-

main.py

@@ -0,0 +1,121 @@
+from typing import List
+
+from historical_data.historical_data import historical_data_tradingview_csv
+from internal_types.types import Instrument, Position, SecurityType
+from strategy.buy_and_hold import BuyAndHold
+from strategy.sma_crossover import SMACrossover
+from strategy.strategy import Strategy
+from strategy.turtle_system_1 import TurtleSystem1
+from trading_gateway.trading_gateway import BacktestGateway, TradingGateway
+from utils.utils import (
+  SEC_1_DAY,
+  SEC_1_HOUR,
+  SEC_15_MINUTES,
+  SEC_30_MINUTES,
+  log_sharpe_ratio,
+  simple_sharpe_ratio,
+)
+
+
+def backtest(strategy: Strategy, instr: Instrument, interval_sec: int, initial_balance: float,
+             drawdown_limit: float, trading_gateway: TradingGateway):
+  balance_history: List[float] = []
+
+  for ohlc in trading_gateway.next_ohlc():
+    balance = strategy.net_liquid_value(ohlc.close)
+    balance_history.append(balance)
+
+    if balance <= initial_balance * (1 - drawdown_limit):
+      break
+
+    strategy.process_ohlc(ohlc)
+
+    unfilled_pos = strategy.unfilled_positions(instr)
+    if unfilled_pos.quantity:
+      if not (ohlc.low <= unfilled_pos.price <= ohlc.high):
+        # unfilled_pos = Position(unfilled_pos.instr, unfilled_pos.quantity, ohlc.open)
+        unfilled_pos = Position(unfilled_pos.instr, unfilled_pos.quantity, ohlc.close)
+      strategy.order_filled(unfilled_pos)
+
+  simple_sharpe = round(simple_sharpe_ratio(balance_history, interval_sec), 4)
+  log_sharpe = round(log_sharpe_ratio(balance_history, interval_sec), 4)
+  return_pct = round((balance_history[-1] / initial_balance - 1) * 100, 4)
+  return f'simple_sharpe: {simple_sharpe}, log_sharpe: {log_sharpe}, return_pct: {return_pct}%'
+
+
+def backtest_turtle(csv: str, instr: Instrument, interval_sec: int, initial_balance: float,
+                    drawdown_limit: float, warmup_t0: str, t0: str, t1: str):
+  warmup_historical_data = historical_data_tradingview_csv(csv, instr, warmup_t0, t0)
+  trading_gateway: TradingGateway = BacktestGateway(csv, instr, t0, t1)
+
+  strategy: Strategy = TurtleSystem1(initial_balance, instr)
+  strategy.warmup(warmup_historical_data)
+
+  return backtest(strategy, instr, interval_sec, initial_balance, drawdown_limit, trading_gateway)
+
+
+def backtest_buy_and_hold(csv: str, instr: Instrument, interval_sec: int, initial_balance: float,
+                          drawdown_limit: float, t0: str, t1: str):
+  trading_gateway: TradingGateway = BacktestGateway(csv, instr, t0, t1)
+  strategy: Strategy = BuyAndHold(initial_balance, instr)
+  return backtest(strategy, instr, interval_sec, initial_balance, drawdown_limit, trading_gateway)
+
+
+def backtest_sma_crossover(csv: str, instr: Instrument, interval_sec: int, initial_balance: float,
+                           drawdown_limit: float, warmup_t0: str, t0: str, t1: str):
+  warmup_historical_data = historical_data_tradingview_csv(csv, instr, warmup_t0, t0)
+  trading_gateway: TradingGateway = BacktestGateway(csv, instr, t0, t1)
+
+  strategy: Strategy = SMACrossover(initial_balance, instr, interval_sec, 12 * SEC_1_HOUR,
+                                    26 * SEC_1_HOUR)
+  strategy.warmup(warmup_historical_data)
+
+  return backtest(strategy, instr, interval_sec, initial_balance, drawdown_limit, trading_gateway)
+
+
+def main():
+  # csv = './csv/qqq_1999_03_10_1_day.csv'
+  # csv = './csv/qqq_2023_02_01_15_min.csv'
+  csv = './csv/slv_2023_01_03_30_min.csv'
+  # instr = Instrument('QQQ', SecurityType.EQUITY, 1)
+  instr = Instrument('SLV', SecurityType.EQUITY, 1)
+  # interval_sec = SEC_15_MINUTES
+  interval_sec = SEC_30_MINUTES
+  # interval_sec = SEC_1_DAY
+  initial_balance = 1_000_000
+  drawdown_limit = 1.00  # allow 100% loss
+  # warmup_t0 = '2023-02-01'
+  # t0, t1 = '2023-03-15', '2026-03-01'
+  # warmup_t0 = '2025-10-01'
+  # t0, t1 = '2026-02-01', '2025-03-10'
+
+  # print(backtest_buy_and_hold(csv, instr, interval_sec, initial_balance, drawdown_limit, t0, t1))
+  # print(
+  #   backtest_turtle(csv, instr, interval_sec, initial_balance, drawdown_limit, warmup_t0, t0, t1))
+  # print(
+  #   backtest_sma_crossover(csv, instr, interval_sec, initial_balance, drawdown_limit, warmup_t0, t0,
+  #                          t1))
+
+  for m in range(1, 12):
+    warmup_t0 = '2023-02-01'
+    t0, t1 = f'2025-{m:02}-01', f'2025-{m+1:02}-01'
+    print(f'---- {t0} ----')
+    print('buy and hold:',
+          backtest_buy_and_hold(csv, instr, interval_sec, initial_balance, drawdown_limit, t0, t1))
+    print(
+      '12-16 SMA:   ',
+      backtest_sma_crossover(csv, instr, interval_sec, initial_balance, drawdown_limit, warmup_t0,
+                             t0, t1))
+
+  # for y in range(2000, 2026):
+  #   warmup_t0, t0, t1 = f'{y-1}-10-01', f'{y}-01-01', f'{y+1}-01-01'
+  #   print(f'---- {y} ----')
+  #   print('buy and hold:',
+  #         backtest_buy_and_hold(csv, instr, interval_sec, initial_balance, drawdown_limit, t0, t1))
+  #   print(
+  #     'turtle      :',
+  #     backtest_turtle(csv, instr, interval_sec, initial_balance, drawdown_limit, warmup_t0, t0, t1))
+
+
+if __name__ == '__main__':
+  main()