个股收益率计算

stock/dnn_predict_by_stock.py

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+# -*- encoding:utf-8 -*-
+import numpy as np
+from keras.models import load_model
+import joblib
+
+
+def read_data(path):
+    stock_lines = {}
+    with open(path) as f:
+        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:
+                stock_lines[stock] = [line]
+    # print(len(day_lines['20191230']))
+    return stock_lines
+
+
+import pymongo
+from util.mongodb import get_mongo_table_instance
+code_table = get_mongo_table_instance('tushare_code')
+k_table = get_mongo_table_instance('stock_day_k')
+
+
+def predict(file_path='', model_path='15min_dnn_seq'):
+    stock_lines = read_data(file_path)
+    print('数据读取完毕')
+
+    models = []
+    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')
+
+    total_money = 0
+    total_num = 0
+    items = sorted(stock_lines.keys())
+    for key in items:
+        # print(day)
+        lines = stock_lines[key]
+        init_money = 10000
+        last_price = 1
+
+        if lines[0][-2][0].startswith('6'):
+            continue
+
+        buy = 0 # 0空 1买入 2卖出
+        chiyou_0 = 0
+
+        x = 24 # 每条数据项数
+        k = 18 # 周期
+        for line in lines:
+            v = line[1:x*k + 1]
+            v = np.array(v)
+            v = v.reshape(k, x)
+            v = v[:,4:8]
+            v = v.reshape(1, 4*k)
+            # print(v)
+            r = estimator.predict(v)
+
+            train_x = np.array([line[:-2]])
+            result = models[r[0]].predict(train_x)
+
+            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:
+                chiyou_0 = 0
+                if r[0] in [2,5,9,10,11]:
+                    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'])
+                        buy = 1
+                    else:
+                        last_price = today_price['close']
+                        print('卖出后买入', line[-2], today_price['open'])
+                        buy = 1
+                else:
+                    if 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'])
+                        buy = 1
+            elif result[0][1] > 0.5 or result[0][2] > 0.5:
+                # if r[0] in [0,1,3,4,6,7] and buy in [0,1]:
+                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 buy == 1:
+                    init_money = (init_money * (today_price['close'] - last_price)/last_price) + init_money
+                    if init_money < 9000:
+                        print('止损卖出', line[-2], today_price['close'])
+                        buy = 0
+                    else:
+                        chiyou_0 = chiyou_0 + 1
+                        if 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'])
+                            buy = 0
+                        else:
+                            buy = 1
+                            print('持有', line[-2], today_price['close'])
+                    last_price = today_price['close']
+
+        print(key, init_money)
+
+        with open('D:\\data\\quantization\\stock_11_18d' + '_' +  'profit.log', 'a') as f:
+            if init_money > 10000:
+                f.write(str(key) + ' ' + str(init_money) + '\n')
+            elif init_money < 10000:
+                f.write(str(key) + ' ' + str(init_money) + '\n')
+
+        if init_money != 10000:
+            total_money = total_money + init_money
+            total_num = total_num + 1
+
+    print(total_money, total_num, total_money/total_num/10000)
+
+
+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\\stock11_18d_stock.log', model_path='11_18d_dnn_seq')