def __init__(self, sec_id: str = 'AAPL'):
self.sec_id = sec_id
self.sf_data_client = DataAPI(which_API = 'SimFin')
self.yh_data_client = DataAPI(which_API = 'yahoo')
self.period = 'annual'
self.market = 'us'
self.IS_revenue = None
def Implement_RSI(self,
sec_id='AAPL',
qty=10,
period=14,
start_date="2018-10-30"):
# Get real time data from Interactive Broker
user1 = DataAPI()
df = user1.yahoo_pricing_data(sec_id, start_date=start_date)
# Check the signal
# -- sma --
BT_user1 = Backtesting(df)
df = BT_user1.RSI_single_stock(period=14)
print('signal: {}'.format(df.loc[df.shape[0] - 1, 'signal']))
# check the most recent signal
if df.loc[df.shape[0] - 1, 'signal'] == 'buy':
self.submit_buy_order(sec_id, qty)
self.Email_client.send_buy_notification(self.email_add, sec_id)
elif df.loc[df.shape[0] - 1, 'signal'] == 'sell':
self.submit_sell_order(sec_id, qty)
self.Email_client.send_sell_notification(self.email_add, sec_id)
from data import DataAPI
from backtesting import Backtesting
from Visualization import Visualization
import pandas as pd
import matplotlib.pyplot as plt
# user_yf = DataAPI('yahoo')
# df = user_yf.yahoo_pricing_data()
# print(df)
user1 = DataAPI("SimFin")
# df_income = user1.SF_income_statement()
# print('Income statement')
# print(df_income)
# df_bs = user1.SF_balance_sheet()
# print('balancesheet statement')
# print(df_bs)
# df_cf = user1.SF_cashflow_statment()
# print('cashflow statement')
# print(df_cf)
#// test sma_backtesting single
# df = user1.SF_pricing_data(start_date='2016-01-01')
# # df = user1.SF_daily_pricing_data_from_local()
from data import DataAPI
from backtesting import Backtesting
from Visualization import Visualization
import pandas as pd
import matplotlib.pyplot as plt
user1 = DataAPI("yahoo")
df = user1.yahoo_pricing_data('AAPL', start_date= "2015-10-30")
# -- sma --
# bt1 = Backtesting(df)
# df1 = bt1.backtesting_sma_single_stock(sma_short=5, sma_long=30)
# v1 = Visualize(df1)
# v1.sma_plot_result()
# -- rsi --
# bt1 = Backtesting(df)
# df1 = bt1.RSI_single_stock(period= 28)
# v1 = Visualize(df1)
# v1.sma_plot_result()
# path = r'D:\K\HU\HU - Courses\CISC 695 Research Methodology and Writing\Assignments\sample_data\rsi_aapl_data.csv'
# df1.to_csv(path)
#// test sma_backtesting bulk
def test_SF_daily_pricing_data(self):
usr = DataAPI(which_API='SimFin', token ='free')
result = usr.SF_pricing_data('AAPL', period='Daily', market = 'us',
start_date='2018-01-01', end_date= '2020-10-30')
self.assertIsInstance(result, pd.DataFrame)
def test_yahoo_pricing_data(self):
usr = DataAPI(which_API='yahoo')
result = usr.yahoo_pricing_data('AAPL', start_date='2018-01-01', end_date= '2020-10-30')
self.assertIsInstance(result, pd.DataFrame)
def test_SF_cashflow_statment(self):
usr = DataAPI(which_API='SimFin', token ='free')
result = usr.SF_cashflow_statment('AAPL', period='quarterly', market = 'us')
self.assertIsInstance(result, pd.DataFrame)
from data import DataAPI
from backtesting import Backtesting
from Visualization import Visualize
import pandas as pd
import matplotlib.pyplot as plt
user1 = DataAPI("IEX", IEX_token)
# path_aapl2y = r'D:\K\HU\HU - Courses\CISC 695 Research Methodology and Writing\Assignments\sample_data\aapl2y.csv'
# df = pd.read_csv(path_aapl2y)
# df = pd.read_csv(path_aapl2y)
df = user1.IEX_daily_pricing_data('AAPL', '2y')
bt1 = Backtesting(df)
df1 = bt1.RSI_single_stock(notification=False)
v1 = Visualize(df1)
v1.sma_plot_result()
# df2 = bt1.sma_backteting_bulk()
# print(df2)