support quant by A market
This commit is contained in:
parent
f3b98bcc22
commit
11c6e25490
49
config.py
49
config.py
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@ -134,6 +134,43 @@ US_STOCK_MONITOR_CONFIG = {
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}
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}
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A_STOCK_MONITOR_CONFIG = {
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"volume_monitor": {
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"symbols": [
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"600276.SH",
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"002714.SZ",
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"600111.SH",
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"603019.SH",
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"600036.SH",
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"300474.SZ",
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"600519.SH",
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"300750.SZ",
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"000858.SZ",
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"000651.SZ",
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"000333.SZ",
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"002230.SZ",
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"300308.SZ",
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"002475.SZ"
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],
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"bars": ["1D", "1W", "1M"],
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"initial_date": "2015-01-01 00:00:00",
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},
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}
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A_INDEX_MONITOR_CONFIG = {
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"volume_monitor": {
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"symbols": [
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"000001.SH",
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"399006.SZ",
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"000300.SH",
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"399001.SZ",
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"000852.SH",
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],
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"bars": ["1D", "1W", "1M"],
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"initial_date": "2015-01-01 00:00:00",
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},
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}
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WINDOW_SIZE = {"window_sizes": [50, 80, 100, 120]}
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BAR_THRESHOLD = {
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@ -146,7 +183,7 @@ BAR_THRESHOLD = {
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"1D": 1000 * 60 * 60 * 24,
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}
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# MYSQL_CONFIG = {
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# COIN_MYSQL_CONFIG = {
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# "host": "localhost",
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# "port": 3306,
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# "user": "xch",
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@ -154,7 +191,7 @@ BAR_THRESHOLD = {
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# "database": "okx",
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# }
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MYSQL_CONFIG = {
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COIN_MYSQL_CONFIG = {
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"host": "218.17.89.43",
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"port": 11013,
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"user": "xch",
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@ -162,6 +199,14 @@ MYSQL_CONFIG = {
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"database": "okx",
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}
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A_MYSQL_CONFIG = {
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"host": "43.139.95.249",
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"port": 3306,
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"user": "root",
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"password": "bengbu_200!",
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"database": "astock",
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}
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WECHAT_CONFIG = {
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"general_key": "11e6f7ac-efa9-418a-904c-9325a9f5d324",
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"btc_key": "529e135d-843b-43dc-8aca-677a860f4b4b",
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Binary file not shown.
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@ -0,0 +1,125 @@
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import pandas as pd
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from sqlalchemy import create_engine, exc, text
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import re
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from core.utils import get_current_date_time
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import core.logger as logging
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from core.utils import transform_data_type
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logger = logging.logger
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class DBAStockData:
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def __init__(
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self,
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db_url: str,
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):
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self.db_url = db_url
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self.db_engine = create_engine(
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self.db_url,
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pool_size=25, # 连接池大小
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max_overflow=10, # 允许的最大溢出连接
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pool_timeout=30, # 连接超时时间（秒）
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pool_recycle=60, # 连接回收时间（秒），避免长时间闲置
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)
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def query_data(self, sql: str, condition_dict: dict, return_multi: bool = True):
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"""
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查询数据
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:param sql: 查询SQL
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:param db_url: 数据库连接URL
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"""
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try:
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with self.db_engine.connect() as conn:
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result = conn.execute(text(sql), condition_dict)
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if return_multi:
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result = result.fetchall()
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if result:
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result_list = [
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transform_data_type(dict(row._mapping)) for row in result
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]
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return result_list
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else:
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return None
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else:
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result = result.fetchone()
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if result:
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result_dict = transform_data_type(dict(result._mapping))
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return result_dict
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else:
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return None
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except Exception as e:
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logger.error(f"查询数据出错: {e}")
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return None
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def query_market_data_by_symbol_bar(
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self,
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symbol: str,
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bar: str,
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fields: list = None,
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start: str = None,
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end: str = None,
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table_name: str = "index_daily_price_from_2021",
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):
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"""
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根据交易对和K线周期查询数据
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:param symbol: 交易对
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:param bar: K线周期
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:param fields: 字段列表
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:param start: 开始时间
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:param end: 结束时间
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"""
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if fields is None:
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fields = ["*"]
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fields_str = ", ".join(fields)
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if table_name is None:
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table_name = "index_daily_price_from_2021"
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join_table = "all_index"
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if table_name.startswith("index"):
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join_table = "all_index"
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else:
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join_table = "all_stock"
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if start is None and end is None:
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sql = f"""
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SELECT {fields_str} FROM {table_name} a
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INNER JOIN {join_table} b ON a.ts_code = b.ts_code
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WHERE a.ts_code = :symbol
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ORDER BY a.trade_date ASC
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"""
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condition_dict = {"symbol": symbol}
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else:
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if start is not None and end is not None:
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start = start.replace("-", "")
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end = end.replace("-", "")
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if start > end:
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start, end = end, start
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sql = f"""
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SELECT {fields_str} FROM {table_name} a
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INNER JOIN {join_table} b ON a.ts_code = b.ts_code
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WHERE a.ts_code = :symbol AND a.trade_date BETWEEN :start AND :end
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ORDER BY a.trade_date ASC
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"""
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condition_dict = {
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"symbol": symbol,
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"start": start,
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"end": end,
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}
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elif start is not None:
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start = start.replace("-", "")
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sql = f"""
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SELECT {fields_str} FROM {table_name} a
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INNER JOIN {join_table} b ON a.ts_code = b.ts_code
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WHERE a.ts_code = :symbol AND a.trade_date >= :start
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ORDER BY a.trade_date ASC
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"""
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condition_dict = {"symbol": symbol, "start": start}
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elif end is not None:
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end = end.replace("-", "")
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sql = f"""
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SELECT {fields_str} FROM {table_name} a
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INNER JOIN {join_table} b ON a.ts_code = b.ts_code
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WHERE a.ts_code = :symbol AND a.trade_date <= :end
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ORDER BY a.trade_date ASC
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"""
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condition_dict = {"symbol": symbol, "end": end}
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return self.query_data(sql, condition_dict, return_multi=True)
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@ -480,6 +480,7 @@ class DBBinanceData:
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fields: list = None,
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start: str = None,
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end: str = None,
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table_name: str = "crypto_binance_data",
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):
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"""
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根据交易对和K线周期查询数据
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@ -494,7 +495,7 @@ class DBBinanceData:
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fields_str = ", ".join(fields)
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if start is None and end is None:
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sql = f"""
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SELECT {fields_str} FROM crypto_binance_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar
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ORDER BY timestamp ASC
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"""
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@ -514,7 +515,7 @@ class DBBinanceData:
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if start > end:
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start, end = end, start
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sql = f"""
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SELECT {fields_str} FROM crypto_binance_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar AND timestamp BETWEEN :start AND :end
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ORDER BY timestamp ASC
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"""
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@ -526,14 +527,14 @@ class DBBinanceData:
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}
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elif start is not None:
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sql = f"""
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SELECT {fields_str} FROM crypto_binance_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar AND timestamp >= :start
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ORDER BY timestamp ASC
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"""
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condition_dict = {"symbol": symbol, "bar": bar, "start": start}
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elif end is not None:
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sql = f"""
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SELECT {fields_str} FROM crypto_binance_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar AND timestamp <= :end
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ORDER BY timestamp ASC
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"""
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@ -7,68 +7,65 @@ logger = logging.logger
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class DBMarketData:
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def __init__(
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self,
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db_url: str
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):
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def __init__(self, db_url: str):
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self.db_url = db_url
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self.table_name = "crypto_market_data"
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self.columns = [
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"symbol",
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"bar",
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"timestamp",
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"date_time",
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"date_time_us",
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"open",
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"high",
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"low",
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"close",
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"pre_close",
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"close_change",
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"pct_chg",
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"volume",
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"volCcy",
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"volCCyQuote",
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"buy_sz",
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"sell_sz",
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# 技术指标字段
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"ma1",
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"ma2",
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"dif",
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"dea",
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"macd",
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"macd_signal",
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"macd_divergence",
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"kdj_k",
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"kdj_d",
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"kdj_j",
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"kdj_signal",
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"kdj_pattern",
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"sar",
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"sar_signal",
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"ma5",
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"ma10",
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"ma20",
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"ma30",
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"ma_cross",
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"ma5_close_diff",
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"ma10_close_diff",
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"ma20_close_diff",
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"ma30_close_diff",
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"ma_close_avg",
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"ma_long_short",
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"ma_divergence",
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"rsi_14",
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"rsi_signal",
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"boll_upper",
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"boll_middle",
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"boll_lower",
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"boll_signal",
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"boll_pattern",
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"k_length",
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"k_shape",
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"k_up_down",
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"create_time",
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"symbol",
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"bar",
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"timestamp",
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"date_time",
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"date_time_us",
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"open",
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"high",
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"low",
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"close",
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"pre_close",
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"close_change",
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"pct_chg",
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"volume",
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"volCcy",
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"volCCyQuote",
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"buy_sz",
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"sell_sz",
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# 技术指标字段
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"ma1",
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"ma2",
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"dif",
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"dea",
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"macd",
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"macd_signal",
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"macd_divergence",
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"kdj_k",
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"kdj_d",
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"kdj_j",
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"kdj_signal",
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"kdj_pattern",
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"sar",
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"sar_signal",
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"ma5",
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"ma10",
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"ma20",
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"ma30",
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"ma_cross",
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"ma5_close_diff",
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"ma10_close_diff",
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"ma20_close_diff",
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"ma30_close_diff",
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"ma_close_avg",
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"ma_long_short",
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"ma_divergence",
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"rsi_14",
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"rsi_signal",
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"boll_upper",
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"boll_middle",
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"boll_lower",
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"boll_signal",
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"boll_pattern",
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"k_length",
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"k_shape",
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"k_up_down",
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"create_time",
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]
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self.db_manager = DBData(db_url, self.table_name, self.columns)
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@ -143,7 +140,9 @@ class DBMarketData:
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condition_dict = {"symbol": symbol, "bar": bar}
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return self.db_manager.query_data(sql, condition_dict, return_multi=False)
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def query_data_before_timestamp(self, symbol: str, bar: str, timestamp: int, limit: int = 100):
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def query_data_before_timestamp(
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self, symbol: str, bar: str, timestamp: int, limit: int = 100
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):
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"""
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根据时间戳查询之前的数据
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:param symbol: 交易对
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@ -157,7 +156,12 @@ class DBMarketData:
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ORDER BY timestamp DESC
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LIMIT :limit
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"""
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condition_dict = {"symbol": symbol, "bar": bar, "timestamp": timestamp, "limit": limit}
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condition_dict = {
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"symbol": symbol,
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"bar": bar,
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"timestamp": timestamp,
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"limit": limit,
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}
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def query_data_by_technical_indicators(
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@ -170,7 +174,7 @@ class DBMarketData:
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kdj_signal: str = None,
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rsi_signal: str = None,
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boll_signal: str = None,
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ma_cross: str = None
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ma_cross: str = None,
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):
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"""
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根据技术指标查询数据
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@ -230,7 +234,7 @@ class DBMarketData:
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bar: str,
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signal: str = None,
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start: str = None,
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end: str = None
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end: str = None,
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):
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"""
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查询MACD信号数据
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@ -275,7 +279,7 @@ class DBMarketData:
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signal: str = None,
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pattern: str = None,
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start: str = None,
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end: str = None
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end: str = None,
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):
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"""
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查询KDJ信号数据
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@ -325,7 +329,7 @@ class DBMarketData:
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long_short: str = None,
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divergence: str = None,
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start: str = None,
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end: str = None
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end: str = None,
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):
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"""
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查询均线信号数据
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@ -378,7 +382,7 @@ class DBMarketData:
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signal: str = None,
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pattern: str = None,
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start: str = None,
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end: str = None
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end: str = None,
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):
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"""
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查询布林带信号数据
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@ -421,11 +425,7 @@ class DBMarketData:
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return self.db_manager.query_data(sql, condition_dict, return_multi=True)
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def get_technical_statistics(
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self,
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symbol: str,
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bar: str,
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start: str = None,
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end: str = None
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self, symbol: str, bar: str, start: str = None, end: str = None
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):
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"""
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获取技术指标统计信息
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@ -473,7 +473,15 @@ class DBMarketData:
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return self.db_manager.query_data(sql, condition_dict, return_multi=False)
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def query_market_data_by_symbol_bar(self, symbol: str, bar: str, fields: list = None, start: str = None, end: str = None):
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def query_market_data_by_symbol_bar(
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self,
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symbol: str,
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bar: str,
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fields: list = None,
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start: str = None,
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end: str = None,
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table_name: str = "crypto_market_data",
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):
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"""
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根据交易对和K线周期查询数据
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:param symbol: 交易对
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|
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@ -487,7 +495,7 @@ class DBMarketData:
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fields_str = ", ".join(fields)
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if start is None and end is None:
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sql = f"""
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SELECT {fields_str} FROM crypto_market_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar
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ORDER BY timestamp ASC
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"""
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@ -507,21 +515,26 @@ class DBMarketData:
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if start > end:
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start, end = end, start
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sql = f"""
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SELECT {fields_str} FROM crypto_market_data
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SELECT {fields_str} FROM {table_name}
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WHERE symbol = :symbol AND bar = :bar AND timestamp BETWEEN :start AND :end
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ORDER BY timestamp ASC
|
||||
"""
|
||||
condition_dict = {"symbol": symbol, "bar": bar, "start": start, "end": end}
|
||||
condition_dict = {
|
||||
"symbol": symbol,
|
||||
"bar": bar,
|
||||
"start": start,
|
||||
"end": end,
|
||||
}
|
||||
elif start is not None:
|
||||
sql = f"""
|
||||
SELECT {fields_str} FROM crypto_market_data
|
||||
SELECT {fields_str} FROM {table_name}
|
||||
WHERE symbol = :symbol AND bar = :bar AND timestamp >= :start
|
||||
ORDER BY timestamp ASC
|
||||
"""
|
||||
condition_dict = {"symbol": symbol, "bar": bar, "start": start}
|
||||
elif end is not None:
|
||||
sql = f"""
|
||||
SELECT {fields_str} FROM crypto_market_data
|
||||
SELECT {fields_str} FROM {table_name}
|
||||
WHERE symbol = :symbol AND bar = :bar AND timestamp <= :end
|
||||
ORDER BY timestamp ASC
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ 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, MYSQL_CONFIG, WINDOW_SIZE
|
||||
from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
|
||||
from core.db.db_market_data import DBMarketData
|
||||
from core.db.db_huge_volume_data import DBHugeVolumeData
|
||||
from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
|
||||
|
|
@ -25,13 +25,13 @@ logger = logging.logger
|
|||
|
||||
class PriceVolumeStats:
|
||||
def __init__(self):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_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)
|
||||
|
|
|
|||
Binary file not shown.
|
|
@ -17,11 +17,16 @@ from PIL import Image as PILImage
|
|||
from config import (
|
||||
OKX_MONITOR_CONFIG,
|
||||
US_STOCK_MONITOR_CONFIG,
|
||||
MYSQL_CONFIG,
|
||||
COIN_MYSQL_CONFIG,
|
||||
A_MYSQL_CONFIG,
|
||||
WINDOW_SIZE,
|
||||
BINANCE_MONITOR_CONFIG,
|
||||
A_STOCK_MONITOR_CONFIG,
|
||||
A_INDEX_MONITOR_CONFIG,
|
||||
)
|
||||
from core.biz.metrics_calculation import MetricsCalculation
|
||||
from core.db.db_market_data import DBMarketData
|
||||
from core.db.db_astock import DBAStockData
|
||||
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
|
||||
|
|
@ -44,21 +49,40 @@ class MaBreakStatistics:
|
|||
def __init__(
|
||||
self,
|
||||
is_us_stock: bool = False,
|
||||
is_binance: bool = False,
|
||||
is_astock: bool = False,
|
||||
is_aindex: bool = False,
|
||||
is_binance: bool = True,
|
||||
buy_by_long_period: dict = {"by_week": False, "by_month": False},
|
||||
long_period_condition: dict = {"ma5>ma10": True, "ma10>ma20": False, "macd_diff>0": True, "macd>0": True},
|
||||
commission_per_share: float = 0.0008,
|
||||
):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
if is_astock or is_aindex:
|
||||
mysql_user = A_MYSQL_CONFIG.get("user", "root")
|
||||
mysql_password = A_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = A_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = A_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = A_MYSQL_CONFIG.get("database", "astock")
|
||||
else:
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
|
||||
self.db_huge_volume_data = DBHugeVolumeData(self.db_url)
|
||||
self.is_us_stock = is_us_stock
|
||||
self.is_astock = is_astock
|
||||
self.is_aindex = is_aindex
|
||||
if self.is_us_stock:
|
||||
self.date_time_field = "date_time_us"
|
||||
else:
|
||||
self.date_time_field = "date_time"
|
||||
self.is_binance = is_binance
|
||||
if is_us_stock:
|
||||
self.symbols = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
|
|
@ -71,6 +95,28 @@ class MaBreakStatistics:
|
|||
"initial_date", "2014-11-30 00:00:00"
|
||||
)
|
||||
self.db_market_data = DBMarketData(self.db_url)
|
||||
elif is_astock:
|
||||
self.symbols = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"symbols", ["000001.SH"]
|
||||
)
|
||||
self.bars = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"bars", ["5m"]
|
||||
)
|
||||
self.initial_date = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"initial_date", "2014-11-30 00:00:00"
|
||||
)
|
||||
self.db_market_data = DBAStockData(self.db_url)
|
||||
elif is_aindex:
|
||||
self.symbols = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"symbols", ["000001.SH"]
|
||||
)
|
||||
self.bars = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"bars", ["5m"]
|
||||
)
|
||||
self.initial_date = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"initial_date", "2014-11-30 00:00:00"
|
||||
)
|
||||
self.db_market_data = DBAStockData(self.db_url)
|
||||
else:
|
||||
if is_binance:
|
||||
self.symbols = BINANCE_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
|
|
@ -98,12 +144,36 @@ class MaBreakStatistics:
|
|||
self.commission_per_share = commission_per_share
|
||||
self.trade_strategy_config = self.get_trade_strategy_config()
|
||||
self.main_strategy = self.trade_strategy_config.get("均线系统策略", None)
|
||||
self.buy_by_long_period = buy_by_long_period
|
||||
self.long_period_condition = long_period_condition
|
||||
|
||||
def get_trade_strategy_config(self):
|
||||
with open("./json/trade_strategy.json", "r", encoding="utf-8") as f:
|
||||
trade_strategy_config = json.load(f)
|
||||
return trade_strategy_config
|
||||
|
||||
def get_by_long_period_desc(self):
|
||||
by_week = self.buy_by_long_period.get("by_week", False)
|
||||
by_month = self.buy_by_long_period.get("by_month", False)
|
||||
by_long_period = ""
|
||||
if by_week:
|
||||
by_long_period += "1W"
|
||||
if by_month:
|
||||
by_long_period += "1M"
|
||||
if by_long_period == "":
|
||||
return "no_long_period_judge"
|
||||
by_condition = ""
|
||||
if self.long_period_condition.get("ma5>ma10", False):
|
||||
by_condition += "ma5gtma10"
|
||||
if self.long_period_condition.get("ma10>ma20", False):
|
||||
by_condition += "_ma10gtma20"
|
||||
if self.long_period_condition.get("macd_diff>0", False):
|
||||
by_condition += "_macd_diffgt0"
|
||||
if self.long_period_condition.get("macd>0", False):
|
||||
by_condition += "_macdgt0"
|
||||
return by_long_period + "_" + by_condition
|
||||
|
||||
|
||||
def batch_statistics(self, strategy_name: str = "全均线策略"):
|
||||
if self.is_us_stock:
|
||||
self.stats_output_dir = (
|
||||
|
|
@ -119,6 +189,38 @@ class MaBreakStatistics:
|
|||
self.stats_chart_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/binance/chart/{strategy_name}/"
|
||||
)
|
||||
elif self.is_astock:
|
||||
long_period_desc = self.get_by_long_period_desc()
|
||||
if len(long_period_desc) > 0:
|
||||
self.stats_output_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/astock/{long_period_desc}/excel/{strategy_name}/"
|
||||
)
|
||||
self.stats_chart_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/astock/{long_period_desc}/chart/{strategy_name}/"
|
||||
)
|
||||
else:
|
||||
self.stats_output_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/astock/excel/{strategy_name}/"
|
||||
)
|
||||
self.stats_chart_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/astock/chart/{strategy_name}/"
|
||||
)
|
||||
elif self.is_aindex:
|
||||
long_period_desc = self.get_by_long_period_desc()
|
||||
if len(long_period_desc) > 0:
|
||||
self.stats_output_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/aindex/{long_period_desc}/excel/{strategy_name}/"
|
||||
)
|
||||
self.stats_chart_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/aindex/{long_period_desc}/chart/{strategy_name}/"
|
||||
)
|
||||
else:
|
||||
self.stats_output_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/aindex/excel/{strategy_name}/"
|
||||
)
|
||||
self.stats_chart_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/aindex/chart/{strategy_name}/"
|
||||
)
|
||||
else:
|
||||
self.stats_output_dir = (
|
||||
f"./output/trade_sandbox/ma_strategy/okx/excel/{strategy_name}/"
|
||||
|
|
@ -192,9 +294,11 @@ class MaBreakStatistics:
|
|||
total_commission = round(total_commission, 4)
|
||||
total_buy_commission = round(total_buy_commission, 4)
|
||||
total_sell_commission = round(total_sell_commission, 4)
|
||||
symbol_name = str(symbol_bar_data["symbol_name"].iloc[0])
|
||||
account_value_chg_list.append({
|
||||
"strategy_name": strategy_name,
|
||||
"symbol": symbol,
|
||||
"symbol_name": symbol_name,
|
||||
"bar": bar,
|
||||
"total_buy_commission": total_buy_commission,
|
||||
"total_sell_commission": total_sell_commission,
|
||||
|
|
@ -209,6 +313,7 @@ class MaBreakStatistics:
|
|||
[
|
||||
"strategy_name",
|
||||
"symbol",
|
||||
"symbol_name",
|
||||
"bar",
|
||||
"total_buy_commission",
|
||||
"total_sell_commission",
|
||||
|
|
@ -221,7 +326,7 @@ class MaBreakStatistics:
|
|||
]
|
||||
|
||||
account_value_statistics_df = (
|
||||
ma_break_market_data.groupby(["symbol", "bar"])["end_account_value"]
|
||||
ma_break_market_data.groupby(["symbol", "symbol_name", "bar"])["end_account_value"]
|
||||
.agg(
|
||||
account_value_max="max",
|
||||
account_value_min="min",
|
||||
|
|
@ -237,6 +342,7 @@ class MaBreakStatistics:
|
|||
[
|
||||
"strategy_name",
|
||||
"symbol",
|
||||
"symbol_name",
|
||||
"bar",
|
||||
"account_value_max",
|
||||
"account_value_min",
|
||||
|
|
@ -249,7 +355,7 @@ class MaBreakStatistics:
|
|||
|
||||
# 依据symbol和bar分组，统计每个symbol和bar的interval_minutes的max, min, mean, std, median, count
|
||||
interval_minutes_df = (
|
||||
ma_break_market_data.groupby(["symbol", "bar"])["interval_minutes"]
|
||||
ma_break_market_data.groupby(["symbol", "symbol_name", "bar"])["interval_minutes"]
|
||||
.agg(
|
||||
interval_minutes_max="max",
|
||||
interval_minutes_min="min",
|
||||
|
|
@ -265,6 +371,7 @@ class MaBreakStatistics:
|
|||
[
|
||||
"strategy_name",
|
||||
"symbol",
|
||||
"symbol_name",
|
||||
"bar",
|
||||
"interval_minutes_max",
|
||||
"interval_minutes_min",
|
||||
|
|
@ -335,6 +442,23 @@ class MaBreakStatistics:
|
|||
strategy_info["买入策略"] = buy_and_text + " 或者 \n" + buy_or_text
|
||||
else:
|
||||
strategy_info["买入策略"] = buy_and_text
|
||||
|
||||
# 假如根据长周期判断买入，则需要设置长周期策略
|
||||
by_week = self.buy_by_long_period.get("by_week", False)
|
||||
by_month = self.buy_by_long_period.get("by_month", False)
|
||||
if by_week:
|
||||
strategy_info["买入策略"] += "根据周线指标，\n"
|
||||
if by_month:
|
||||
strategy_info["买入策略"] += "根据月线指标，\n"
|
||||
if self.long_period_condition.get("ma5>ma10", False):
|
||||
strategy_info["买入策略"] += "ma5>ma10, \n"
|
||||
if self.long_period_condition.get("ma10>ma20", False):
|
||||
strategy_info["买入策略"] += "ma10>ma20, \n"
|
||||
if self.long_period_condition.get("macd_diff>0", False):
|
||||
strategy_info["买入策略"] += "macd_diff>0, \n"
|
||||
if self.long_period_condition.get("macd>0", False):
|
||||
strategy_info["买入策略"] += "macd>0, \n"
|
||||
strategy_info["买入策略"] = strategy_info["买入策略"].strip()
|
||||
sell_dict = strategy_config.get("sell", {})
|
||||
sell_and_list = sell_dict.get("and", [])
|
||||
sell_or_list = sell_dict.get("or", [])
|
||||
|
|
@ -349,6 +473,7 @@ class MaBreakStatistics:
|
|||
strategy_info["卖出策略"] = sell_and_text + " 或者 \n" + sell_or_text
|
||||
else:
|
||||
strategy_info["卖出策略"] = sell_and_text
|
||||
strategy_info["卖出策略"] = strategy_info["卖出策略"].strip()
|
||||
# 将strategy_info转换为pd.DataFrame
|
||||
strategy_info_df = pd.DataFrame([strategy_info])
|
||||
return strategy_info_df
|
||||
|
|
@ -384,22 +509,24 @@ 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"
|
||||
close_mean = market_data["close"].mean()
|
||||
self.update_initial_capital(close_mean)
|
||||
logger.info(
|
||||
f"成功获取{symbol}数据：{len(market_data)}根{bar}K线,开始日期={market_data[date_time_field].min()}，结束日期={market_data[date_time_field].max()}"
|
||||
f"成功获取{symbol}数据：{len(market_data)}根{bar}K线,开始日期={market_data[self.date_time_field].min()}，结束日期={market_data[self.date_time_field].max()}"
|
||||
)
|
||||
|
||||
account_value = self.initial_capital
|
||||
|
||||
for index, row in market_data.iterrows():
|
||||
if self.is_astock:
|
||||
symbol_name = row["symbol_name"]
|
||||
elif self.is_aindex:
|
||||
symbol_name = row["symbol_name"]
|
||||
else:
|
||||
symbol_name = row["symbol"]
|
||||
ma_cross = row["ma_cross"]
|
||||
timestamp = row["timestamp"]
|
||||
date_time = row[date_time_field]
|
||||
date_time = row[self.date_time_field]
|
||||
close = row["close"]
|
||||
ma5 = row["ma5"]
|
||||
ma10 = row["ma10"]
|
||||
|
|
@ -411,7 +538,6 @@ class MaBreakStatistics:
|
|||
if ma_break_market_data_pair.get("begin_timestamp", None) is None:
|
||||
buy_condition = self.fit_strategy(
|
||||
strategy_name=strategy_name,
|
||||
market_data=market_data,
|
||||
row=row,
|
||||
behavior="buy",
|
||||
)
|
||||
|
|
@ -431,6 +557,7 @@ class MaBreakStatistics:
|
|||
|
||||
ma_break_market_data_pair = {}
|
||||
ma_break_market_data_pair["symbol"] = symbol
|
||||
ma_break_market_data_pair["symbol_name"] = symbol_name
|
||||
ma_break_market_data_pair["bar"] = bar
|
||||
ma_break_market_data_pair["begin_timestamp"] = timestamp
|
||||
ma_break_market_data_pair["begin_date_time"] = date_time
|
||||
|
|
@ -449,12 +576,12 @@ class MaBreakStatistics:
|
|||
else:
|
||||
sell_condition = self.fit_strategy(
|
||||
strategy_name=strategy_name,
|
||||
market_data=market_data,
|
||||
row=row,
|
||||
behavior="sell",
|
||||
)
|
||||
|
||||
if sell_condition:
|
||||
if sell_condition or index == len(market_data) - 1:
|
||||
# 达到卖出条件或者最后一条数据，则卖出
|
||||
shares = ma_break_market_data_pair["shares"]
|
||||
entry_price = ma_break_market_data_pair["begin_close"]
|
||||
exit_price = close
|
||||
|
|
@ -525,8 +652,10 @@ class MaBreakStatistics:
|
|||
* 100
|
||||
)
|
||||
pct_chg = round(pct_chg, 4)
|
||||
symbol_name = ma_break_market_data["symbol_name"].iloc[0]
|
||||
market_data_pct_chg = {
|
||||
"symbol": symbol,
|
||||
"symbol_name": symbol_name,
|
||||
"bar": bar,
|
||||
"pct_chg": pct_chg,
|
||||
"initial_capital": self.initial_capital,
|
||||
|
|
@ -604,52 +733,191 @@ class MaBreakStatistics:
|
|||
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",
|
||||
]
|
||||
table_name = ""
|
||||
if self.is_astock:
|
||||
if bar == "1D":
|
||||
table_name = "stock_daily_price_from_2021"
|
||||
elif bar == "1W":
|
||||
table_name = "stock_weekly_price_from_2020"
|
||||
elif bar == "1M":
|
||||
table_name = "stock_monthly_price_from_2015"
|
||||
elif self.is_aindex:
|
||||
if bar == "1D":
|
||||
table_name = "index_daily_price_from_2021"
|
||||
elif bar == "1W":
|
||||
table_name = "index_weekly_price_from_2020"
|
||||
elif bar == "1M":
|
||||
table_name = "index_monthly_price_from_2015"
|
||||
elif self.is_us_stock:
|
||||
table_name = "crypto_market_data"
|
||||
elif self.is_binance:
|
||||
table_name = "crypto_binance_data"
|
||||
else:
|
||||
table_name = "crypto_binance_data"
|
||||
|
||||
if self.is_astock or self.is_aindex:
|
||||
fields = [
|
||||
"a.ts_code as symbol",
|
||||
"b.name as symbol_name",
|
||||
f"'{bar}' as bar",
|
||||
"0 as timestamp",
|
||||
"trade_date as date_time",
|
||||
"open",
|
||||
"high",
|
||||
"low",
|
||||
"close",
|
||||
"vol as volume",
|
||||
"MA5 as ma5",
|
||||
"MA10 as ma10",
|
||||
"MA20 as ma20",
|
||||
"MA30 as ma30",
|
||||
"均线交叉 as ma_cross",
|
||||
"DIF as dif",
|
||||
"DEA as dea",
|
||||
"MACD as macd",
|
||||
]
|
||||
else:
|
||||
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
|
||||
symbol, bar, fields, start=start_date_str, end=current_end_date_str, table_name=table_name
|
||||
)
|
||||
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.sort_values(by=self.date_time_field, inplace=True)
|
||||
data.reset_index(drop=True, inplace=True)
|
||||
if self.is_astock or self.is_aindex:
|
||||
data = self.update_data(data)
|
||||
return data
|
||||
|
||||
def get_long_period_data(self, symbol: str, bar: str, end_date: str):
|
||||
"""
|
||||
获取长周期数据
|
||||
:param data: 数据
|
||||
:return: 长周期数据
|
||||
"""
|
||||
if not (self.is_astock or self.is_aindex):
|
||||
return None
|
||||
table_name = ""
|
||||
if self.is_astock:
|
||||
if bar == "1M":
|
||||
table_name = "stock_monthly_price_from_2015"
|
||||
elif bar == "1W":
|
||||
table_name = "stock_weekly_price_from_2020"
|
||||
else:
|
||||
pass
|
||||
elif self.is_aindex:
|
||||
if bar == "1M":
|
||||
table_name = "index_monthly_price_from_2015"
|
||||
elif bar == "1W":
|
||||
table_name = "index_weekly_price_from_2020"
|
||||
else:
|
||||
pass
|
||||
if len(end_date) != 10:
|
||||
end_date = self.change_date_format(end_date)
|
||||
if bar == "1M":
|
||||
# 获取上两个月的日期
|
||||
last_date = datetime.strptime(end_date, "%Y-%m-%d") - timedelta(days=60)
|
||||
last_date = last_date.strftime("%Y-%m-%d")
|
||||
elif bar == "1W":
|
||||
# 获取上两周的日期
|
||||
last_date = datetime.strptime(end_date, "%Y-%m-%d") - timedelta(days=14)
|
||||
last_date = last_date.strftime("%Y-%m-%d")
|
||||
else:
|
||||
last_date = None
|
||||
|
||||
if len(table_name) == 0 or last_date is None:
|
||||
return None
|
||||
fields = [
|
||||
"a.ts_code as symbol",
|
||||
"b.name as symbol_name",
|
||||
f"'{bar}' as bar",
|
||||
"0 as timestamp",
|
||||
"trade_date as date_time",
|
||||
"open",
|
||||
"high",
|
||||
"low",
|
||||
"close",
|
||||
"vol as volume",
|
||||
"MA5 as ma5",
|
||||
"MA10 as ma10",
|
||||
"MA20 as ma20",
|
||||
"MA30 as ma30",
|
||||
"均线交叉 as ma_cross",
|
||||
"DIF as dif",
|
||||
"DEA as dea",
|
||||
"MACD as macd",
|
||||
]
|
||||
data = self.db_market_data.query_market_data_by_symbol_bar(
|
||||
symbol, bar, fields, start=last_date, end=end_date, table_name=table_name
|
||||
)
|
||||
if data is not None and len(data) > 0:
|
||||
data = pd.DataFrame(data)
|
||||
data.sort_values(by="date_time", inplace=True)
|
||||
latest_row = data.iloc[-1]
|
||||
if (latest_row["ma5"] is None or
|
||||
latest_row["ma10"] is None or
|
||||
latest_row["ma20"] is None or
|
||||
latest_row["dif"] is None or
|
||||
latest_row["macd"] is None):
|
||||
return None
|
||||
return latest_row
|
||||
else:
|
||||
return None
|
||||
|
||||
|
||||
def update_data(self, data: pd.DataFrame):
|
||||
"""
|
||||
更新数据
|
||||
1. 将date_time列中的20210104这种格式，替换为2021-01-04的格式
|
||||
2. 将date_time转换为timestamp，并更新timestamp列
|
||||
3. 通过MetricsCalculation的ma5102030方法更新ma_cross列
|
||||
:param data: 数据
|
||||
:return: 更新后的数据
|
||||
"""
|
||||
data["date_time"] = data["date_time"].apply(lambda x: self.change_date_format(x))
|
||||
data["timestamp"] = data["date_time"].apply(lambda x: transform_date_time_to_timestamp(x))
|
||||
metrics_calculation = MetricsCalculation()
|
||||
data = metrics_calculation.ma5102030(data)
|
||||
return data
|
||||
|
||||
def change_date_format(self, date_text: str):
|
||||
# 将20210104这种格式，替换为2021-01-04的格式
|
||||
if len(date_text) == 8:
|
||||
return date_text[0:4] + "-" + date_text[4:6] + "-" + date_text[6:8]
|
||||
else:
|
||||
return date_text
|
||||
|
||||
def fit_strategy(
|
||||
self,
|
||||
strategy_name: str = "全均线策略",
|
||||
market_data: pd.DataFrame = None,
|
||||
row: pd.Series = None,
|
||||
behavior: str = "buy",
|
||||
):
|
||||
|
|
@ -661,6 +929,45 @@ class MaBreakStatistics:
|
|||
if condition_dict is None:
|
||||
logger.error(f"策略{strategy_name}的{behavior}条件不存在")
|
||||
return False
|
||||
|
||||
and_list = condition_dict.get("and", [])
|
||||
|
||||
condition = True
|
||||
condition = self.get_judge_result(row, and_list, "and", condition)
|
||||
or_list = condition_dict.get("or", [])
|
||||
condition = self.get_judge_result(row, or_list, "or", condition)
|
||||
|
||||
if behavior == "buy" and condition:
|
||||
# 如果满足条件，则判断是否根据长周期指标买入
|
||||
bar = row["bar"]
|
||||
if (self.is_astock or self.is_aindex) and bar == "1D":
|
||||
date_time = row["date_time"]
|
||||
long_period_condition_list = []
|
||||
if self.long_period_condition.get("ma5>ma10", False):
|
||||
long_period_condition_list.append("ma5>ma10")
|
||||
if self.long_period_condition.get("ma10>ma20", False):
|
||||
long_period_condition_list.append("ma10>ma20")
|
||||
if self.long_period_condition.get("macd_diff>0", False):
|
||||
long_period_condition_list.append("macd_diff>0")
|
||||
if self.long_period_condition.get("macd>0", False):
|
||||
long_period_condition_list.append("macd>0")
|
||||
if len(long_period_condition_list) > 0:
|
||||
if self.buy_by_long_period.get("by_week", False):
|
||||
long_period_data = self.get_long_period_data(row["symbol"], "1W", date_time)
|
||||
if long_period_data is not None:
|
||||
condition = self.get_judge_result(long_period_data, long_period_condition_list, "and", condition)
|
||||
if not condition:
|
||||
logger.info(f"根据周线指标，{row['symbol']}不满足买入条件")
|
||||
if self.buy_by_long_period.get("by_month", False):
|
||||
long_period_data = self.get_long_period_data(row["symbol"], "1M", date_time)
|
||||
if long_period_data is not None:
|
||||
condition = self.get_judge_result(long_period_data, long_period_condition_list, "and", condition)
|
||||
if not condition:
|
||||
logger.info(f"根据月线指标，{row['symbol']}不满足买入条件")
|
||||
|
||||
return condition
|
||||
|
||||
def get_judge_result(self, row: pd.Series, condition_list: list, and_or: str = "and", raw_condition: bool = True):
|
||||
ma_cross = row["ma_cross"]
|
||||
if pd.isna(ma_cross) or ma_cross is None:
|
||||
ma_cross = ""
|
||||
|
|
@ -670,107 +977,107 @@ class MaBreakStatistics:
|
|||
ma20 = float(row["ma20"])
|
||||
ma30 = float(row["ma30"])
|
||||
close = float(row["close"])
|
||||
volume_pct_chg = float(row["volume_pct_chg"])
|
||||
if "volume_pct_chg" in list(row.index) and row["volume_pct_chg"] is not None:
|
||||
volume_pct_chg = float(row["volume_pct_chg"])
|
||||
else:
|
||||
volume_pct_chg = None
|
||||
macd_diff = float(row["dif"])
|
||||
macd_dea = float(row["dea"])
|
||||
macd = float(row["macd"])
|
||||
|
||||
and_list = condition_dict.get("and", [])
|
||||
|
||||
condition = True
|
||||
for and_condition in and_list:
|
||||
if and_or == "and":
|
||||
for and_condition in condition_list:
|
||||
if and_condition == "5上穿10":
|
||||
condition = condition and ("5上穿10" in ma_cross)
|
||||
raw_condition = raw_condition and ("5上穿10" in ma_cross)
|
||||
elif and_condition == "10上穿20":
|
||||
condition = condition and ("10上穿20" in ma_cross)
|
||||
raw_condition = raw_condition and ("10上穿20" in ma_cross)
|
||||
elif and_condition == "20上穿30":
|
||||
condition = condition and ("20上穿30" in ma_cross)
|
||||
raw_condition = raw_condition and ("20上穿30" in ma_cross)
|
||||
elif and_condition == "ma5>ma10":
|
||||
condition = condition and (ma5 > ma10)
|
||||
raw_condition = raw_condition and (ma5 > ma10)
|
||||
elif and_condition == "ma10>ma20":
|
||||
condition = condition and (ma10 > ma20)
|
||||
raw_condition = raw_condition and (ma10 > ma20)
|
||||
elif and_condition == "ma20>ma30":
|
||||
condition = condition and (ma20 > ma30)
|
||||
raw_condition = raw_condition and (ma20 > ma30)
|
||||
elif and_condition == "close>ma20":
|
||||
condition = condition and (close > ma20)
|
||||
elif and_condition == "volume_pct_chg>0.2":
|
||||
condition = condition and (volume_pct_chg > 0.2)
|
||||
raw_condition = raw_condition and (close > ma20)
|
||||
elif and_condition == "volume_pct_chg>0.2" and volume_pct_chg is not None:
|
||||
raw_condition = raw_condition and (volume_pct_chg > 0.2)
|
||||
elif and_condition == "macd_diff>0":
|
||||
condition = condition and (macd_diff > 0)
|
||||
raw_condition = raw_condition and (macd_diff > 0)
|
||||
elif and_condition == "macd_dea>0":
|
||||
condition = condition and (macd_dea > 0)
|
||||
raw_condition = raw_condition and (macd_dea > 0)
|
||||
elif and_condition == "macd>0":
|
||||
condition = condition and (macd > 0)
|
||||
raw_condition = raw_condition and (macd > 0)
|
||||
elif and_condition == "10下穿5":
|
||||
condition = condition and ("10下穿5" in ma_cross)
|
||||
raw_condition = raw_condition and ("10下穿5" in ma_cross)
|
||||
elif and_condition == "20下穿10":
|
||||
condition = condition and ("20下穿10" in ma_cross)
|
||||
raw_condition = raw_condition and ("20下穿10" in ma_cross)
|
||||
elif and_condition == "30下穿20":
|
||||
condition = condition and ("30下穿20" in ma_cross)
|
||||
raw_condition = raw_condition and ("30下穿20" in ma_cross)
|
||||
elif and_condition == "ma5<ma10":
|
||||
condition = condition and (ma5 < ma10)
|
||||
raw_condition = raw_condition and (ma5 < ma10)
|
||||
elif and_condition == "ma10<ma20":
|
||||
condition = condition and (ma10 < ma20)
|
||||
raw_condition = raw_condition and (ma10 < ma20)
|
||||
elif and_condition == "ma20<ma30":
|
||||
condition = condition and (ma20 < ma30)
|
||||
raw_condition = raw_condition and (ma20 < ma30)
|
||||
elif and_condition == "close<ma20":
|
||||
condition = condition and (close < ma20)
|
||||
raw_condition = raw_condition and (close < ma20)
|
||||
elif and_condition == "macd_diff<0":
|
||||
condition = condition and (macd_diff < 0)
|
||||
raw_condition = raw_condition and (macd_diff < 0)
|
||||
elif and_condition == "macd_dea<0":
|
||||
condition = condition and (macd_dea < 0)
|
||||
raw_condition = raw_condition and (macd_dea < 0)
|
||||
elif and_condition == "macd<0":
|
||||
condition = condition and (macd < 0)
|
||||
raw_condition = raw_condition and (macd < 0)
|
||||
else:
|
||||
pass
|
||||
if not condition:
|
||||
or_list = condition_dict.get("or", [])
|
||||
for or_condition in or_list:
|
||||
elif and_or == "or":
|
||||
for or_condition in condition_list:
|
||||
if or_condition == "5上穿10":
|
||||
condition = condition or ("5上穿10" in ma_cross)
|
||||
raw_condition = raw_condition or ("5上穿10" in ma_cross)
|
||||
elif or_condition == "10上穿20":
|
||||
condition = condition or ("10上穿20" in ma_cross)
|
||||
raw_condition = raw_condition or ("10上穿20" in ma_cross)
|
||||
elif or_condition == "20上穿30":
|
||||
condition = condition or ("20上穿30" in ma_cross)
|
||||
raw_condition = raw_condition or ("20上穿30" in ma_cross)
|
||||
elif or_condition == "ma5>ma10":
|
||||
condition = condition or (ma5 > ma10)
|
||||
raw_condition = raw_condition or (ma5 > ma10)
|
||||
elif or_condition == "ma10>ma20":
|
||||
condition = condition or (ma10 > ma20)
|
||||
raw_condition = raw_condition or (ma10 > ma20)
|
||||
elif or_condition == "ma20>ma30":
|
||||
condition = condition or (ma20 > ma30)
|
||||
raw_condition = raw_condition or (ma20 > ma30)
|
||||
elif or_condition == "close>ma20":
|
||||
condition = condition or (close > ma20)
|
||||
elif or_condition == "volume_pct_chg>0.2":
|
||||
condition = condition or (volume_pct_chg > 0.2)
|
||||
raw_condition = raw_condition or (close > ma20)
|
||||
elif or_condition == "volume_pct_chg>0.2" and volume_pct_chg is not None:
|
||||
raw_condition = raw_condition or (volume_pct_chg > 0.2)
|
||||
elif or_condition == "macd_diff>0":
|
||||
condition = condition or (macd_diff > 0)
|
||||
raw_condition = raw_condition or (macd_diff > 0)
|
||||
elif or_condition == "macd_dea>0":
|
||||
condition = condition or (macd_dea > 0)
|
||||
raw_condition = raw_condition or (macd_dea > 0)
|
||||
elif or_condition == "macd>0":
|
||||
condition = condition or (macd > 0)
|
||||
raw_condition = raw_condition or (macd > 0)
|
||||
elif or_condition == "10下穿5":
|
||||
condition = condition or ("10下穿5" in ma_cross)
|
||||
raw_condition = raw_condition or ("10下穿5" in ma_cross)
|
||||
elif or_condition == "20下穿10":
|
||||
condition = condition or ("20下穿10" in ma_cross)
|
||||
raw_condition = raw_condition or ("20下穿10" in ma_cross)
|
||||
elif or_condition == "30下穿20":
|
||||
condition = condition or ("30下穿20" in ma_cross)
|
||||
raw_condition = raw_condition or ("30下穿20" in ma_cross)
|
||||
elif or_condition == "ma5<ma10":
|
||||
condition = condition or (ma5 < ma10)
|
||||
raw_condition = raw_condition or (ma5 < ma10)
|
||||
elif or_condition == "ma10<ma20":
|
||||
condition = condition or (ma10 < ma20)
|
||||
raw_condition = raw_condition or (ma10 < ma20)
|
||||
elif or_condition == "ma20<ma30":
|
||||
condition = condition or (ma20 < ma30)
|
||||
raw_condition = raw_condition or (ma20 < ma30)
|
||||
elif or_condition == "close<ma20":
|
||||
condition = condition or (close < ma20)
|
||||
raw_condition = raw_condition or (close < ma20)
|
||||
elif or_condition == "macd_diff<0":
|
||||
condition = condition or (macd_diff < 0)
|
||||
raw_condition = raw_condition or (macd_diff < 0)
|
||||
elif or_condition == "macd_dea<0":
|
||||
condition = condition or (macd_dea < 0)
|
||||
raw_condition = raw_condition or (macd_dea < 0)
|
||||
elif or_condition == "macd<0":
|
||||
condition = condition or (macd < 0)
|
||||
raw_condition = raw_condition or (macd < 0)
|
||||
else:
|
||||
pass
|
||||
return condition
|
||||
return raw_condition
|
||||
|
||||
|
||||
def draw_quant_pct_chg_bar_chart(
|
||||
self, data: pd.DataFrame, strategy_name: str = "全均线策略"
|
||||
|
|
@ -812,8 +1119,8 @@ class MaBreakStatistics:
|
|||
width = 0.35 # 柱状图宽度
|
||||
|
||||
# 确保symbol列是字符串类型，避免matplotlib警告
|
||||
bar_data["symbol"] = bar_data["symbol"].astype(str)
|
||||
|
||||
# bar_data["symbol"] = bar_data["symbol"].astype(str)
|
||||
bar_data["symbol_name"] = bar_data["symbol_name"].astype(str)
|
||||
# 绘制量化策略涨跌柱状图（蓝色渐变色）
|
||||
bars1 = plt.bar(
|
||||
x - width / 2,
|
||||
|
|
@ -840,7 +1147,7 @@ class MaBreakStatistics:
|
|||
)
|
||||
plt.xlabel("Symbol", fontsize=12)
|
||||
plt.ylabel("涨跌幅(%)", fontsize=12)
|
||||
plt.xticks(x, bar_data["symbol"], rotation=45, ha="right")
|
||||
plt.xticks(x, bar_data["symbol_name"], rotation=45, ha="right")
|
||||
plt.legend()
|
||||
plt.grid(True, alpha=0.3)
|
||||
|
||||
|
|
@ -907,13 +1214,13 @@ class MaBreakStatistics:
|
|||
:param strategy_name: 策略名称
|
||||
:return: None
|
||||
"""
|
||||
symbols = data["symbol"].unique()
|
||||
symbols = data["symbol_name"].unique()
|
||||
bars = data["bar"].unique()
|
||||
chart_dict = {}
|
||||
for symbol in symbols:
|
||||
for bar in bars:
|
||||
symbol_bar_data = data[
|
||||
(data["symbol"] == symbol) & (data["bar"] == bar)
|
||||
(data["symbol_name"] == symbol) & (data["bar"] == bar)
|
||||
]
|
||||
if symbol_bar_data.empty:
|
||||
continue
|
||||
|
|
@ -922,7 +1229,7 @@ class MaBreakStatistics:
|
|||
first_row = symbol_bar_data.iloc[0].copy()
|
||||
initial_capital = int(
|
||||
market_data_pct_chg_df.loc[
|
||||
(market_data_pct_chg_df["symbol"] == symbol)
|
||||
(market_data_pct_chg_df["symbol_name"] == symbol)
|
||||
& (market_data_pct_chg_df["bar"] == bar),
|
||||
"initial_capital",
|
||||
].values[0]
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ 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, MYSQL_CONFIG, WINDOW_SIZE
|
||||
from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
|
||||
import core.logger as logging
|
||||
from core.db.db_merge_market_huge_volume import DBMergeMarketHugeVolume
|
||||
from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
|
||||
|
|
@ -24,13 +24,13 @@ logger = logging.logger
|
|||
|
||||
class MeanReversionSandbox:
|
||||
def __init__(self, solution: str):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
self.db_merge_market_huge_volume = DBMergeMarketHugeVolume(self.db_url)
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ from PIL import Image as PILImage
|
|||
from datetime import datetime, timedelta
|
||||
|
||||
import core.logger as logging
|
||||
from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
|
||||
from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
|
||||
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
|
||||
|
|
@ -92,13 +92,13 @@ class ORBStrategy:
|
|||
self.data = None # 存储K线数据
|
||||
self.trades = [] # 存储交易记录
|
||||
self.equity_curve = None # 存储账户净值曲线
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
self.is_us_stock = is_us_stock
|
||||
self.is_binance = is_binance
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,62 @@
|
|||
- core/biz/huge_volume.py
|
||||
- 作用: 放量(巨量)检测与后续涨跌统计的核心逻辑。
|
||||
- 要点:
|
||||
- 基于滑窗计算 volume_ma、volume_std、volume_threshold=均值+N倍标准差，生成 huge_volume、volume_ratio、spike_intensity。
|
||||
- 可选价格分位检查：对 close/high/low 计算 80/20、90/10 分位并标注高低点命中位。
|
||||
- next_periods_rise_or_fall: 以未来 N 周期涨跌结果做分组统计，输出明细与汇总。
|
||||
|
||||
- core/biz/huge_volume_chart.py
|
||||
- 作用: 将“巨量后走势统计”数据绘图（热力图/折线图）。
|
||||
- 要点:
|
||||
- 输入统计 DataFrame，支持是否包含热力图/折线图。
|
||||
- 被 `huge_volume_main.plot_huge_volume_data` 调用，输出到 `./output/huge_volume_statistics/`。
|
||||
|
||||
- core/biz/market_data.py
|
||||
- 作用: 行情获取统一封装（OKX 为主，Linux 环境下支持 Binance，且支持美股模式）。
|
||||
- 要点:
|
||||
- get_realtime_kline_data / get_historical_kline_data：统一返回 DataFrame，含 `timestamp/date_time/date_time_us/symbol/bar/...`，自动数值化与排序。
|
||||
- 历史数据分页向后抓取，含时间边界、去重与交易时段过滤（美股）。
|
||||
- 提供 `get_realtime_candlesticks_from_binance/okx` 与基本 trade 聚合辅助（buy_sz/sell_sz 预留）。
|
||||
|
||||
- core/biz/market_data_from_itick.py
|
||||
- 作用: 从 iTick 等源拉取美股K线（供 `market_data_from_itick_main.py` 使用）。
|
||||
- 要点:
|
||||
- 封装美股数据下载，适配 `MarketData` 历史数据流程，统一列结构。
|
||||
|
||||
- core/biz/market_monitor.py
|
||||
- 作用: 实时监控报表生成（面向企业微信推送的Markdown文案）。
|
||||
- 要点:
|
||||
- create_metrics_report: 基于一根最新K线及全量数据，汇总价量、分位、MACD/KDJ/RSI/BOLL、均线多空/发散等信号，生成可读文本。
|
||||
- get_last_huge_volume_record: 最近一次巨量回溯与十周期内巨量次数。
|
||||
- get_long_short_over_buy_sell: 跨周期或对标BTC的多空/超买超卖对比说明。
|
||||
- 依赖 `METRICS_CONFIG` 的权重与阈值映射。
|
||||
|
||||
- core/biz/metrics_calculation.py
|
||||
- 作用: 技术指标与形态计算的总入口。
|
||||
- 要点:
|
||||
- 指标: pre_close/pct_chg、MACD(含金叉死叉)、KDJ(K/D/J+信号)、RSI、BOLL(上下轨与形态)、SAR(多/空/观望)。
|
||||
- 均线: ma5/10/20/30、交叉组合信号、价格-均线相对百分比、`ma_long_short`（多/空/震荡）与 `ma_divergence`（发散/粘合等），提供多策略判定：weighted_voting/trend_strength/ma_alignment/statistical/hybrid。
|
||||
- K线形态: k_length（短/中/长/超长）、k_shape（吊锤线、倒T、十字星、超大实体、光头光脚等），基于统计分布和Z-score自适应阈值。
|
||||
- MACD 背离: 标准版与滑窗版两套检测。
|
||||
|
||||
- core/biz/quant_trader.py
|
||||
- 作用: OKX 交易封装（账户、下单、行情、公共数据）。
|
||||
- 要点:
|
||||
- 余额查询（USDT/现货币/合约）、当前价格、K线拉取。
|
||||
- 现货市价单买卖；合约侧设置杠杆、开空(卖出)与平空(买入)流程。
|
||||
- 计算合约所需保证金与推荐保证金（含缓冲比例）。
|
||||
|
||||
- core/biz/strategy.py
|
||||
- 作用: 策略抽象/占位（被 `trade_main.py` 中的 `QuantStrategy` 引用）。
|
||||
- 要点:
|
||||
- 用于承载策略接口或具体策略实现（与 `quant_trader` 协作下单）。
|
||||
|
||||
- core/biz/trade_data.py
|
||||
- 作用: 交易明细获取与存储封装（供 `TradeDataMain` 使用）。
|
||||
- 要点:
|
||||
- 负责对接交易API、落库与查询，支持按时间段增量补齐。
|
||||
|
||||
- core/biz/market_data_from_itick.py（若存在）
|
||||
- 作用: iTick 美股数据源适配器。
|
||||
- 要点:
|
||||
- 输出结构与 OKX/Binance 对齐，便于统一后续指标/巨量检测流程。
|
||||
|
|
@ -0,0 +1,78 @@
|
|||
- market_monitor_main.py
|
||||
- 功能: 实时监控市场K线（优先OKX，Linux下可切换Binance），计算技术指标与巨量信号，生成监控报告并推送企业微信。
|
||||
- 要点:
|
||||
- 直接API拉取最近K线，不访问DB以保证速度。
|
||||
- 固定滑窗window_size=100，实时判定huge_volume与价格分位异常。
|
||||
- 通过最新时间戳与本地记录去重，避免重复推送。
|
||||
- 支持过滤条件：仅巨量、仅超过均量、仅上涨。
|
||||
- 依赖 Wechat 推送、DBMarketMonitor 记录、OKX_REALTIME_MONITOR_CONFIG 配置。
|
||||
|
||||
- trade_ma_strategy_main.py
|
||||
- 功能: 批量运行“均线突破/相关”策略的统计回测（主要是MACD命名策略）。
|
||||
- 要点:
|
||||
- 入口类 TradeMaStrategyMain -> MaBreakStatistics 批量统计。
|
||||
- 聚合多个策略结果输出合并的资金曲线/收益数据。
|
||||
- 可配置是否美股/是否Binance、佣金参数等。
|
||||
|
||||
- trade_sandbox_main.py
|
||||
- 功能: 均值回归策略沙盒回测，批量跑不同方案并输出Excel和图表。
|
||||
- 要点:
|
||||
- 批量维度：symbols × bars × solutions。
|
||||
- 统计指标：止盈/止损次数与占比、收益分布、均值等，按 `symbol, bar` 分组。
|
||||
- 自动绘制2×2面板图（不同bar），嵌入Excel文件。
|
||||
- 可仅跑5m，也可多周期。
|
||||
|
||||
- market_data_from_itick_main.py
|
||||
- 功能: 按时间段分片下载美股/ETF数据（示例使用AlphaVantage类命名），处理并保存CSV，展示统计。
|
||||
- 要点:
|
||||
- 配置symbol/interval/分段天数，降低单次请求压力。
|
||||
- 下载→处理→保存→打印统计的串行流程。
|
||||
- 作为离线数据拉取脚本模版使用。
|
||||
|
||||
- auto_schedule.py
|
||||
- 功能: 简易定时调度器，周期性运行 `huge_volume_main.py`。
|
||||
- 要点:
|
||||
- 使用 schedule 每小时执行一次；记录执行时间与耗时。
|
||||
- 兼容不同当前工作目录定位脚本路径。
|
||||
- 适合本地常驻调度。
|
||||
|
||||
- auto_update_market_data.py
|
||||
- 功能: 同上，定时运行 `huge_volume_main.py`（与 auto_schedule.py 功能基本一致）。
|
||||
- 要点:
|
||||
- 同样是每小时执行，日志与输出一致。
|
||||
- 可按需要二选一保留，避免重复。
|
||||
|
||||
- update_data_main.py
|
||||
- 功能: 批量更新数据库中行情数据的技术指标与美东时间字段。
|
||||
- 要点:
|
||||
- 从DB读取全量数据→按timestamp排序→更新 `date_time_us` 与 `SAR` 指标→回写DB。
|
||||
- 支持美股/加密两套symbols与bars配置。
|
||||
- 严格校验MySQL配置是否存在密码。
|
||||
|
||||
- trade_data_main.py
|
||||
- 功能: 交易明细拉取与补齐（API与DB结合），返回时间段内整理过的交易数据。
|
||||
- 要点:
|
||||
- 依据DB现有最早/最新时间决定是否调用API补齐前段或后段。
|
||||
- 默认时间范围从配置初始时间到当前；最终结果从DB聚合、排序、去重。
|
||||
- 依赖 TradeData 实现API交互与DB写入。
|
||||
|
||||
- statistics_main.py
|
||||
- 功能: 批量价格/成交量统计。
|
||||
- 要点:
|
||||
- 调用 PriceVolumeStats 批处理，返回价格统计、成交量统计与联动统计结果。
|
||||
- 用作一次性统计入口，便于离线分析。
|
||||
|
||||
- trade_main.py
|
||||
- 功能: 交易流程演示脚本（三段式示例：开空→现货卖出→平空）。
|
||||
- 要点:
|
||||
- 封装 QuantTrader，对接实盘/模拟（由配置SANDBOX决定）。
|
||||
- 展示下单参数：逐仓/全仓、张数、杠杆、缓冲比例；以及余额检查、下单、平仓流程。
|
||||
- 以日志形式串联完整交易生命周期，适合作为交易API联通性验证与流程Demo。
|
||||
|
||||
- huge_volume_main.py
|
||||
- 功能: 巨量成交检测与统计分析的核心入口（OKX与Binance均支持）。
|
||||
- 要点:
|
||||
- 从行情表读取K线，计算滑窗放量、价格分位等；支持初始化、按窗口增量更新。
|
||||
- Binance 支持CSV历史导入，导入后联动更新巨量表。
|
||||
- 提供后续N周期涨跌统计、Excel导出与可视化，以及企业微信推送过滤（如volume_ratio>10且极值价位）。
|
||||
- 多窗口（50/80/100/120）与多周期（1m~1D）批量处理能力，MySQL落库去重。
|
||||
|
|
@ -0,0 +1,23 @@
|
|||
- ma_break_statistics.py
|
||||
- 功能: 统计“均线突破”后的收益表现，批量跑不同标的/周期，生成统计与图表/Excel。
|
||||
- 要点:
|
||||
- 数据源可切换：OKX/Binance/美股；时间范围从配置读取。
|
||||
- 关注 MA5/10/20/30 多组“上穿/下穿”组合，度量突破后的区间收益。
|
||||
- 可配置手续费率，输出多策略合并结果，落地到指定 output 目录。
|
||||
- 与数据库类 `DBMarketData/DBBinanceData/DBHugeVolumeData` 协同，读取K线、过滤区间。
|
||||
|
||||
- mean_reversion_sandbox.py
|
||||
- 功能: 均值回归策略沙盒（回测器），按多种“买入/止损/止盈方案”跑批评估，生成统计+图表+Excel。
|
||||
- 要点:
|
||||
- 条件以“价格分位+巨量”触发为主：如 close_10_low=1 或 close_80/90_high=1 且近2根K线任一巨量。
|
||||
- 多个方案（solution_1/2/3）策略化定义（止盈可用波段中位数、分位、高位形态等）。
|
||||
- 读自合并视图 `DBMergeMarketHugeVolume`（含价量与巨量事件），统一回测窗口与分组汇总。
|
||||
- 自动出图（seaborn/matplotlib）并将图贴入 Excel，结果分 symbol×bar 汇总。
|
||||
|
||||
- orb_trade.py
|
||||
- 功能: ORB（Opening Range Breakout）日内策略回测与可视化。
|
||||
- 要点:
|
||||
- 以开盘第一根5分钟K线的高低（High1/Low1）作为区间，第二根K线产生多空信号；入场价=第二根开盘价，止损价=第一根极值；盈亏基于 $R（entry-stop）。
|
||||
- 支持参数：账户初始资金、最大杠杆、单笔风险比例、佣金、盈利目标倍数、仅做多/仅做空/双向、是否参考 SAR、是否参考 1H 形态等。
|
||||
- 数据获取两路：优先本地DB（OKX/Binance），也提供 yfinance 拉取美股数据的流程；自动调整初始资金规模以适配价格量级。
|
||||
- 回测输出交易清单、资金曲线，生成图表与Excel摘要到 output 目录。
|
||||
|
|
@ -11,7 +11,7 @@ import core.logger as logging
|
|||
from config import (
|
||||
OKX_MONITOR_CONFIG,
|
||||
US_STOCK_MONITOR_CONFIG,
|
||||
MYSQL_CONFIG,
|
||||
COIN_MYSQL_CONFIG,
|
||||
WINDOW_SIZE,
|
||||
BINANCE_MONITOR_CONFIG,
|
||||
)
|
||||
|
|
@ -30,13 +30,13 @@ class HugeVolumeMain:
|
|||
is_us_stock: bool = False,
|
||||
is_binance: bool = False,
|
||||
):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
self.huge_volume = HugeVolume()
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ from config import (
|
|||
OKX_MONITOR_CONFIG,
|
||||
BINANCE_MONITOR_CONFIG,
|
||||
US_STOCK_MONITOR_CONFIG,
|
||||
MYSQL_CONFIG,
|
||||
COIN_MYSQL_CONFIG,
|
||||
BAR_THRESHOLD,
|
||||
)
|
||||
|
||||
|
|
@ -67,13 +67,13 @@ class MarketDataMain:
|
|||
self.initial_date = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get(
|
||||
"initial_date", "2025-07-01 00:00:00"
|
||||
)
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
if is_binance:
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@ from huge_volume_main import HugeVolumeMain
|
|||
from core.biz.market_monitor import create_metrics_report
|
||||
from core.db.db_market_monitor import DBMarketMonitor
|
||||
from core.wechat import Wechat
|
||||
from config import OKX_MONITOR_CONFIG, OKX_REALTIME_MONITOR_CONFIG, MYSQL_CONFIG, WECHAT_CONFIG
|
||||
from config import OKX_MONITOR_CONFIG, OKX_REALTIME_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WECHAT_CONFIG
|
||||
from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
|
||||
import core.logger as logging
|
||||
|
||||
|
|
@ -31,13 +31,13 @@ class MarketMonitorMain:
|
|||
self.output_folder = "./output/report/market_monitor/"
|
||||
os.makedirs(self.output_folder, exist_ok=True)
|
||||
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
|
||||
|
|
|
|||
12
play.py
12
play.py
|
|
@ -2,7 +2,7 @@ import logging
|
|||
from core.biz.quant_trader import QuantTrader
|
||||
from core.biz.strategy import QuantStrategy
|
||||
|
||||
from config import MYSQL_CONFIG
|
||||
from config import COIN_MYSQL_CONFIG
|
||||
from sqlalchemy import create_engine, exc, text
|
||||
import pandas as pd
|
||||
|
||||
|
|
@ -100,13 +100,13 @@ def main() -> None:
|
|||
|
||||
|
||||
def test_query():
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
db_engine = create_engine(
|
||||
db_url,
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ import matplotlib.pyplot as plt
|
|||
from core.db.db_market_data import DBMarketData
|
||||
from core.biz.metrics_calculation import MetricsCalculation
|
||||
import logging
|
||||
from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
|
||||
from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
|
||||
# plt支持中文
|
||||
plt.rcParams['font.family'] = ['SimHei']
|
||||
|
||||
|
|
@ -18,13 +18,13 @@ plt.rcParams['font.family'] = ['SimHei']
|
|||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
|
||||
|
||||
def get_real_data(symbol, bar, start, end):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
db_market_data = DBMarketData(db_url)
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ from config import (
|
|||
PASSPHRASE,
|
||||
SANDBOX,
|
||||
OKX_MONITOR_CONFIG,
|
||||
MYSQL_CONFIG,
|
||||
COIN_MYSQL_CONFIG,
|
||||
)
|
||||
|
||||
logger = logging.logger
|
||||
|
|
@ -18,13 +18,13 @@ logger = logging.logger
|
|||
|
||||
class TradeDataMain:
|
||||
def __init__(self):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
|
||||
|
||||
self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
|
||||
self.trade_data = TradeData(
|
||||
|
|
|
|||
|
|
@ -18,7 +18,6 @@ from config import (
|
|||
PASSPHRASE,
|
||||
SANDBOX,
|
||||
OKX_MONITOR_CONFIG,
|
||||
MYSQL_CONFIG,
|
||||
BAR_THRESHOLD,
|
||||
)
|
||||
|
||||
|
|
@ -29,13 +28,21 @@ class TradeMaStrategyMain:
|
|||
def __init__(
|
||||
self,
|
||||
is_us_stock: bool = False,
|
||||
is_astock: bool = False,
|
||||
is_aindex: bool = True,
|
||||
is_binance: bool = False,
|
||||
commission_per_share: float = 0,
|
||||
buy_by_long_period: dict = {"by_week": False, "by_month": False},
|
||||
long_period_condition: dict = {"ma5>ma10": False, "ma10>ma20": False, "macd_diff>0": False, "macd>0": False},
|
||||
):
|
||||
self.ma_break_statistics = MaBreakStatistics(
|
||||
is_us_stock=is_us_stock,
|
||||
is_astock=is_astock,
|
||||
is_aindex=is_aindex,
|
||||
is_binance=is_binance,
|
||||
commission_per_share=commission_per_share,
|
||||
buy_by_long_period=buy_by_long_period,
|
||||
long_period_condition=long_period_condition,
|
||||
)
|
||||
|
||||
def batch_ma_break_statistics(self):
|
||||
|
|
@ -60,12 +67,51 @@ class TradeMaStrategyMain:
|
|||
logger.info("开始统计account_value_chg")
|
||||
|
||||
|
||||
def test_single_symbol():
|
||||
ma_break_statistics = MaBreakStatistics(
|
||||
is_us_stock=False,
|
||||
is_astock=True,
|
||||
is_aindex=False,
|
||||
is_binance=False,
|
||||
commission_per_share=0,
|
||||
)
|
||||
symbol = "600111.SH"
|
||||
bar = "1D"
|
||||
ma_break_statistics.trade_simulate(symbol=symbol, bar=bar, strategy_name="均线macd结合策略2")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
commission_per_share_list = [0, 0.0008]
|
||||
buy_by_long_period_list = [{"by_week": True, "by_month": True},
|
||||
{"by_week": True, "by_month": False},
|
||||
{"by_week": False, "by_month": True},
|
||||
{"by_week": False, "by_month": False}]
|
||||
long_period_condition_list = [{"ma5>ma10": True, "ma10>ma20": True, "macd_diff>0": True, "macd>0": True},
|
||||
{"ma5>ma10": True, "ma10>ma20": False, "macd_diff>0": True, "macd>0": True},
|
||||
{"ma5>ma10": False, "ma10>ma20": True, "macd_diff>0": True, "macd>0": True}]
|
||||
|
||||
for commission_per_share in commission_per_share_list:
|
||||
trade_ma_strategy_main = TradeMaStrategyMain(
|
||||
is_us_stock=False,
|
||||
is_binance=True,
|
||||
commission_per_share=commission_per_share,
|
||||
)
|
||||
trade_ma_strategy_main.batch_ma_break_statistics()
|
||||
for buy_by_long_period in buy_by_long_period_list:
|
||||
for long_period_condition in long_period_condition_list:
|
||||
logger.info(f"开始计算, 主要参数：commission_per_share: {commission_per_share}, buy_by_long_period: {buy_by_long_period}, long_period_condition: {long_period_condition}")
|
||||
trade_ma_strategy_main = TradeMaStrategyMain(
|
||||
is_us_stock=False,
|
||||
is_astock=False,
|
||||
is_aindex=True,
|
||||
is_binance=False,
|
||||
commission_per_share=commission_per_share,
|
||||
buy_by_long_period=buy_by_long_period,
|
||||
long_period_condition=long_period_condition,
|
||||
)
|
||||
trade_ma_strategy_main.batch_ma_break_statistics()
|
||||
|
||||
trade_ma_strategy_main = TradeMaStrategyMain(
|
||||
is_us_stock=False,
|
||||
is_astock=True,
|
||||
is_aindex=False,
|
||||
is_binance=False,
|
||||
commission_per_share=commission_per_share,
|
||||
buy_by_long_period=buy_by_long_period,
|
||||
long_period_condition=long_period_condition,
|
||||
)
|
||||
trade_ma_strategy_main.batch_ma_break_statistics()
|
||||
|
|
|
|||
|
|
@ -2,20 +2,20 @@ import pandas as pd
|
|||
|
||||
from core.db.db_market_data import DBMarketData
|
||||
from core.biz.metrics_calculation import MetricsCalculation
|
||||
from config import MYSQL_CONFIG, US_STOCK_MONITOR_CONFIG, OKX_MONITOR_CONFIG
|
||||
from config import COIN_MYSQL_CONFIG, US_STOCK_MONITOR_CONFIG, OKX_MONITOR_CONFIG
|
||||
import core.logger as logging
|
||||
|
||||
logger = logging.logger
|
||||
|
||||
class UpdateDataMain:
|
||||
def __init__(self):
|
||||
mysql_user = MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = MYSQL_CONFIG.get("password", "")
|
||||
mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
|
||||
mysql_password = COIN_MYSQL_CONFIG.get("password", "")
|
||||
if not mysql_password:
|
||||
raise ValueError("MySQL password is not set")
|
||||
mysql_host = MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = MYSQL_CONFIG.get("database", "okx")
|
||||
mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
|
||||
mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
|
||||
mysql_database = COIN_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)
|
||||
|
|
|
|||
Loading…
Reference in New Issue