ diff --git a/core/trade/ma_break_statistics.py b/core/trade/ma_break_statistics.py index 8721002..5bdd774 100644 --- a/core/trade/ma_break_statistics.py +++ b/core/trade/ma_break_statistics.py @@ -4,7 +4,7 @@ import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns -from datetime import datetime +from datetime import datetime, timedelta import re import json from openpyxl import Workbook @@ -12,8 +12,9 @@ from openpyxl.drawing.image import Image import openpyxl from openpyxl.styles import Font from PIL import Image as PILImage -from config import OKX_MONITOR_CONFIG, US_STOCK_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE +from config import OKX_MONITOR_CONFIG, US_STOCK_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE, BINANCE_MONITOR_CONFIG from core.db.db_market_data import DBMarketData +from core.db.db_binance_data import DBBinanceData from core.db.db_huge_volume_data import DBHugeVolumeData from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp @@ -32,7 +33,7 @@ class MaBreakStatistics: 之间的涨跌幅 """ - def __init__(self, is_us_stock: bool = False): + def __init__(self, is_us_stock: bool = False, is_binance: bool = False): mysql_user = MYSQL_CONFIG.get("user", "xch") mysql_password = MYSQL_CONFIG.get("password", "") if not mysql_password: @@ -42,28 +43,45 @@ class MaBreakStatistics: mysql_database = MYSQL_CONFIG.get("database", "okx") self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}" - self.db_market_data = DBMarketData(self.db_url) + self.db_huge_volume_data = DBHugeVolumeData(self.db_url) + self.is_us_stock = is_us_stock + self.is_binance = is_binance if is_us_stock: self.symbols = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get( "symbols", ["QQQ"] ) - else: - self.symbols = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( - "symbols", ["XCH-USDT"] - ) - if is_us_stock: self.bars = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get( "bars", ["5m"] ) + self.initial_date = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get( + "initial_date", "2014-11-30 00:00:00" + ) + self.db_market_data = DBMarketData(self.db_url) else: - self.bars = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( - "bars", ["5m", "15m", "30m", "1H"] - ) - self.stats_output_dir = "./output/trade_sandbox/ma_strategy/excel/" - os.makedirs(self.stats_output_dir, exist_ok=True) - self.stats_chart_dir = "./output/trade_sandbox/ma_strategy/chart/" - os.makedirs(self.stats_chart_dir, exist_ok=True) + if is_binance: + self.symbols = BINANCE_MONITOR_CONFIG.get("volume_monitor", {}).get( + "symbols", ["BTC-USDT"] + ) + self.bars = ["30m", "1H"] + self.initial_date = BINANCE_MONITOR_CONFIG.get("volume_monitor", {}).get( + "initial_date", "2017-08-16 00:00:00" + ) + self.db_market_data = DBBinanceData(self.db_url) + else: + self.symbols = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( + "symbols", ["XCH-USDT"] + ) + self.bars = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( + "bars", ["5m", "15m", "30m", "1H"] + ) + self.initial_date = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( + "initial_date", "2025-05-15 00:00:00" + ) + self.db_market_data = DBMarketData(self.db_url) + if len(self.initial_date) > 10: + self.initial_date = self.initial_date[:10] + self.end_date = datetime.now().strftime("%Y-%m-%d") self.trade_strategy_config = self.get_trade_strategy_config() self.main_strategy = self.trade_strategy_config.get("均线系统策略", None) @@ -73,14 +91,18 @@ class MaBreakStatistics: return trade_strategy_config def batch_statistics(self, strategy_name: str = "全均线策略"): - self.stats_output_dir = ( - f"./output/trade_sandbox/ma_strategy/excel/{strategy_name}/" - ) + if self.is_us_stock: + self.stats_output_dir = f"./output/trade_sandbox/ma_strategy/us_stock/excel/{strategy_name}/" + self.stats_chart_dir = f"./output/trade_sandbox/ma_strategy/us_stock/chart/{strategy_name}/" + elif self.is_binance: + self.stats_output_dir = f"./output/trade_sandbox/ma_strategy/binance/excel/{strategy_name}/" + self.stats_chart_dir = f"./output/trade_sandbox/ma_strategy/binance/chart/{strategy_name}/" + else: + self.stats_output_dir = f"./output/trade_sandbox/ma_strategy/okx/excel/{strategy_name}/" + self.stats_chart_dir = f"./output/trade_sandbox/ma_strategy/okx/chart/{strategy_name}/" os.makedirs(self.stats_output_dir, exist_ok=True) - self.stats_chart_dir = ( - f"./output/trade_sandbox/ma_strategy/chart/{strategy_name}/" - ) os.makedirs(self.stats_chart_dir, exist_ok=True) + ma_break_market_data_list = [] market_data_pct_chg_list = [] if strategy_name not in self.main_strategy.keys() or strategy_name is None: @@ -276,16 +298,11 @@ class MaBreakStatistics: return strategy_info_df def trade_simulate(self, symbol: str, bar: str, strategy_name: str = "全均线策略"): - market_data = self.db_market_data.query_market_data_by_symbol_bar( - symbol, bar, start=None, end=None - ) + market_data = self.get_full_data(symbol, bar) if market_data is None or len(market_data) == 0: logger.warning(f"获取{symbol} {bar} 数据失败") return None, None else: - market_data = pd.DataFrame(market_data) - market_data.sort_values(by="timestamp", ascending=True, inplace=True) - market_data.reset_index(drop=True, inplace=True) logger.info(f"获取{symbol} {bar} 数据成功，数据条数: {len(market_data)}") # 获得ma5, ma10, ma20, ma30不为空的行 market_data = market_data[ @@ -299,7 +316,7 @@ class MaBreakStatistics: ) # 计算volume_ma5 market_data["volume_ma5"] = market_data["volume"].rolling(window=5).mean() - # 获得5上穿10且ma5 > ma10 > ma20 > ma30且close > ma20的行,成交量较前5日均量放大20%以上 + market_data["volume_pct_chg"] = ( market_data["volume"] - market_data["volume_ma5"] ) / market_data["volume_ma5"] @@ -311,9 +328,14 @@ class MaBreakStatistics: market_data.reset_index(drop=True, inplace=True) ma_break_market_data_pair_list = [] ma_break_market_data_pair = {} + if self.is_us_stock: + date_time_field = "date_time_us" + else: + date_time_field = "date_time" for index, row in market_data.iterrows(): ma_cross = row["ma_cross"] timestamp = row["timestamp"] + date_time = row[date_time_field] close = row["close"] ma5 = row["ma5"] ma10 = row["ma10"] @@ -336,9 +358,7 @@ class MaBreakStatistics: ma_break_market_data_pair["symbol"] = symbol ma_break_market_data_pair["bar"] = bar ma_break_market_data_pair["begin_timestamp"] = timestamp - ma_break_market_data_pair["begin_date_time"] = ( - timestamp_to_datetime(timestamp) - ) + ma_break_market_data_pair["begin_date_time"] = date_time ma_break_market_data_pair["begin_close"] = close ma_break_market_data_pair["begin_ma5"] = ma5 ma_break_market_data_pair["begin_ma10"] = ma10 @@ -358,9 +378,7 @@ class MaBreakStatistics: if sell_condition: ma_break_market_data_pair["end_timestamp"] = timestamp - ma_break_market_data_pair["end_date_time"] = ( - timestamp_to_datetime(timestamp) - ) + ma_break_market_data_pair["end_date_time"] = date_time ma_break_market_data_pair["end_close"] = close ma_break_market_data_pair["end_ma5"] = ma5 ma_break_market_data_pair["end_ma10"] = ma10 @@ -411,6 +429,59 @@ class MaBreakStatistics: return ma_break_market_data, market_data_pct_chg else: return None, None + + def get_full_data(self, symbol: str, bar: str = "5m"): + """ + 分段获取数据，并将数据合并为完整数据 + 分段依据：如果end_date与start_date相差超过一年，则每次取一年数据 + """ + data = pd.DataFrame() + start_date = datetime.strptime(self.initial_date, "%Y-%m-%d") + end_date = datetime.strptime(self.end_date, "%Y-%m-%d") + timedelta(days=1) + fields = [ + "symbol", + "bar", + "timestamp", + "date_time", + "date_time_us", + "open", + "high", + "low", + "close", + "volume", + "sar_signal", + "ma5", + "ma10", + "ma20", + "ma30", + "ma_cross", + "dif", + "dea", + "macd", + ] + while start_date < end_date: + current_end_date = min(start_date + timedelta(days=180), end_date) + start_date_str = start_date.strftime("%Y-%m-%d") + current_end_date_str = current_end_date.strftime("%Y-%m-%d") + logger.info( + f"获取{symbol}数据：{start_date_str}至{current_end_date_str}" + ) + current_data = self.db_market_data.query_market_data_by_symbol_bar( + symbol, bar, fields, start=start_date_str, end=current_end_date_str + ) + if current_data is not None and len(current_data) > 0: + current_data = pd.DataFrame(current_data) + data = pd.concat([data, current_data]) + start_date = current_end_date + data.drop_duplicates(inplace=True) + if self.is_us_stock: + date_time_field = "date_time_us" + else: + date_time_field = "date_time" + data.sort_values(by=date_time_field, inplace=True) + data.reset_index(drop=True, inplace=True) + return data + def fit_strategy( self, @@ -734,12 +805,12 @@ class MaBreakStatistics: # 设置x轴标签 plt.xticks(symbol_bar_data["end_date_time"].iloc[label_indices], - symbol_bar_data["end_date_time"].iloc[label_indices].dt.strftime('%m-%d %H:%M'), + symbol_bar_data["end_date_time"].iloc[label_indices].dt.strftime('%Y%m%d %H:%M'), rotation=45, ha='right') else: # 如果数据点较少，全部显示 plt.xticks(symbol_bar_data["end_date_time"], - symbol_bar_data["end_date_time"].dt.strftime('%m-%d %H:%M'), + symbol_bar_data["end_date_time"].dt.strftime('%Y%m%d %H:%M'), rotation=45, ha='right') plt.tight_layout() diff --git a/orb_trade_main.py b/orb_trade_main.py index 9360c37..8ac38e3 100644 --- a/orb_trade_main.py +++ b/orb_trade_main.py @@ -28,11 +28,20 @@ def main(): else: start_date = "2024-01-01" end_date = datetime.now().strftime("%Y-%m-%d") + + # 原值 盈利目标倍数（默认10倍$R，即10R） profit_target_multiple = 10 + # 新值 盈利目标倍数（默认20倍$R，即10R） -- 20250909 + # profit_target_multiple = 20 + initial_capital = 25000 max_leverage = 4 risk_per_trade = 0.01 - commission_per_share = 0.0005 + # if is_us_stock: + # commission_per_share = 0.0005 + # else: + # commission_per_share = 0 + # commission_per_share = 0 trades_df_list = [] trades_summary_df_list = [] @@ -47,6 +56,7 @@ def main(): symbols = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get( "symbols", ["QQQ"] ) + commission_per_share = 0.0005 else: if is_binance: symbols = BINANCE_MONITOR_CONFIG.get("volume_monitor", {}).get( @@ -56,6 +66,7 @@ def main(): symbols = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get( "symbols", ["BTC-USDT"] ) + commission_per_share = 0 for symbol in symbols: logger.info( f"开始回测 {symbol}, 交易周期:{bar}, 开始日期:{start_date}, 结束日期:{end_date}, 是否是美股:{is_us_stock}, 交易方向:{direction}, 是否使用SAR:{by_sar}, 是否使用R为entry减stop:{price_range_mean_as_R}, 是否使用K线实体过50%:{by_big_k}" diff --git a/trade_ma_strategy_main.py b/trade_ma_strategy_main.py index 927c85a..338c2fa 100644 --- a/trade_ma_strategy_main.py +++ b/trade_ma_strategy_main.py @@ -25,8 +25,8 @@ from config import ( logger = logging.logger class TradeMaStrategyMain: - def __init__(self, is_us_stock: bool = False): - self.ma_break_statistics = MaBreakStatistics(is_us_stock=is_us_stock) + def __init__(self, is_us_stock: bool = False, is_binance: bool = False): + self.ma_break_statistics = MaBreakStatistics(is_us_stock=is_us_stock, is_binance=is_binance) def batch_ma_break_statistics(self): """ @@ -36,8 +36,10 @@ class TradeMaStrategyMain: strategy_dict = self.ma_break_statistics.main_strategy pct_chg_df_list = [] for strategy_name, strategy_info in strategy_dict.items(): - pct_chg_df = self.ma_break_statistics.batch_statistics(strategy_name=strategy_name) - pct_chg_df_list.append(pct_chg_df) + if "macd" in strategy_name: + # 只计算macd策略 + pct_chg_df = self.ma_break_statistics.batch_statistics(strategy_name=strategy_name) + pct_chg_df_list.append(pct_chg_df) pct_chg_df = pd.concat(pct_chg_df_list) @@ -59,5 +61,5 @@ class TradeMaStrategyMain: if __name__ == "__main__": - trade_ma_strategy_main = TradeMaStrategyMain(is_us_stock=True) + trade_ma_strategy_main = TradeMaStrategyMain(is_us_stock=False, is_binance=True) trade_ma_strategy_main.batch_ma_break_statistics() \ No newline at end of file