优化按股票计算收益

stock/dnn_predict_by_stock.py

@@ -10,6 +10,7 @@ def read_data(path):
         for line in f.readlines()[:]:
             line = eval(line.strip())
             stock = str(line[-2][0])
+
             if stock in stock_lines:
                 stock_lines[stock].append(line)
             else:
@@ -29,7 +30,7 @@ def predict(file_path='', model_path='15min_dnn_seq'):
     print('数据读取完毕')
 
     models = []
-    for x in range(0, 20):
+    for x in range(0, 12):
         models.append(load_model(model_path + '_' + str(x) + '.h5'))
     estimator = joblib.load('km_dmi_18.pkl')
     print('模型加载完毕')
@@ -48,6 +49,7 @@ def predict(file_path='', model_path='15min_dnn_seq'):
 
         buy = 0 # 0空 1买入 2卖出
         chiyou_0 = 0
+        high_price = 0
 
         x = 24 # 每条数据项数
         k = 18 # 周期
@@ -55,7 +57,7 @@ def predict(file_path='', model_path='15min_dnn_seq'):
             v = line[1:x*k + 1]
             v = np.array(v)
             v = v.reshape(k, x)
-            v = v[:,4:8]
+            v = v[:,6:10]
             v = v.reshape(1, 4*k)
             # print(v)
             r = estimator.predict(v)
@@ -63,49 +65,73 @@ def predict(file_path='', model_path='15min_dnn_seq'):
             train_x = np.array([line[:-2]])
             result = models[r[0]].predict(train_x)
 
+            stock_name = line[-2]
             today_price = list(k_table.find({'code':line[-2][0], 'tradeDate':{'$gt':int(line[-2][1])}}).sort('tradeDate',pymongo.ASCENDING).limit(1))
             today_price = today_price[0]
 
-            if result[0][1] > 0.5 or result[0][2] > 0.5:
+            if result[0][0] > 0.5 or result[0][1] > 0.5: #and (r[0] not in [2,6,8,10]):
                 chiyou_0 = 0
                 print(r[0])
                 if buy == 0:
                     last_price = today_price['open']
-                    print('首次买入', line[-2], today_price['open'])
-                    buy = 1
-                elif buy == 1:
-                    init_money = init_money * (today_price['close'] - last_price)/last_price + init_money
-                    last_price = today_price['close']
-                    print('买入+买入', line[-2], today_price['open'])
+                    high_price = last_price
+                    print('首次买入', stock_name, today_price['open'])
                     buy = 1
                 else:
+                    init_money = init_money * (today_price['close'] - last_price)/last_price + init_money
                     last_price = today_price['close']
-                    print('卖出后买入', line[-2], today_price['open'])
+                    print('买入+买入', stock_name, today_price['open'])
                     buy = 1
-            elif result[0][1] > 0.5 or result[0][2] > 0.5:
-                buy = 0
-                init_money = init_money * (today_price['close'] - last_price)/last_price + init_money
-                print('卖出', line[-2], today_price['close'])
-            else:
+                    if last_price > high_price:
+                        high_price = last_price
+            elif result[0][3] > 0.5 or result[0][4] > 0.5:#and (r[0] not in [5,8]):
+                if buy == 1:
+                    if chiyou_0 > 2 or init_money < 9000:
+                        init_money = init_money * (today_price['open'] - last_price)/last_price + init_money
+                        print('卖出', stock_name, today_price['open'])
+                        buy = 0
+                        chiyou_0 = 0
+                    # elif init_money > 15000 and 100*(today_price['close'] - high_price)/high_price < -15:
+                    #     init_money = init_money * (today_price['open'] - last_price)/last_price + init_money
+                    #     print('最高点回撤卖出', stock_name, today_price['open'])
+                    #     buy = 0
+                    #     chiyou_0 = 0
+                    else:
+                        init_money = init_money * (today_price['close'] - last_price)/last_price + init_money
+                        print('继续持有，不卖出', stock_name, today_price['close'])
+                        buy = 1
+                        chiyou_0 = chiyou_0 + 1
+
+                        if today_price['close'] > high_price:
+                            high_price = today_price['close']
+
+        else:
                 if buy == 1:
                     init_money = (init_money * (today_price['close'] - last_price)/last_price) + init_money
                     if init_money < 8500:
-                        print('止损卖出', line[-2], today_price['close'])
+                        print('止损卖出', stock_name, today_price['close'])
                         buy = 0
                     else:
                         chiyou_0 = chiyou_0 + 1
-                        if init_money < 10000 and chiyou_0 > 3 and today_price['close'] < last_price:
-                            print('连续持有次数太多-- 卖出', line[-2], today_price['close'])
+                        if init_money < 10500 and chiyou_0 > 1 and today_price['close'] < last_price:
+                            print('连续持有次数太多-- 卖出', stock_name, today_price['close'])
                             buy = 0
                             chiyou_0 = 0
-                        elif chiyou_0 > 5 and today_price['close'] < last_price:
-                            print('连续持有次数太多++ 卖出', line[-2], today_price['close'])
+                        elif chiyou_0 > 2 and today_price['close'] < last_price:
+                            print('连续持有次数太多++ 卖出', stock_name, today_price['close'])
                             buy = 0
                             chiyou_0 = 0
                         else:
                             buy = 1
-                            print('持有', line[-2], today_price['close'])
+                            print('持有', stock_name, today_price['close'])
+
+                            if today_price['close'] > high_price:
+                                high_price = today_price['close']
+
                     last_price = today_price['close']
+                else:
+                    # print('忽略')
+                    pass
 
             # 具有后验知识的存在，
             # if result[0][1] > 0.5 or result[0][2] > 0.5:
@@ -153,7 +179,7 @@ def predict(file_path='', model_path='15min_dnn_seq'):
 
         print(key, init_money)
 
-        with open('D:\\data\\quantization\\stock_12_18d' + '_' +  'profit.log', 'a') as f:
+        with open('D:\\data\\quantization\\stock_15_18d' + '_' +  'profit.log', 'a') as f:
             if init_money > 10000:
                 f.write(str(key) + ' ' + str(init_money) + '\n')
             elif init_money < 10000:
@@ -169,4 +195,5 @@ def predict(file_path='', model_path='15min_dnn_seq'):
 if __name__ == '__main__':
     # predict(file_path='D:\\data\\quantization\\stock6_5_test.log', model_path='5d_dnn_seq.h5')
     # predict(file_path='D:\\data\\quantization\\stock12_18d_test.log', model_path='12_18d_dnn_seq')
-    predict(file_path='D:\\data\\quantization\\stock11_18d_test.log', model_path='12_18d_dnn_seq')
+    predict(file_path='D:\\data\\quantization\\stock15_18d_test.log', model_path='15_18d_dnn_seq')
+    # predict(file_path='D:\\data\\quantization\\stock12_18d_20190103_20190604.log', model_path='13_18d_dnn_seq')