init

screener.py

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+from pandas_datareader import data as pdr
+import json
+from yahoo_fin import stock_info as si
+from pandas import ExcelWriter
+import numpy as np
+import matplotlib.pyplot as plt
+import yfinance as yf
+import pandas as pd
+import requests
+import datetime
+import time
+import sys
+
+
+def roc11(closes):
+    print(len(closes))
+    roc11_val   = []
+    roc14_val   = []
+    roc_sum     = []
+    x = len(closes)
+    for i in range(x):
+        if i+11 == x: # Fixed
+            break
+        # cur_indx = x - i
+        # temp_11 = (closes[cur_indx] - closes[cur_indx-11])/closes[cur_indx-11]*100
+        temp_11 = (closes[i+11] - closes[i])/closes[i]*100
+        roc11_val.append(temp_11)
+
+    for i in range(x):
+        if i+14 == x: # Fixed
+            break
+        temp_14 = (closes[i+14] - closes[i])/closes[i]*100
+        roc14_val.append(temp_14)
+
+    for i in range(len(roc14_val)):
+        roc_sum.append(roc11_val[i+3]+roc14_val[i])
+    print("Finished ")
+    return roc_sum
+
+def wma10(roc_sum, n=10):
+    roc_sum = pd.DataFrame(roc_sum, columns=['COPPOCK'])
+    weights = np.arange(1, n+1)
+    wmas = roc_sum.rolling(n).apply(lambda x:np.dot(x, weights)/weights.sum(), raw=True)
+    
+    print(wmas)
+    return wmas
+
+
+yf.pdr_override()
+
+# stocklist = si.tickers_sp500()
+stock_file = open("./symbols_backup.txt", "r")
+stocklist = stock_file.readlines()
+stock_file.close()
+index_name = '^GSPC' # S&P 500
+
+final = []
+index = []
+n = -1
+f = open("./Samples/SHOP/2020-01-22/SHOP0.vezpal2")
+ticker = sys.argv[1]
+path='./Samples/'+ticker+'/2021-01-30/'+ticker+'0.vezpal2'
+path = open(path)
+a = json.load(path)
+
+pred_stock = a[0]
+
+
+
+n += 1
+time.sleep(1)
+
+
+# RS_Rating 
+start_date = datetime.datetime.now() - datetime.timedelta(days=365)
+end_date = datetime.date.today()
+# 
+# df = pdr.get_data_yahoo(stock, start=start_date, end=end_date)
+# df['Percent Change'] = df['Adj Close'].pct_change()    
+# stock_return = df['Percent Change'].sum() * 100
+# 
+# index_df = pdr.get_data_yahoo(index_name, start=start_date, end=end_date)
+# index_df['Percent Change'] = index_df['Adj Close'].pct_change()
+# index_return = index_df['Percent Change'].sum() * 100
+# 
+# RS_Rating = round((stock_return / index_return) * 10, 2)
+# 
+# sma = [50, 150, 200]
+# for x in sma:
+#     df["SMA_"+str(x)] = round(df.iloc[:,4].rolling(window=x).mean(), 2)
+
+# currentClose = df["Adj Close"][-1]
+# moving_average_50 = df["SMA_50"][-1]
+# moving_average_150 = df["SMA_150"][-1]
+# moving_average_200 = df["SMA_200"][-1]
+# low_of_52week = min(df["Adj Close"][-260:])
+# high_of_52week = max(df["Adj Close"][-260:])
+# closePrice = df["Close"]
+closePrice = pred_stock
+# print(closePrice.head())
+
+roc_res = roc11(closePrice)
+wma_res = wma10(roc_res)
+print("==========")
+print(len(wma_res));
+print(len(closePrice));
+print(closePrice.index)
+entry_buy = []
+entry_sell= []
+entry_date = []
+
+# for i in range(len(wma_res)):
+#     # mark_1 = sum(wma_res["COPPOCK"][i:i+3])
+#     if ( i+6  < len(wma_res)):
+#         mark_1 = wma_res["COPPOCK"][i]
+#         mark_2 = wma_res["COPPOCK"][i+3]
+#         mark_3 = wma_res["COPPOCK"][i+6]
+#         if (mark_2 < mark_1 and mark_2 < mark_3):
+#             # entry_date.append(closePrice.index[-237:][i])
+#             entry_buy.append(i)
+#             print("Down ",i)
+#             # print(entry_date)
+# 
+#         if (mark_2 > mark_1 and mark_2 > mark_3):
+#             # entry_date.append(closePrice.index[-237:][i])
+#             entry_sell.append(i)
+#             print("Up ",i)
+#             # print(entry_date)
+
+# i = 0
+for i in range(len(wma_res)):
+    # mark_1 = sum(wma_res["COPPOCK"][i:i+3])
+    if ( i+15  < len(wma_res)):
+        mark_1 = wma_res["COPPOCK"][i]
+        mark_2 = wma_res["COPPOCK"][i+8]
+        mark_3 = wma_res["COPPOCK"][i+15]
+
+        mark_h = wma_res["COPPOCK"][i+10]
+
+        if ((mark_2*3 < mark_1) and ( mark_2*3 < mark_3 ) and ( mark_2 > mark_h )):
+            # entry_date.append(closePrice.index[-237:][i])
+            entry_buy.append(i+8)
+            print("Down ",i," ",mark_2)
+            # print(entry_date)
+
+        if (mark_2 > mark_1 and mark_2 > mark_3 and mark_2 < mark_h):
+            # entry_date.append(closePrice.index[-237:][i])
+            entry_sell.append(i+8)
+            print("Up ",i," ",mark_2)
+            # print(entry_date)
+    # i = i + 7
+    # print(i)
+
+# wma_res['Date'] = closePrice.index[-237:]
+ax1 = plt.subplot(211)
+plt.title("COPPOCK Indicator "+str(ticker))
+# for i in entry_points:
+#     plt.vlines(x=closePrice[-237:][i], ymin=0, ymax=max(closePrice))
+plt.plot(closePrice, markevery=entry_buy, marker="^", ms=4, mfc="y", linewidth=1)
+plt.plot(closePrice, markevery=entry_sell, marker="v", ms=4, mfc="r", linewidth=1)
+
+ax2 = plt.subplot(212, sharex=ax1)
+# plt.axhline(y=0, color='r')
+# plt.plot(closePrice[-len(wma_res):], wma_res, markevery=entry_sell, marker="o")
+plt.plot(range(len(wma_res)), wma_res, markevery=entry_sell, marker="o", mfc='r' )
+plt.plot(range(len(wma_res)), wma_res, markevery=entry_buy, marker="+", mfc='g', linewidth=0.1)
+plt.show()
+plt.savefig("./screening_result/pred.png")
+# plt.savefig("./screening_result/"+str(stock)+".png", dpi=1200)
+plt.close()
+
+
+
+# writer = ExcelWriter("ScreenOutput.xlsx")
+# exportList.to_excel(writer, "Sheet1")
+# writer.save()