可以指定任意天数的预测

ai/EstimateMarketTrendV20.py

@@ -20,9 +20,10 @@ toForecast = True  # False means test, True means forecast
 syncData = True  # 开启会同步数据库指数及基金数据
 uploadData = True  # 开启会上传预测结果
 doReport = True  # 开启会生成Excel报告
+numForecastDays = 21  # business days, 21 business days means one month
 
 # 待预测指数
-# PREDICT_LIST = [67, 121, 122, 123]
+# PREDICT_LIST = [156]
 PREDICT_LIST = [67, 121, 122, 123, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163,
                 164, 165, 166, 167, 168, 169, 170, 171, 174, 175, 177, 178]
 eco = [65, 66, 74, 134]
@@ -48,7 +49,7 @@ def report_prediction(label, predict_item, indexDict: dict):
     index_info = get_base_info(key)[0]
     if uploadData:
         if len(LABEL_RANGE) > 2:
-            data = {"rbd_id": key, "date": forecastDay, "predict": prediction}
+            data = {"rbd_id": key, "date": forecastDay, "predict": prediction, "remark": {"period": numForecastDays}}
             robo_predict.insert(data)
         else:
             from ai.noticer import upload_predict
@@ -59,16 +60,15 @@ def report_prediction(label, predict_item, indexDict: dict):
 
 def judgement(id, type, predict):
     from datetime import datetime
-    predict_term = 21
     start = parse_date(max_date) if max_date else prev_workday(datetime.today())
     navs = []
     if type == 'INDEX':
-        navs = get_index_list(index_ids=id, min_date=start, limit=predict_term + 1)
+        navs = get_index_list(index_ids=id, min_date=start, limit=numForecastDays + 1)
         navs = [nav['rid_close'] for nav in navs]
     elif type == 'FUND':
-        navs = get_fund_list(fund_ids=id, min_date=start, limit=predict_term + 1)
+        navs = get_fund_list(fund_ids=id, min_date=start, limit=numForecastDays + 1)
         navs = [nav['rfn_nav_cal'] for nav in navs]
-    if len(navs) == predict_term + 1:
+    if len(navs) == numForecastDays + 1:
         upper = True if navs[-1] >= navs[0] else False
         result = {}
         for k, v, in predict.items():
@@ -95,7 +95,6 @@ if __name__ == '__main__':
     win1W = 5  # 1 week
     win1M = 21  # 1 Month
     win1Q = 63  # 1 Quarter
-    numForecastDays = 21  # business days, 21 business days means one month
     theThreshold = 0.0
     ids = set(PREDICT_LIST) | set(eco) | set(index) | set(fund)
     infos = get_base_info(ids)

ai/reporter.py

@@ -41,18 +41,20 @@ def do_reporter2(records=None, excel_name=None):
     if not records:
         records = robo_predict.get_list()
     for item in records:
+        predict_term = json.loads(item['remark'])['period']
         result, rtn, real = is_right(item['rbd_id'], info.get(item['rbd_id'])['type'], item['date'],
-                                     item['predict'])
+                                     item['predict'], predict_term)
         labels = list(LABEL_RANGE.keys())[::-1]
         data = {
             'Forcast On Date': item['date'],
             'Ticker': info.get(item['rbd_id'])['ticker'].replace(' Index', '').replace(' Equity', ''),
-            'In 21 business days': LABEL_TAG.get(item['predict']),
+            'Forecast Business Days After': predict_term,
+            'In business days': LABEL_TAG.get(item['predict']),
             'real outcome label': LABEL_TAG.get(real),
             'random variable label': LABEL_TAG.get(random.randint(labels[0], labels[-1])),
             'Ticker Name': json.loads(info.get(item['rbd_id'])['datas'])['chineseName'],
             'Run On Time': item['create_time'].replace(minute=0, second=0),
-            'return in 21 business days': rtn,
+            'return in business days': rtn,
             'result': result
         }
         datas.append(data)
@@ -83,7 +85,7 @@ def get_RMSE(datas):
         return 0
     tags = {v: k for k, v in LABEL_TAG.items()}
     return (sum(
-        [(tags.get(data['real outcome label']) - tags.get(data['In 21 business days'])) ** 2 for data in datas]) / len(
+        [(tags.get(data['real outcome label']) - tags.get(data['In business days'])) ** 2 for data in datas]) / len(
         datas)) ** 0.5
 
 
@@ -102,8 +104,7 @@ def get_RefRMSE(datas):
          datas]) / len(datas)) ** 0.5
 
 
-def is_right(id, type, start, predict):
-    predict_term = 21
+def is_right(id, type, start, predict, predict_term):
     navs = []
     if type == 'INDEX':
         navs = get_index_list(index_ids=id, min_date=start, limit=predict_term + 1)