42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
|
import pandas as pd
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
from datetime import datetime, timedelta
|
||
|
|
from ohlc import ohlc
|
||
|
|
|
||
|
|
symbol = 'SPY'
|
||
|
|
today = datetime.today()
|
||
|
|
data = ohlc(symbol = symbol, start_date = today - timedelta(days = 365), end_date = today)
|
||
|
|
|
||
|
|
def calculate_moving_average(data, window = 200):
|
||
|
|
data['200_MA'] = data['Close'].rolling(window = window).mean()
|
||
|
|
return data
|
||
|
|
|
||
|
|
def calculate_rsi(data, period = 2):
|
||
|
|
delta = data['Close'].diff()
|
||
|
|
|
||
|
|
gain = np.where(delta > 0, delta, 0)
|
||
|
|
loss = np.where(delta < 0, -delta, 0)
|
||
|
|
|
||
|
|
alpha = 1 / period
|
||
|
|
avg_gain = pd.Series(gain).ewm(alpha = alpha, adjust = False).mean()
|
||
|
|
avg_loss = pd.Series(loss).ewm(alpha = alpha, adjust = False).mean()
|
||
|
|
|
||
|
|
rs = avg_gain / avg_loss
|
||
|
|
rsi = 100 - (100 / (1 + rs))
|
||
|
|
data['RSI_2'] = rsi
|
||
|
|
return data
|
||
|
|
|
||
|
|
def generate_signals(data):
|
||
|
|
conditions = (data['Close'] > data['200_MA']) & (data['RSI_2'] < 5)
|
||
|
|
data['Signal'] = np.where(conditions, 'Long', 'None')
|
||
|
|
return data
|
||
|
|
|
||
|
|
data['Date'] = pd.to_datetime(data['Date'])
|
||
|
|
|
||
|
|
data = calculate_moving_average(data)
|
||
|
|
data = calculate_rsi(data)
|
||
|
|
data = generate_signals(data)
|
||
|
|
|
||
|
|
print(data)
|