init

screener_2.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
+import glob
+import os
+
+
+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
+
+def screener(ticker):
+    # ticker = sys.argv[1]
+    path='./Samples/'+ticker+'/'
+    all_dirs   = glob.glob(path+"*")
+    print(path)
+    print(all_dirs)
+    latest_dir = max(all_dirs, key=os.path.getmtime)
+    print("Latest Data = ", latest_dir)
+    latest_dir = latest_dir + "/"
+    listsymbol = os.listdir(latest_dir+'/')
+    path = open(latest_dir+listsymbol[0])
+    a = json.load(path)
+    
+    pred_stock = a[0]
+    real_pred = a[1]
+    
+    # RS_Rating 
+    start_date = datetime.datetime.now() - datetime.timedelta(days=(365*3)+13)
+    end_date = datetime.date.today()
+    # 
+    df = pdr.get_data_yahoo(ticker, start=start_date, end=end_date)
+    real_stock = df["Close"].values
+    # real_stock = real_stock.reset_index(drop=True, inplace=True)
+    # real_stock = df["Close"].drop("Date")
+    print(real_stock)
+    print("************")
+    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 = []
+    
+    
+    # i = 0
+    entry_buy = []
+    
+    val = wma_res["COPPOCK"]
+    y = 0
+    while (y<len(val)-4):
+        x = val[y]
+        z = val[y+1]
+    
+        if x < z:
+            x = z
+    
+        if x > z and x < val[y+4]:
+            entry_buy.append(y+1)
+    
+        y = y+1
+    
+    y = 0
+    while (y<len(val)-1):
+        x = val[y]
+        z = val[y+1]
+        if x > z:
+            x = z
+        if x < z and x > val[y+1]:
+            entry_sell.append(y)
+        y = y+1
+    
+    mark_zero = []
+    for i in range(len(wma_res)-1):
+        mark_1 = wma_res["COPPOCK"][i]
+        mark_2 = wma_res["COPPOCK"][i+1]
+        if mark_1 > 0 and mark_2 < 0:
+            mark_zero.append(i+1)
+    
+    mark_zero_sell = []
+    for i in range(len(wma_res)-20):
+        mark_1 = wma_res["COPPOCK"][i]
+        mark_2 = wma_res["COPPOCK"][i+1]
+        if mark_1 < 0 and mark_2 > 0:
+            mark_zero_sell.append(i+1)
+    
+    print(entry_buy[-10:])
+    for i in  range(len(entry_buy)):
+        entry_buy[i] = entry_buy[i]+21
+    
+    for i in  range(len(mark_zero)):
+        mark_zero[i] = mark_zero[i]+21
+    
+    for i in  range(len(mark_zero_sell)):
+        mark_zero_sell[i] = mark_zero_sell[i]+21
+    
+    for i in  entry_sell:
+        i = i+14
+    
+    print(entry_buy[-10:])
+    
+    # ax1 = plt.subplot(211)
+    # plt.title("COPPOCK Indicator "+str(ticker))
+    # plt.plot(real_stock[2:], linewidth=2, label="real", linestyle="--")
+    # plt.plot(real_pred, linewidth=2, label="real", linestyle="--")
+    # plt.plot(closePrice, linewidth=0.2, label="Prediction")
+    # plt.legend()
+    # 
+    # ax2 = plt.subplot(212, sharex=ax1)
+    
+    fill_front = []
+    for i in range(21):
+        fill_front.append(np.nan)
+    fill_front.extend(wma_res["COPPOCK"])
+    
+    wma_res = fill_front
+    
+    # plt.plot(range(len(wma_res)), wma_res, markevery=mark_zero_sell, marker="x", mfc='c', linewidth=0.8)
+    # plt.plot(range(len(wma_res)), wma_res, markevery=mark_zero, marker="x", mfc='c', linewidth=0.8)
+    # plt.plot(range(len(wma_res)), np.zeros(len(wma_res)), linewidth=0.8)
+    # 
+    # plt.show()
+    # plt.savefig("./screening_result/pred.png")
+    # plt.close()
+    indictaor = []
+    indictaor.append(wma_res)
+    indictaor.append(np.zeros(len(wma_res)))
+    markers = []
+    markers.append(mark_zero)
+    markers.append(mark_zero_sell)
+    stocks = []
+    stocks.append(real_pred)
+    stocks.append(closePrice)
+    return indictaor, markers, stocks
+
+#  screener("MA")
+
+
+# writer = ExcelWriter("ScreenOutput.xlsx")
+# exportList.to_excel(writer, "Sheet1")
+# writer.save()