135 lines
5.0 KiB
Python
135 lines
5.0 KiB
Python
# flake8: noqa
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# encoding: UTF-8
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# 功能:
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# 每日夜盘扫描一次
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# 根据账号所在目录下得cta_stock_setting.json，检查所有运行中网格策略实例的持仓合约，
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# 如果当日存在除权除息情况，就进行计算更新
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# AUTHOR:李来佳
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# WeChat/QQ: 28888502
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# 广东华富资产管理
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import sys, os, copy, csv, json
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import sys, os, platform
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from datetime import datetime, timedelta
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import pandas as pd
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import traceback
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import matplotlib
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import json
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from pymongo import *
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from datetime import datetime
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VNPY_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
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if VNPY_ROOT not in sys.path:
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print(f'append {VNPY_ROOT} into sys.path')
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sys.path.append(VNPY_ROOT)
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os.environ["VNPY_TESTING"] = "1"
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from vnpy.trader.utility import load_json, save_json, append_data
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from vnpy.data.stock.adjust_factor import get_adjust_factor, get_stock_base
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from vnpy.trader.util_wechat import send_wx_msg
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if __name__ == "__main__":
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if len(sys.argv) <= 1:
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print(u'请输入:{}目录下的子目录作为参数1'.format(os.path.abspath(os.path.join(VNPY_ROOT, 'prod'))))
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exit()
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# 进行报告的账号目录
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account_folder = sys.argv[1]
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account_folder = os.path.abspath(os.path.join(VNPY_ROOT, 'prod', account_folder))
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# 策略实例配置文件
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cta_setting_file = os.path.abspath(os.path.join(account_folder, 'cta_stock_setting.json'))
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# 除权调整记录文件
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adj_record_file = os.path.abspath(os.path.join(account_folder, 'data', 'adj_records.csv'))
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field_names = ['date', 'strategy_name', 'vt_symbol', 'name', 'pre_volume', 'new_volume', 'rate', 'pre_back_adj',
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'last_back_adj']
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print('开始扫描:{}'.format(cta_setting_file))
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if not os.path.exists(cta_setting_file):
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print(u'不存在策略实例配置文件{}'.format(cta_setting_file), file=sys.stderr)
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exit()
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# 获取所有股票基本信息
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all_symbols = get_stock_base()
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# 读取策略
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cta_settings = []
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with open(cta_setting_file, encoding='UTF-8') as f:
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cta_settings = json.load(f)
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# 逐一策略扫描
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all_margin_usage = 0
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for strategy_name in cta_settings.keys():
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# 获取策略实例配置
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strategy_setting = cta_settings.get(strategy_name)
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# 策略类
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strategy_class = strategy_setting.get("class_name", "")
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setting = strategy_setting.get('setting', {})
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grids = load_json(os.path.abspath(os.path.join(account_folder, 'data', f'{strategy_name}_Grids.json')),
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auto_save=False)
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changed = False
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margin_usage = 0
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for grid in grids['dn_grids']:
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if not grid['open_status']:
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continue
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vt_symbol = grid['vt_symbol']
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info = all_symbols.get(vt_symbol,{})
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name = info.get('name',vt_symbol)
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factor = get_adjust_factor(vt_symbol)
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if factor is None or len(factor) < 2:
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print(f'没有找到{vt_symbol}的除权因子')
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continue
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# 检查除权日子的最后日期
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last_data = factor[-1]
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pre_data = factor[-2]
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print(f'{vt_symbol}[{name}]复权因子:\n{pre_data} => \n{last_data}')
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dividOperateDate = last_data['dividOperateDate']
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foreAdjustFactor = float(last_data['foreAdjustFactor'])
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adjusted_date = grid['snapshot'].get('adjusted_date', "")
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yd_date = (datetime.now() - timedelta(days=1)).strftime('%Y-%m-%d')
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# 记录的除权执行日期，跟昨日或今日不一样，除权日发生在昨日或今日
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if adjusted_date != dividOperateDate and dividOperateDate >= yd_date and foreAdjustFactor == 1.0:
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adj_rate = last_data.get('backAdjustFactor') / pre_data.get('backAdjustFactor')
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# 当前持仓
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cur_volume = grid['volume']
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# 除权后的股票新数量
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adj_volume = int(cur_volume * adj_rate)
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# 更新数量
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grid['volume'] = adj_volume
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# 更新执行日期
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grid['snapshot'].update({'adjusted_date': dividOperateDate})
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msg = f'{strategy_name}:{vt_symbol}[{name}]发生除权调整:{cur_volume}=>{adj_volume}'
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send_wx_msg(msg)
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print(msg)
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append_data(adj_record_file, dict_data={
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'date': dividOperateDate,
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'strategy_name': strategy_name,
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'vt_symbol': vt_symbol,
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'name': name,
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'pre_volume': cur_volume,
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'adj_volume': adj_volume,
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'rate': adj_rate,
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'pre_back_adj': pre_data.get('backAdjustFactor'),
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'last_back_adj': last_data.get('backAdjustFactor')
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})
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changed = True
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if changed:
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print('保存更新后的Grids.json文件')
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save_json(os.path.abspath(os.path.join(account_folder, 'data', f'{strategy_name}_Grids.json')), grids)
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