暂存

database/finhack_structure.sql

@@ -39,7 +39,7 @@ CREATE TABLE `auto_train` (
   `score` double(10,10) DEFAULT NULL,
   PRIMARY KEY (`id`),
   UNIQUE KEY `hash` (`hash`)
-) ENGINE=InnoDB AUTO_INCREMENT=14227 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
+) ENGINE=InnoDB AUTO_INCREMENT=14397 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
 /*!40101 SET character_set_client = @saved_cs_client */;
 
 --
@@ -93,7 +93,7 @@ CREATE TABLE `backtest` (
   `strategy_code` text,
   PRIMARY KEY (`id`),
   UNIQUE KEY `instence_id` (`instance_id`)
-) ENGINE=InnoDB AUTO_INCREMENT=443191 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
+) ENGINE=InnoDB AUTO_INCREMENT=447981 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
 /*!40101 SET character_set_client = @saved_cs_client */;
 
 --
@@ -255,4 +255,4 @@ CREATE TABLE `rqalpha` (
 /*!40101 SET COLLATION_CONNECTION=@OLD_COLLATION_CONNECTION */;
 /*!40111 SET SQL_NOTES=@OLD_SQL_NOTES */;
 
--- Dump completed on 2024-04-09 14:04:21
+-- Dump completed on 2024-06-28 13:29:27

examples/demo-project/backtest/default/default_backtest.py

@@ -72,8 +72,15 @@ def rqalpha(self):
             entry_file_path = os.path.realpath(sys.executable)
         else:
             entry_file_path = os.path.realpath(sys.argv[0])
-
-        bt_list=mydb.selectToList(f"SELECT id, instance_id, features_list, train, model, strategy, start_date, end_date, init_cash, params, total_value, alpha, beta, annual_return, cagr, annual_volatility, info_ratio, downside_risk, R2, sharpe, sortino, calmar, omega, max_down, SQN, created_at, filter, win, server, trade_num, runtime, starttime, endtime,  roto, simulate, benchmark, strategy_code FROM `finhack`.`backtest`  order by sharpe desc LIMIT 1000",'finhack')   
+
+        sql=""
+        path=f"{BASE_DIR}/data/config/sqllist/backtest/bt_list.sql"
+        if os.path.exists(path):
+            with open(path, 'r', encoding='utf-8') as file:
+                sql= file.read()
+        else:
+            sql="SELECT id, instance_id, features_list, train, model, strategy, start_date, end_date, init_cash, params, total_value, alpha, beta, annual_return, cagr, annual_volatility, info_ratio, downside_risk, R2, sharpe, sortino, calmar, omega, max_down, SQN, created_at, filter, win, server, trade_num, runtime, starttime, endtime,  roto, simulate, benchmark, strategy_code FROM `finhack`.`backtest`  order by sharpe desc LIMIT 1000"
+        bt_list=mydb.selectToList(sql,'finhack')   
 
         def to_json(s):
             dict_str = re.sub(r"DictObj\((.*?)\)", r"{\1}", s)

examples/demo-project/script/qmt.sh

@@ -4,6 +4,6 @@
 cd /data/code/demo_project
 /root/anaconda3/envs/finhack/bin/python -u /root/anaconda3/envs/finhack/bin/finhack trader run \
  --project_path=/data/code/demo_project/ \
-  --vendor=qmt --id=r_ad6709f1d13f642e16d74a40190d06c5 \
- --strategy=QMTStrategy --model_id=929526e7c5f8807a04205c17cc95b742  \
- --params='{"stocknum": "5", "refresh_rate": "5", "stop_loss_threshold": "0.95", "stop_gain_threshold": "1.2"}'  >>/tmp/finhack_qmt.log
+ --vendor=qmt --id=r_golden \
+ --strategy=QMTStrategy --model_id=97b190dd39d86b464dd76597cef2dc48 \
+ --params='{"stocknum": "30", "refresh_rate": "3", "stop_loss_threshold": "0.9", "stop_gain_threshold": "1.3"}'  >>/tmp/finhack_qmt.log

examples/demo-project/strategy/QMTStrategy.py

@@ -136,7 +136,7 @@ def trade_open(context):
 
 # 盘尾逻辑
 def trade_close(context):
-    # sync(context)
+    sync(context)
     g=context.g
     adjust_dynamic_parameters(context)
 

examples/demo-project/strategy/testStrategy.py

@@ -24,13 +24,13 @@ def initialize(context):
     # 设定滑点
     set_slippage(PriceRelatedSlippage(0.00246), type='stock')
 
-    model_id = context.trade.model_id
-    preds_cache=context.get('params', {}).get('preds_cache', 'False')
-    if preds_cache.lower()[0:1]=='t':
-        preds_data = load_preds_data(model_id,True)
-    else:
-        preds_data = load_preds_data(model_id)
-    g.preds=preds_data
+    # model_id = context.trade.model_id
+    # preds_cache=context.get('params', {}).get('preds_cache', 'False')
+    # if preds_cache.lower()[0:1]=='t':
+    #     preds_data = load_preds_data(model_id,True)
+    # else:
+    #     preds_data = load_preds_data(model_id)
+    # g.preds=preds_data
     # 全局变量初始化
     g.stock_num = int(context.get('params', {}).get('stocknum', 10))  # 持仓股票数量
     g.refresh_rate = int(context.get('params', {}).get('refresh_rate', 10))  # 调仓频率，动态调整
@@ -39,11 +39,34 @@ def initialize(context):
     g.days = 0  # 交易日计时器
 
     # 每日运行
-    run_daily(trade_open, time="09:30")
-    run_daily(trade_open, time="09:30")
-    run_daily(trade_open, time="09:30")
-    run_daily(trade_close, time="15:00")
+    run_daily(trade_open, time="09:20:10")
+    run_daily(trade_close, time="14:57:10")
 
+    # # 当前时间
+    # now = datetime.now()
+
+
+
+    # # 10分钟后的时间
+    # ten_minutes_later = now + timedelta(minutes=60*24)
+
+    # # 当前时间加上10秒，用于第一次调度
+    # next_call_time = now + timedelta(seconds=10)
+
+
+
+    # # 循环，直到达到10分钟后的时间
+    # while next_call_time <= ten_minutes_later:
+    #     print(next_call_time.strftime("%H:%M:%S"))
+    #     # 计划函数调用
+    #     run_daily(test, next_call_time.strftime("%H:%M:%S"))
+
+    #     # 更新下一次调用时间（增加10秒）
+    #     next_call_time += timedelta(seconds=10)
+
+
+def days_inc(context):
+    g.days += 1
 
 
 # 动态调整策略参数
@@ -55,11 +78,13 @@ def adjust_dynamic_parameters(context):
 def select_stocks(context):
     # 加载AI模型预测数据
     g=context.g
+    print(g)
     now_date = context.current_dt.strftime('%Y%m%d')
     preds_data=g.preds
     # 筛选今日预测数据，并排序
     pred_today = preds_data[preds_data['trade_date'] == now_date]
     pred_today_sorted = pred_today.sort_values(by='pred', ascending=False)
+    print(pred_today_sorted)
     # 返回股票列表
     return pred_today_sorted['ts_code'].tolist()
 
@@ -71,7 +96,9 @@ def should_sell(stock, context):
     if current_price==None:
         return False
     cost_price = context.portfolio.positions[stock].cost_basis
+    print(f"{stock}的当前价为{current_price}，均价为{cost_price}，止损价为{cost_price * g.stop_loss_threshold}，止盈价为{cost_price * g.stop_gain_threshold}")
     if current_price <= cost_price * g.stop_loss_threshold or current_price >= cost_price * g.stop_gain_threshold:
+        print('触发卖出条件')
         return True
     return False
 
@@ -106,17 +133,17 @@ def trade_open(context):
                     successed=successed+1
                 if successed>=num_stocks_to_buy:
                     break
-    g.days += 1
 
 
 
 # 盘尾逻辑
 def trade_close(context):
-    # sync(context)
+    sync(context)
     g=context.g
     adjust_dynamic_parameters(context)
 
     # 卖出逻辑
     for stock in list(context.portfolio.positions.keys()):
         if should_sell(stock, context):
-            order_target_value(stock, 0)
+            order_target_value(stock, 0)
+    g.days += 1

examples/demo-project/trader/miniqmt/calendar.py

@@ -0,0 +1,19 @@
+from finhack.library.mydb import mydb
+class Calendar:
+    def get_calendar(start_time,end_time,market):
+        start_time=start_time.replace('-','')[0:8]
+        end_time=end_time.replace('-','')[0:8]
+        calendar={}
+
+        if market=='astock':
+            calendar=Calendar.get_astock_calendar(start_time,end_time)
+        calendar = [f"{date[:4]}-{date[4:6]}-{date[6:]}" for date in calendar]
+        return calendar
+
+
+    #获取A股交易日历
+    def get_astock_calendar(start_time,end_time):
+        cal=mydb.selectToDf(f"select cal_date from astock_trade_cal where is_open=1 \
+        and exchange='SSE'  and cal_date>={start_time} and cal_date<={end_time} \
+        order by cal_date asc",'tushare')
+        return cal['cal_date'].tolist()

examples/demo-project/trader/miniqmt/context.py

@@ -0,0 +1,120 @@
+from trader.miniqmt.dictobj import DictObj
+
+
+g=DictObj({
+    'preds':None
+})
+
+
+context_attr= {
+            'id':'',
+            'universe':[],
+            'previous_date':None,
+            'current_dt':None,
+            'params':None,
+            'trade':DictObj({
+                'market':'',
+                'model_id':'',
+                'start_time':'',
+                'end_time':'',
+                'benchmark':'000001',
+                'log_type':'',
+                'record_type':'',
+                'strategy':'',
+                'order_volume_ratio':1,
+                'slip':0,
+                'sliptype':'pricerelated',
+                'rule_list':''
+            }),
+            'g':g,
+            'account':DictObj({
+                'username':'',
+                'password':'',
+                'account_id':'',
+                'open_tax':0,
+                'close_tax':0.001,
+                'open_commission':0.0003,
+                'close_commission':0.0003,
+                'close_today_commission':0, 
+                'min_commission':5
+
+            }),
+
+            'portfolio':DictObj({
+                'inout_cash':0,
+                'cash':0,
+                'transferable_cash':0,
+                'locked_cash':0,
+                'margin':0,
+                'total_value':0,
+                'previous_value':0,
+                'returns':0,
+                'starting_cash':0,
+                'positions_value':0,
+                'portfolio_value':0,
+                'locked_cash_by_purchase':0,
+                'locked_cash_by_redeem':0,
+                'locked_amound_by_redeen':0,
+                'positions':{
+
+                }
+            }),
+
+            'data':DictObj({
+                'calendar':[],
+                'event_interval_list':[],
+                'event_list':[],
+                'data_source':'file',
+                'daily_info':None,
+                'dividend':{},
+                'quote':None,
+                'client':None
+            }),
+
+            'logs':DictObj({
+                'trade_list':[],
+                'order_list':[],
+                'position_list':[],
+                'return_list':[],
+                'trade_returns':[],
+                'history':{}
+            }),
+            'performance':DictObj({
+                'returns':[],
+                'bench_returns':[],
+                'turnover':[],
+                'win':0,
+                'win_ratio':0,
+                'trade_num':0,
+                'indicators':{}
+            })
+
+        }
+context=DictObj(context_attr)
+
+
+
+
+           #'position':{
+                # 'xxx':sid 标的代码
+                # enable_amount 可用数量
+                # amount 总持仓数量
+                # last_sale_price 最新价格
+                # cost_basis 持仓成本价格(期货不支持)
+                # today_amount 今日开仓数量(期货不支持，且仅回测有效)
+                # 期货专用字段：
+                # delivery_date 交割日，期货使用
+                # today_short_amount 空头今仓数量
+                # today_long_amount 多头今仓数量
+                # long_cost_basis 多头持仓成本
+                # short_cost_basis 空头持仓成本
+                # margin_rate 保证金比例
+                # contract_multiplier 合约乘数
+                # long_amount 多头总持仓量
+                # short_amount 空头总持仓量
+                # long_pnl 多头浮动盈亏
+                # short_pnl 空头浮动盈亏
+                # long_enable_amount 多头可用数量
+                # short_enable_amount 多空头可用数量
+                # business_type 业务类型
+           # },

examples/demo-project/trader/miniqmt/data.py

@@ -0,0 +1,24 @@
+from finhack.library.config import Config
+from runtime.constant import *
+from finhack.market.astock.astock import AStock
+import json
+import pickle
+import pandas as pd
+import os
+import time
+from datetime import datetime
+import trader.miniqmt.calendar
+import finhack.library.log as Log
+from finhack.core.classes.dictobj import DictObj
+from trader.miniqmt.qmtClient import qclient
+
+
+class Data: 
+    def get_daily_info(code,context,date=None):
+        return qclient.getInfo(code)
+
+    #根据当前时间获取价格
+    def get_price(code,context=None):
+        return qclient.getPrice(code)
+
+