A quickly backtesting library for inversion strategies
pip install nanobt
Columns required = ['datetime', 'open', 'high', 'low', 'close', 'volume']
Column 'datetime' must be datetime object.
from nanobt.backtesting import Backtesting
from nanobt.trades import TradeHistory, SideOrder
import pandas as pd
INIT_PORTFOLIO = 1000
class BuyAndHoldStrategy(Backtesting):
def next(self):
if not self.position:
self.entry(SideOrder.BUY)
data = pd.read_csv('./data/binance_BTCUSDT_5m.csv')
data['datetime'] = pd.to_datetime(data['time'], unit='s')
data = data.drop(columns=['time'])
strategy = BuyAndHoldStrategy()
strategy.setdata(data)
trades = strategy.run()
th = TradeHistory(trades=trades)
print("Init Portfolio: ", INIT_PORTFOLIO)
print("Buy and Hold Strategy: ", th.study(cash=INIT_PORTFOLIO, sizer=1, commision=0.04, show_plot=False))