optimize trade strategy
This commit is contained in:
parent
1e204839a9
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@ -0,0 +1,29 @@
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import schedule
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import time
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import datetime
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import core.logger as logging
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import subprocess
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import os
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logger = logging.logger
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# 定义要执行的任务
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def run_script():
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start_time = time.time()
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logger.info(f"Executing script at: {datetime.datetime.now()}")
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output_file = r'./output/auto_schedule.txt'
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with open(output_file, 'a') as f:
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f.write(f"Task ran at {datetime.datetime.now()}\n")
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python_path = r"D:\miniconda3\envs\okx\python.exe"
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script_path = r"D:\python_projects\crypto_quant\huge_volume_main.py"
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subprocess.run([python_path, script_path])
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end_time = time.time()
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logger.info(f"Script execution time: {end_time - start_time} seconds")
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# 设置每小时运行一次
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interval = 60 * 60
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schedule.every(interval).seconds.do(run_script)
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# 保持程序运行并检查调度
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logger.info("Scheduler started. Press Ctrl+C to stop.")
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while True:
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schedule.run_pending()
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time.sleep(1)
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@ -171,9 +171,9 @@ class MaBreakStatistics:
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ma_cross = str(ma_cross)
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buy_condition = False
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if all_change:
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buy_condition = (ma5 > ma10 and ma10 > ma20 and ma20 > ma30) and (close > ma20)
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buy_condition = (ma_cross == "5上穿10") and (ma5 > ma10 and ma10 > ma20 and ma20 > ma30) and (close > ma20)
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else:
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buy_condition = ma_cross == "5上穿10" and (ma5 > ma10)
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buy_condition = (ma_cross == "5上穿10") and (ma5 > ma10)
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if buy_condition:
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ma_break_market_data_pair = {}
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ma_break_market_data_pair["symbol"] = symbol
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Binary file not shown.
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@ -4,7 +4,7 @@ import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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import seaborn as sns
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from datetime import datetime
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from datetime import datetime, timedelta
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import re
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from openpyxl import Workbook
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from openpyxl.drawing.image import Image
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@ -45,21 +45,22 @@ class MeanReversionSandbox:
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desc_dict = {
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"买入": [
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"1. 窗口周期为100, 即100个K线",
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"2. 当前low_10_low为1, 即当前最低价格在窗口周期的10分位以下",
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"2. 当前close_10_low为1, 即当前收盘价在窗口周期的10分位以下",
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"3. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量",
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"4. 当前K线为阳线, 即close > open",
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"4. 当前K线为阳线, 即close > open或者K线为一字, 长倒T线, 倒T线, 长十字星, 十字星",
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# "5. 相同symbol的1H当前周期, ma5大于ma10",
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# "5. KDJ, RSI, BOLL任意一个指标出现超卖",
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],
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"止损": ["跌幅超过下跌周期跌幅中位数, 即down_median后卖出"],
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"止盈": {
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"solution_1": [
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"高位放量止盈 - 简易版",
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"1. 当前high_80_high为1或者high_90_high为1",
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"1. 当前close_80_high为1或者close_90_high为1",
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"2. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量",
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],
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"solution_2": [
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"高位放量止盈 - 复杂版",
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"前提条件"
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"1. 当前high_80_high为1或者high_90_high为1",
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"前提条件" "1. 当前close_80_high为1或者close_90_high为1",
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"2. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量",
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"以下两个条件, 任一满足即可",
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"1. K线为阴线, 即close < open",
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@ -68,9 +69,10 @@ class MeanReversionSandbox:
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],
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"solution_3": [
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"上涨波段盈利中位数止盈法",
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"1. 超过波段中位数涨幅, 即up_median后, 记录当前价格, 继续持仓",
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"1. 超过波段中位数涨幅, 即up_median/ 到达价位90分位/ 任意技术指标出现中度超卖, 记录当前价格, 继续持仓",
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"2. 之后一个周期, 如果价格上涨, 则记录该价格继续持仓",
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"3. 之后一个周期, 如果价格跌到记录价格之下, 则卖出",
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"4. 如果买入时ma5小于ma10, 过程中ma5大于ma10, 进行记录。之后出现ma5小于ma10, 则卖出",
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],
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},
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}
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@ -160,7 +162,8 @@ class MeanReversionSandbox:
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trade_pair_dict["buy_huge_volume"] = row["huge_volume"]
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trade_pair_dict["buy_volume_ratio"] = row["volume_ratio"]
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trade_pair_dict["buy_k_shape"] = row["k_shape"]
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trade_pair_dict["buy_low_10_low"] = row["low_10_low"]
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trade_pair_dict["buy_close_10_low"] = row["close_10_low"]
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trade_pair_dict["buy_ma5_lt_ma10"] = row["ma5"] < row["ma10"]
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continue
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if trade_pair_dict.get("buy_timestamp", None) is not None:
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@ -188,22 +191,27 @@ class MeanReversionSandbox:
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trade_pair_dict["sell_huge_volume"] = row["huge_volume"]
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trade_pair_dict["sell_volume_ratio"] = row["volume_ratio"]
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trade_pair_dict["sell_k_shape"] = row["k_shape"]
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trade_pair_dict["sell_high_80_high"] = row["high_80_high"]
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trade_pair_dict["sell_high_90_high"] = row["high_90_high"]
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trade_pair_dict["sell_low_10_low"] = row["low_10_low"]
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trade_pair_dict["sell_low_20_low"] = row["low_20_low"]
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trade_pair_dict["sell_close_80_high"] = row["close_80_high"]
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trade_pair_dict["sell_close_90_high"] = row["close_90_high"]
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trade_pair_dict["sell_close_10_low"] = row["close_10_low"]
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trade_pair_dict["sell_close_20_low"] = row["close_20_low"]
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trade_pair_dict["profit_pct"] = round(
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(trade_pair_dict["sell_close"] - trade_pair_dict["buy_close"])
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/ trade_pair_dict["buy_close"]
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* 100,
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4,
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)
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if trade_pair_dict["sell_type"] == "止盈" and trade_pair_dict["profit_pct"] < 0:
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if trade_pair_dict["profit_pct"] <= 0:
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trade_pair_dict["sell_type"] = "止损"
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else:
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trade_pair_dict["sell_type"] = "止盈"
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if trade_pair_dict.get("last_max_close", None) is not None:
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# remove last_max_close
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trade_pair_dict.pop("last_max_close")
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if trade_pair_dict.get("process_ma5_gt_ma10", None) is not None:
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trade_pair_dict.pop("process_ma5_gt_ma10")
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trade_list.append(trade_pair_dict)
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trade_pair_dict = {}
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@ -219,30 +227,75 @@ class MeanReversionSandbox:
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):
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"""
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买入条件
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1. 窗口周期为100, 即100个K线
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2. 当前low_10_low为1, 即当前最低价格在窗口周期的10分位以下
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3. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量
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4. 当前K线为阳线, 即close > open
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5. TODO: 考虑K线形态
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1. 窗口周期为100, 即100个K线,
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2. 当前close_10_low为1, 即当前收盘价在窗口周期的10分位以下,
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3. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量,
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4. (当前K线为阳线, 即close > open)或者K线为一字, 长倒T线, 倒T线, 长十字星, 十字星,
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"""
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if index < 2:
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return False
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if row["close"] <= row["open"]:
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if row["close"] <= row["open"] and row["k_shape"] not in [
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"一字",
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"长倒T线",
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"倒T线",
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"长十字星",
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"十字星",
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]:
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return False
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if row["low_10_low"] != 1:
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if row["close_10_low"] != 1:
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return False
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# 如果当前与前两个K线，huge_volume都不为1，则返回False
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# 如果当前与前两个K线, huge_volume都不为1, 则返回False
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if (
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row["huge_volume"] != 1
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and market_data.loc[index - 1, "huge_volume"] != 1
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and market_data.loc[index - 2, "huge_volume"] != 1
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):
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return False
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logger.info(f"符合买入条件")
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# if not self.check_metrics_over_sell(row):
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# return False
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# latest_1h_data = self.get_latest_1h_data(row["symbol"], row["date_time"])
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# if latest_1h_data is None or len(latest_1h_data) == 0:
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# logger.info(f"符合买入条件")
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# return True
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# # 当前小时周期的ma5小于ma10, 表明空头趋势, 则返回False
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# elif (
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# not pd.isna(latest_1h_data["ma5"])
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# and not pd.isna(latest_1h_data["ma10"])
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# and latest_1h_data["ma5"] < latest_1h_data["ma10"]
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# ):
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# # logger.info(f"当前小时周期的ma5小于ma10, 空头趋势, 不符合买入条件")
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# return False
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# else:
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# logger.info(f"符合买入条件")
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# return True
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return True
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def get_latest_1h_data(self, symbol: str, current_date_time: str):
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bar = "1H"
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# 根据current_date_time, 获取当前时间往前推1H的日期时间,
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# 如当前时间为2025-08-20 10:20:05, 则获取2025-08-20 09:00:00
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before_date_time = datetime.strptime(current_date_time, "%Y-%m-%d %H:%M:%S")
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before_date_time = before_date_time - timedelta(hours=1)
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# current_date_time取整数小时，如2025-08-20 10:20:05, 取2025-08-20 10:00:00
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before_date_time = before_date_time.replace(minute=0, second=0, microsecond=0)
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before_date_time = before_date_time.strftime("%Y-%m-%d %H:%M:%S")
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end_date_time = datetime.strptime(current_date_time, "%Y-%m-%d %H:%M:%S")
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end_date_time = end_date_time.replace(minute=0, second=0, microsecond=0)
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end_date_time = end_date_time - timedelta(seconds=1)
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end_date_time = end_date_time.strftime("%Y-%m-%d %H:%M:%S")
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latest_1h_data = self.db_merge_market_huge_volume.merge_market_huge_volume(
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symbol, bar, 100, before_date_time, end_date_time
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)
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if latest_1h_data is None or len(latest_1h_data) == 0:
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return None
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# 只获取第一行数据
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latest_1h_data = latest_1h_data.iloc[0]
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return latest_1h_data
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def check_stop_loss_condition(self, trade_pair_dict: dict, row: pd.Series):
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symbol = trade_pair_dict["symbol"]
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bar = trade_pair_dict["bar"]
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@ -282,9 +335,7 @@ class MeanReversionSandbox:
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market_data, row, index
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)
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elif self.solution == "solution_3":
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return self.check_take_profit_condition_solution_3(
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trade_pair_dict, row
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)
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return self.check_take_profit_condition_solution_3(trade_pair_dict, row)
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else:
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raise ValueError(f"Invalid strategy name: {self.solution}")
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except Exception as e:
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@ -299,10 +350,10 @@ class MeanReversionSandbox:
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):
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"""
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高位放量止盈 - 简易版
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1. 当前high_80_high为1或者high_90_high为1
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1. 当前close_80_high为1或者close_90_high为1
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2. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量
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"""
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if row["high_80_high"] != 1 and row["high_90_high"] != 1:
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if row["close_80_high"] != 1 and row["close_90_high"] != 1:
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return False
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if (
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row["huge_volume"] != 1
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@ -322,7 +373,7 @@ class MeanReversionSandbox:
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"""
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高位放量止盈 - 复杂版
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前提条件
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1. 当前high_80_high为1或者high_90_high为1
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1. 当前close_80_high为1或者close_90_high为1
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2. 之前2个K线与当前K线, 存在任意一个K线huge_volume为1, 即存在一个K线是巨量
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以下两个条件, 任一满足即可
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1. K线为阴线, 即close < open
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@ -334,25 +385,46 @@ class MeanReversionSandbox:
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if row["close"] < row["open"]:
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logger.info(f"符合高位放量止盈 - 复杂版条件")
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return True
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elif row["k_shape"] in ["一字", "长吊锤线", "吊锤线", "长倒T线", "倒T线", "长十字星", "十字星", "长上影线纺锤体", "长下影线纺锤体"]:
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elif row["k_shape"] in [
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"一字",
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"长吊锤线",
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"吊锤线",
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"长倒T线",
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"倒T线",
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"长十字星",
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"十字星",
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"长上影线纺锤体",
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"长下影线纺锤体",
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]:
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logger.info(f"符合高位放量止盈 - 复杂版条件")
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return True
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else:
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return False
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def check_take_profit_condition_solution_3(
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self,
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trade_pair_dict: dict,
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row: pd.Series
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self, trade_pair_dict: dict, row: pd.Series
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):
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"""
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上涨波段盈利中位数止盈法
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1. 超过波段中位数涨幅, 即up_median后, 记录当前价格, 继续持仓
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上涨波段盈利阶段止盈法
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1. 超过波段中位数涨幅, 即up_median/ 到达价位90分位/ 任意技术指标出现中度超卖, 记录当前价格, 继续持仓
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2. 之后一个周期, 如果价格上涨, 则记录该价格继续持仓
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3. 之后一个周期, 如果价格跌到记录价格之下, 则卖出
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4. 如果买入时ma5小于ma10, 过程中ma5大于ma10, 进行记录。之后出现ma5小于ma10, 则卖出
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"""
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current_close = row["close"]
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last_max_close = trade_pair_dict.get("last_max_close", None)
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if trade_pair_dict["buy_ma5_lt_ma10"]:
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if trade_pair_dict.get("process_ma5_gt_ma10", None):
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if row["ma5"] < row["ma10"]:
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logger.info(f"MA5小于MA10发生转势, 卖出")
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return True
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if row["ma5"] > row["ma10"]:
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trade_pair_dict["process_ma5_gt_ma10"] = True
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else:
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trade_pair_dict["process_ma5_gt_ma10"] = False
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if last_max_close is not None:
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if current_close >= last_max_close:
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logger.info(f"价格上涨, 继续持仓")
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@ -373,9 +445,72 @@ class MeanReversionSandbox:
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/ 100
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)
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need_record = False
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buy_close = trade_pair_dict["buy_close"]
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price_chg = (current_close - buy_close) / buy_close
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if price_chg > up_median:
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logger.info(f"当前价格上涨超过波段中位数涨幅, 记录当前价格")
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need_record = True
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elif self.check_metrics_over_buy(row):
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logger.info(f"技术指标超买, 记录当前价格")
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need_record = True
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elif row["close_90_high"] == 1:
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logger.info(f"到达价位90分位, 记录当前价格")
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need_record = True
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else:
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need_record = False
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if need_record:
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trade_pair_dict["last_max_close"] = current_close
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return False
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def check_metrics_over_buy(self, row: pd.Series):
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"""
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检查技术指标是否出现中度超买
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KDJ
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K：85.00
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D：80.00
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J：100.00
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说明：K 和 D 进一步上升, J 显著高于100, 表示超买加剧, 回调概率增加, 但可能仍需确认。
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RSI 14
|
||||
RSI：80.00
|
||||
说明：RSI 进一步上升, 超买程度加深, 市场可能接近短期顶部, 回调概率增加。
|
||||
BOLL
|
||||
价格位置：价格突破上轨, 偏离上轨约 +2.00%（即价格 = 上轨 × 1.02）
|
||||
说明：价格显著突破上轨, 超买程度加深, 可能预示短期回调或反转
|
||||
"""
|
||||
if row["kdj_k"] > 85 and row["kdj_d"] > 80 and row["kdj_j"] > 100:
|
||||
logger.info(f"KDJ超买")
|
||||
return True
|
||||
if row["rsi_14"] > 80:
|
||||
logger.info(f"RSI超买")
|
||||
return True
|
||||
if row["boll_upper"] * 1.02 < row["close"]:
|
||||
logger.info(f"BOLL超买")
|
||||
return True
|
||||
return False
|
||||
|
||||
def check_metrics_over_sell(self, row: pd.Series):
|
||||
"""
|
||||
检查技术指标是否出现超卖
|
||||
KDJ
|
||||
K: 25.00
|
||||
D: 30.00
|
||||
J: 20.00
|
||||
|
||||
RSI 14
|
||||
RSI:30.00
|
||||
说明: RSI 进一步下降, 超卖程度加深, 市场可能接近短期底部, 反弹概率增加。
|
||||
|
||||
BOLL
|
||||
价格位置: 价格接近下轨
|
||||
"""
|
||||
if row["kdj_k"] < 25 and row["kdj_d"] < 30 and row["kdj_j"] < 20:
|
||||
logger.info(f"KDJ超卖")
|
||||
return True
|
||||
if row["rsi_14"] < 30:
|
||||
logger.info(f"RSI超卖")
|
||||
return True
|
||||
if row["boll_lower"] >= row["close"]:
|
||||
logger.info(f"BOLL超卖")
|
||||
return True
|
||||
return False
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
okx>=2.1.2
|
||||
python-okx >= 0.3.9
|
||||
pandas>=2.0.0
|
||||
requests>=2.25.0
|
||||
sqlalchemy >= 2.0.41
|
||||
|
|
@ -6,3 +7,6 @@ pymysql >= 1.1.1
|
|||
wechatpy >= 1.8.18
|
||||
seaborn >= 0.13.2
|
||||
schedule >= 1.2.2
|
||||
xlsxwriter >= 3.2.5
|
||||
openpyxl >= 3.1.5
|
||||
cryptography >= 3.4.8
|
||||
|
|
@ -23,14 +23,21 @@ logger = logging.logger
|
|||
|
||||
|
||||
class MeanReversionSandboxMain:
|
||||
def __init__(self, start_date: str, end_date: str, window_size: int):
|
||||
def __init__(self, start_date: str, end_date: str, window_size: int, only_5m: bool = False, solution_list: list = None):
|
||||
self.symbols = MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"symbols", ["XCH-USDT"]
|
||||
)
|
||||
self.bars = MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"bars", ["5m", "15m", "30m", "1H"]
|
||||
)
|
||||
self.solution_list = ["solution_1", "solution_2", "solution_3"]
|
||||
self.only_5m = only_5m
|
||||
if only_5m:
|
||||
self.bars = ["5m"]
|
||||
else:
|
||||
self.bars = MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"bars", ["5m", "15m", "30m", "1H"]
|
||||
)
|
||||
if solution_list is None:
|
||||
self.solution_list = ["solution_1", "solution_2", "solution_3"]
|
||||
else:
|
||||
self.solution_list = solution_list
|
||||
self.start_date = start_date
|
||||
self.end_date = end_date
|
||||
self.window_size = window_size
|
||||
|
|
@ -176,8 +183,13 @@ class MeanReversionSandboxMain:
|
|||
sheet_name = f"{solution}_chart"
|
||||
chart_dict[sheet_name] = {}
|
||||
for y_axis_field in y_axis_fields:
|
||||
# 绘制2x2的画布
|
||||
fig, axs = plt.subplots(2, 2, figsize=(10, 10))
|
||||
if self.only_5m:
|
||||
fig, axs = plt.subplots(1, 1, figsize=(10, 10))
|
||||
# 当只有一个子图时，将axs包装成数组以便统一处理
|
||||
axs = np.array([[axs]])
|
||||
else:
|
||||
# 绘制2x2的画布
|
||||
fig, axs = plt.subplots(2, 2, figsize=(10, 10))
|
||||
for j, bar in enumerate(bars_in_order):
|
||||
ax = axs[j // 2, j % 2]
|
||||
bar_data = stat_data[stat_data["bar"] == bar].copy()
|
||||
|
|
@ -191,6 +203,21 @@ class MeanReversionSandboxMain:
|
|||
palette=colors,
|
||||
ax=ax,
|
||||
)
|
||||
|
||||
# 在柱子上方添加数值标签
|
||||
for i, (idx, row) in enumerate(bar_data.iterrows()):
|
||||
value = row[y_axis_field]
|
||||
# 根据数值类型格式化标签
|
||||
if "ratio" in y_axis_field:
|
||||
label = f"{value:.2f}%"
|
||||
else:
|
||||
label = f"{value:.4f}"
|
||||
|
||||
# 在柱子上方显示数值
|
||||
ax.text(i, value, label,
|
||||
ha='center', va='bottom',
|
||||
fontsize=9, fontweight='bold')
|
||||
|
||||
ax.set_ylabel(y_axis_field)
|
||||
ax.set_xlabel("symbol")
|
||||
ax.set_title(f"{solution} {bar}")
|
||||
|
|
@ -203,9 +230,10 @@ class MeanReversionSandboxMain:
|
|||
label.set_horizontalalignment("right")
|
||||
# 隐藏未使用的subplot
|
||||
total_used = len(bars_in_order)
|
||||
for k in range(total_used, 4):
|
||||
ax = axs[k // 2, k % 2]
|
||||
ax.axis("off")
|
||||
if not self.only_5m:
|
||||
for k in range(total_used, 4):
|
||||
ax = axs[k // 2, k % 2]
|
||||
ax.axis("off")
|
||||
fig.tight_layout()
|
||||
file_name = f"{solution}_{y_axis_field}.png"
|
||||
fig.savefig(os.path.join(save_path, file_name))
|
||||
|
|
@ -271,7 +299,8 @@ class MeanReversionSandboxMain:
|
|||
if __name__ == "__main__":
|
||||
start_date = "2025-05-15 00:00:00"
|
||||
end_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
solution_list = ["solution_3"]
|
||||
mean_reversion_sandbox_main = MeanReversionSandboxMain(
|
||||
start_date=start_date, end_date=end_date, window_size=100
|
||||
start_date=start_date, end_date=end_date, window_size=100, only_5m=True, solution_list=solution_list
|
||||
)
|
||||
mean_reversion_sandbox_main.batch_mean_reversion_sandbox()
|
||||
|
|
|
|||
Loading…
Reference in New Issue