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