A backtester (backtest helper) for testing my trading strategies.
Project description
Testwise
A backtester (backtest helper) for testing my trading strategies.
Example Usage
Note: Explanatory comments will be updated soon.
# Testwise is a backtester library that requires some coding knowledge
# There is no cli or interface.
# You should directly execute necessary functions like enter_long() or exit_short()
# This is a backtesting example of Exponantial Moving Average cross strategy.
# There is 1.5 ATR stop loss level and 1 ATR take profit level for every position.
# Commission rate is 0.1000%.
# Margin usage is allowed up to 5 times the main capital.
from datetime import datetime, timedelta
from testwise import Testwise
import requests
from legitindicators import ema, atr
# In this example, daily BTCUSDT kline data is used from binance
# Let's say you want to backtest your strategy for 180 days.
# It would be useful to add some extra days to the specified time interval
# for the indicators to work properly.
# (For example a 10 days of EMA won't be calculated for the first 9 days of time range)
# In this examle I add 40 extra days. This value can be determined by assigning the TRIM variable
TRIM = 40
BINANCE_URL = "https://api.binance.com/api/v3/klines"
SYMBOL = "BTCUSDT"
INTERVAL = "1d"
# These are the initial paramteres for backtester.
# You can find a more detailed explanation where the Testwise definition is given below.
COMMISSION = 0.001
DYNAMIC_POSITIONING = True
MARGIN_FACTOR = 5
LIMIT_FACTOR = 1
RISK_FACTOR = 1.5
def main():
# Here we define start time and end time of backtest.
# Notice usage of TRIM variable to start backtest a few days earlier for proper indicator use.
start_time = datetime(2020, 6, 1, 0, 0, 0)
start_time = start_time - timedelta(days=TRIM)
end_time = datetime(2021, 9, 1, 0, 0, 0)
# In this example, timestamps are used. (Because binance api requests accept timestamp)
start_time_ts = int(datetime.timestamp(start_time) * 1000)
end_time_ts = int(datetime.timestamp(end_time) * 1000)
backtest(start_time_ts, end_time_ts)
def backtest(start_time, end_time):
# Getting OHLC data
params = {"symbol": SYMBOL, "interval": INTERVAL, "startTime": start_time, "endTime": end_time}
data = get_data(params)
opn, high, low, close = get_ohlc(data)
# Backtest section
lookback = len(data) - TRIM
data = data[-lookback:]
close_tmp = close[-lookback:]
opn = opn[-lookback:]
high = high[-lookback:]
low = low[-lookback:]
# ATR
atr_input = []
for i, _ in enumerate(data):
ohlc = [opn[i], high[i], low[i], close_tmp[i]]
atr_input.append(ohlc)
atrng = atr(atr_input, 14)
for ema_length1 in range(10, 11):
for ema_length2 in range(ema_length1 + 1, 12):
# When the dynamic_positioning is set to True,
# the backtester will work as if the margin usage is available for use.
# margin_factor indicates the margin ratio. (In this example, it is 5 times the main capital)
# limit_factor is an ATR based take profit level. (In this example, it is 1 ATR from the position price)
# risk_factor is an ATR based stop loss level. (In this example, it is 1.5 ATR from the position price)
twise = Testwise(
commission=COMMISSION,
dynamic_positioning=DYNAMIC_POSITIONING,
margin_factor=MARGIN_FACTOR,
limit_factor=LIMIT_FACTOR,
risk_factor=RISK_FACTOR
)
ema_first = ema(close, ema_length1)
ema_second = ema(close, ema_length2)
ema_first = ema_first[-lookback:]
ema_second = ema_second[-lookback:]
for i, _ in enumerate(data):
if i > 1 and i < len(data) - 1:
date_open = datetime.fromtimestamp(int(data[i+1][0] / 1000)).strftime("%Y-%m-%d %H")
date_close = datetime.fromtimestamp(int(data[i][0] / 1000)).strftime("%Y-%m-%d %H")
# Position exits
if twise.pos == 1 and (ema_first[i] < ema_second[i]):
twise.exit_long(date_close, opn[i + 1], twise.current_open_pos["qty"])
if twise.pos == -1 and (ema_first[i] > ema_second[i]):
twise.exit_short(date_close, opn[i + 1], twise.current_open_pos["qty"])
if abs(high[i] - opn[i]) < abs(low[i] - opn[i]):
# open - high - low - close
# if long
# TP check
if twise.pos == 1 and high[i] > twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
twise.break_even()
twise.exit_long(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
# SL check
if twise.pos == 1 and low[i] < twise.current_open_pos["sl"]:
twise.exit_long(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
# if short
# SL check
if twise.pos == -1 and high[i] > twise.current_open_pos["sl"]:
twise.exit_short(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
# TP check
if twise.pos == -1 and low[i] < twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
twise.break_even()
twise.exit_short(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
else:
# open - low - high - close
# if long
# SL check
if twise.pos == 1 and low[i] < twise.current_open_pos["sl"]:
twise.exit_long(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
# TP check
if twise.pos == 1 and high[i] > twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
twise.break_even()
twise.exit_long(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
# if short
# TP check
if twise.pos == -1 and low[i] < twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
twise.break_even()
twise.exit_short(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
# SL check
if twise.pos == -1 and high[i] > twise.current_open_pos["sl"]:
twise.exit_short(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
# Open position
if twise.pos != 1:
if ema_first[i] > ema_second[i]:
share = twise.calculate_share(atrng[i], custom_position_risk=0.02)
twise.entry_long(date_open, opn[i + 1], share, atrng[i])
if twise.pos != -1:
if ema_first[i] < ema_second[i]:
share = twise.calculate_share(atrng[i], custom_position_risk=0.02)
twise.entry_short(date_open, opn[i + 1], share, atrng[i])
print(twise.get_result())
def get_data(params):
r = requests.get(url=BINANCE_URL, params=params)
data = r.json()
return data
def get_ohlc(data):
opn = [float(o[1]) for o in data]
close = [float(d[4]) for d in data]
high = [float(h[2]) for h in data]
low = [float(lo[3]) for lo in data]
return opn, high, low, close
if __name__ == "__main__":
main()
Installation
Run the following to install:
pip install testwise
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