Introduction

cipher

Cipher is distinct from most other backtesting frameworks. It focuses on position adjustments in the scope of a session.

Translate to Cipher:

buy -> add to position
sell -> reduce position
trade -> session (trading session)
close trade -> close session (a side effect of adjusting position to 0)
order(market) -> transaction (a side effect for position change)
order(limit, stop_loss) -> brackets

Features

well-structured, simple to use, extensible
multiple trading sessions at the same time
complex exit strategies can be implemented (trailing take profit, etc.)
multiple data sources support (multiple exchanges, symbols, timeframes, etc.)
signal generation and signal handlers are splitted
simple to run, just python my_strategy.py
works in Google Colab
finplot and mplfinance plotters
TA: pandas-ta is included, you can still use your libraries of choice

Cipher does no forward testing, paper, or live trading.

Example

EMA crossover strategy example:

import numpy as np

from cipher import Cipher, Session, Strategy


class EmaCrossoverStrategy(Strategy):
    def __init__(self, fast_ema_length=9, slow_ema_length=21, trend_ema_length=200):
        self.fast_ema_length = fast_ema_length
        self.slow_ema_length = slow_ema_length
        self.trend_ema_length = trend_ema_length

    def compose(self):
        df = self.datas.df
        df["fast_ema"] = df.ta.ema(length=self.fast_ema_length)
        df["slow_ema"] = df.ta.ema(length=self.slow_ema_length)
        df["trend_ema"] = df.ta.ema(length=self.trend_ema_length)

        df["difference"] = df["fast_ema"] - df["slow_ema"]

        # signal columns have to be boolean type
        df["entry"] = np.sign(df["difference"].shift(1)) != np.sign(df["difference"])

        df["max_6"] = df["high"].rolling(window=6).max()
        df["min_6"] = df["low"].rolling(window=6).min()

        return df

    def on_entry(self, row: dict, session: Session):
        if row["difference"] > 0 and row["close"] > row["trend_ema"]:
            # start a new long session
            session.position += "0.01"
            session.stop_loss = row["min_6"]
            session.take_profit = row["close"] + 1.5 * (row["close"] - row["min_6"])

        elif row["difference"] < 0 and row["close"] < row["trend_ema"]:
            # start a new short session
            session.position -= "0.01"
            session.stop_loss = row["max_6"]
            session.take_profit = row["close"] - 1.5 * (row["max_6"] - row["close"])

    # def on_<signal>(self, row: dict, session: Session) -> None:
    #     """Custom signal handler, called for each open session.
    #     We can adjust or close position or adjust brackets here."""
    #     # session.position = 1
    #     # session.position = base(1)  # same as the one above
    #     # session.position = '1'  # int, str, float are being converted to Decimal
    #     # session.position = quote(100)  # sets position worth 100 quote asset
    #     # session.position += 1  # adds to the position
    #     # session.position -= Decimal('1.25')  # reduces position by 1.25
    #     # session.position += percent(50)  # adds 50% more position
    #     # session.position *= 1.5  # has the same effect as the one above
    #     pass
    #
    # def on_take_profit(self, row: dict, session: Session) -> None:
    #     """Called once take profit hit, default action - close position.
    #     We can adjust the position and brackets here and let the session continue."""
    #     session.position = 0
    #
    # def on_stop_loss(self, row: dict, session: Session) -> None:
    #     """Called once stop loss hit, default action - close position.
    #     We can adjust the position and brackets here and let the session continue."""
    #     session.position = 0
    #
    # def on_stop(self, row: dict, session: Session) -> None:
    #     """Called for each open session when the dataframe end reached.
    #     We have an opportunity to close open sessions, otherwise - they will be ignored."""
    #     session.position = 0


def main():
    cipher = Cipher()
    cipher.add_source("binance_spot_ohlc", symbol="BTCUSDT", interval="1h")
    cipher.set_strategy(EmaCrossoverStrategy())
    cipher.run(start_ts="2020-01-01", stop_ts="2020-04-01")
    cipher.set_commission("0.00075")
    print(cipher.sessions)
    print(cipher.stats)
    cipher.plot()


if __name__ == "__main__":
    main()

plotter

Disclaimer

This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.