HA Candles Backtest

ha-candles-backtest.py

import yfinance as yf
import pandas as pd
import numpy as np
import pandas_datareader as pdr
import matplotlib.pyplot as plt
import plotly
import plotly.graph_objects as go
yf.pdr_override()

stock = yf.Ticker("SPY")
df = stock.history(period="10y", interval="1d")

df['OpenS'] = df['Open'].shift(1)
df['CloseS'] = df['Close'].shift(1)

nums = [0]
for i in range(len(df)):
  number = nums[-1] + 1
  nums.append(number)

df['rownum'] = nums[1:]

df['returns'] = df['Close'].pct_change()
df['returnsS'] = df['returns'].shift(-1)
df['HA Close'] = (df['Open'] + df['Close'] + df['Low'] + df['Close']) * .25
df['HA Open'] = (df['OpenS'] + df['CloseS']) * .5
df['HA Low'] = df['Low']
df['HA High'] = df['High']

df['position'] = np.where(df['HA Close'] > df['HA Open'] , 1 , 0)
df['strat returns'] = np.where(df['position'] ==1 , 1 + df['returnsS'] , 1)
df['adj close'] = df['Close'] / df['Close'][0]
df['cumreturns'] = df['strat returns'].cumprod()

df['cumreturns'].plot(figsize = (21,9))
df['adj close'].plot()
plt.legend();

plot-candles.py

fig = go.Figure(data=[go.Candlestick(x=df['rownum'],
                open=df['HA Open'],
                high=df['HA High'],
                low=df['HA Low'],
                close=df['HA Close'])])

fig.show()