File size: 1,243 Bytes
354a78a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
def f(z):
c = 0.1
n = 2
return c * abs(z)**n * (np.cos(n * np.angle(z)) + 1j * np.sin(n * np.angle(z)))
def buy_signal(data):
if f(data['Close'].iloc[-1]) > 0:
return True
else:
return False
def sell_signal(data):
if f(data['Close'].iloc[-1]) < 0:
return True
else:
return False
def trade(data):
bought = False
for i in range(len(data)):
if buy_signal(data.iloc[i:i+1]):
if not bought:
bought = True
data.loc[i, 'Action'] = 'Buy'
elif sell_signal(data.iloc[i:i+1]):
if bought:
bought = False
data.loc[i, 'Action'] = 'Sell'
def backtest(data):
trade(data)
data['Return'] = data['Close'].pct_change()
data['Strategy Return'] = data['Action'].shift(1) * data['Return']
strategy_return = data['Strategy Return'].sum()
print(f"Strategy Return: {strategy_return}")
# Load data
data = pd.read_csv('data.csv', index_col='Date', parse_dates=True)
# Backtest strategy
backtest(data)
# Plot results
plt.plot(data['Close'])
plt.plot(data['Strategy Return'] + data['Close'])
plt.show() |