feat: add strategy and backtest services
- strategy_service.py combines opportunity + portfolio signals into unified buy/sell/hold recommendations - backtest_service.py runs walk-forward backtests on historical datasets with virtual cash and positions - CLI adds `strategy` and `backtest` commands with `--decision-interval` and other tuning parameters - Add tests for both services and CLI dispatch - Update CLAUDE.md with new architecture docs - Optimize model weights via opportunity optimizer Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Carlos Ouyang
129
tests/test_backtest_service.py
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129
tests/test_backtest_service.py
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"""Tests for backtest_service."""
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from __future__ import annotations
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import json
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import tempfile
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import unittest
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from pathlib import Path
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from typing import Any
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from coinhunter.services import backtest_service
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class BacktestServiceTestCase(unittest.TestCase):
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def _klines(self, closes: list[float], start_ms: int = 0, volumes: list[float] | None = None) -> list[list[float]]:
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volumes = volumes or [1.0] * len(closes)
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return [
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[start_ms + i * 3600000, c * 0.98, c * 1.02, c * 0.97, c, v, 0.0, c * v, 100, 0.0, 0.0, 0.0]
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for i, (c, v) in enumerate(zip(closes, volumes))
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]
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def _config(self) -> dict[str, Any]:
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return {
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"opportunity": {
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"entry_threshold": 1.5,
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"watch_threshold": 0.6,
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"min_trigger_score": 0.45,
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"min_setup_score": 0.35,
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"overlap_penalty": 0.6,
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"top_n": 10,
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"scan_limit": 50,
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"kline_limit": 48,
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"weights": {},
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"model_weights": {},
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},
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"portfolio": {
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"add_threshold": 1.5,
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"hold_threshold": 0.6,
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"trim_threshold": 0.2,
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"exit_threshold": -0.2,
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"max_position_weight": 0.6,
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"max_positions": 5,
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},
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"signal": {
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"lookback_interval": "1h",
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},
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"market": {
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"default_quote": "USDT",
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},
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"trading": {
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"commission_pct": 0.001,
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},
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}
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def _make_dataset(self, closes_by_symbol: dict[str, list[float]], start_iso: str = "2025-12-28T00:00:00Z", sim_start_iso: str = "2025-12-30T00:00:00Z", sim_end_iso: str = "2026-01-01T00:00:00Z") -> Path:
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from datetime import datetime, timezone
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start_ms = int(datetime.fromisoformat(start_iso.replace("Z", "+00:00")).timestamp() * 1000)
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klines: dict[str, dict[str, list[list[float]]]] = {}
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for symbol, closes in closes_by_symbol.items():
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klines[symbol] = {"1h": self._klines(closes, start_ms=start_ms)}
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dataset = {
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"metadata": {
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"created_at": "2026-01-01T00:00:00Z",
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"quote": "USDT",
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"symbols": list(closes_by_symbol.keys()),
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"plan": {
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"intervals": ["1h"],
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"kline_limit": 48,
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"reference_days": 2.0,
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"simulate_days": 1.0,
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"run_days": 1.0,
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"total_days": 4.0,
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"start": start_iso,
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"simulation_start": sim_start_iso,
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"simulation_end": sim_end_iso,
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"end": sim_end_iso,
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},
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"external_history": {"provider": "disabled", "status": "disabled"},
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},
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"klines": klines,
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}
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fp = tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False)
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json.dump(dataset, fp)
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fp.close()
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return Path(fp.name)
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def test_run_backtest_produces_summary(self) -> None:
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config = self._config()
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closes = list(range(20, 92))
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path = self._make_dataset({"BTCUSDT": closes})
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try:
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result = backtest_service.run_backtest(config, dataset_path=str(path), initial_cash=10000.0)
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self.assertIn("summary", result)
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self.assertIn("trades", result)
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self.assertIn("equity_curve", result)
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self.assertIn("parameters", result)
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summary = result["summary"]
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self.assertIn("initial_cash", summary)
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self.assertIn("final_equity", summary)
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self.assertIn("total_return_pct", summary)
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self.assertIn("max_drawdown_pct", summary)
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self.assertIn("win_rate", summary)
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finally:
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path.unlink()
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def test_run_backtest_missing_simulation_dates_raises(self) -> None:
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config = self._config()
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path = self._make_dataset({"BTCUSDT": list(range(20, 92))}, sim_start_iso="", sim_end_iso="")
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try:
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with self.assertRaises(ValueError):
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backtest_service.run_backtest(config, dataset_path=str(path))
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finally:
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path.unlink()
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def test_run_backtest_tracks_equity_curve(self) -> None:
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config = self._config()
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# Need ~72 candles to cover 2025-12-28 through 2026-01-01 (warmup + simulation)
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closes = list(range(20, 92))
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path = self._make_dataset({"BTCUSDT": closes})
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try:
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result = backtest_service.run_backtest(config, dataset_path=str(path), initial_cash=10000.0)
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self.assertTrue(len(result["equity_curve"]) > 0)
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first = result["equity_curve"][0]
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self.assertIn("time", first)
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self.assertIn("equity", first)
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self.assertIn("cash", first)
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self.assertIn("positions_count", first)
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finally:
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path.unlink()
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@@ -336,6 +336,76 @@ class CLITestCase(unittest.TestCase):
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max_examples=5,
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)
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def test_strategy_dispatches(self):
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captured = {}
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with (
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patch.object(
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cli, "load_config", return_value={"binance": {"spot_base_url": "https://test", "recv_window": 5000}, "market": {"default_quote": "USDT"}, "opportunity": {"top_n": 10}}
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),
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patch.object(cli, "get_binance_credentials", return_value={"api_key": "k", "api_secret": "s"}),
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patch.object(cli, "SpotBinanceClient"),
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patch.object(
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cli.strategy_service,
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"generate_trade_signals",
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return_value={"buy": [{"symbol": "BTCUSDT", "score": 0.82}], "sell": [], "hold": []},
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),
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patch.object(
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cli, "print_output", side_effect=lambda payload, **kwargs: captured.setdefault("payload", payload)
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),
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):
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result = cli.main(["strategy", "-s", "BTCUSDT"])
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self.assertEqual(result, 0)
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self.assertEqual(captured["payload"]["buy"][0]["symbol"], "BTCUSDT")
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def test_backtest_dispatches_without_private_client(self):
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captured = {}
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config = {"market": {"default_quote": "USDT"}, "opportunity": {}}
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with (
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patch.object(cli, "load_config", return_value=config),
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patch.object(cli, "_load_spot_client", side_effect=AssertionError("backtest should use dataset only")),
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patch.object(
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cli.backtest_service,
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"run_backtest",
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return_value={"summary": {"total_return_pct": 5.0, "win_rate": 0.6}, "trades": []},
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) as backtest_mock,
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patch.object(
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cli,
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"print_output",
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side_effect=lambda payload, **kwargs: captured.update({"payload": payload, "agent": kwargs["agent"]}),
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),
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):
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result = cli.main(
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[
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"backtest",
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"/tmp/dataset.json",
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"--initial-cash",
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"5000",
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"--max-positions",
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"3",
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"--position-size-pct",
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"20",
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"--commission-pct",
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"0.1",
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"--lookback",
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"12",
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"--agent",
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]
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)
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self.assertEqual(result, 0)
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self.assertEqual(captured["payload"]["summary"]["total_return_pct"], 5.0)
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self.assertTrue(captured["agent"])
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backtest_mock.assert_called_once_with(
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config,
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dataset_path="/tmp/dataset.json",
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initial_cash=5000.0,
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max_positions=3,
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position_size_pct=0.2,
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commission_pct=0.001,
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lookback=12,
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decision_interval_minutes=None,
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)
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def test_opportunity_optimize_dispatches_without_private_client(self):
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captured = {}
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config = {"market": {"default_quote": "USDT"}, "opportunity": {}}
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100
tests/test_strategy_service.py
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100
tests/test_strategy_service.py
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"""Tests for strategy_service."""
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from __future__ import annotations
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import unittest
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from typing import Any
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from unittest import mock
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from unittest.mock import MagicMock
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from coinhunter.services import strategy_service
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class StrategyServiceTestCase(unittest.TestCase):
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def _klines(self, closes: list[float], volumes: list[float] | None = None) -> list[list[float]]:
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volumes = volumes or [1.0] * len(closes)
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return [
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[i * 3600000.0, c * 0.98, c * 1.02, c * 0.97, c, v, 0.0, c * v, 100, 0.0, 0.0, 0.0]
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for i, (c, v) in enumerate(zip(closes, volumes))
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]
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def _config(self) -> dict[str, Any]:
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return {
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"opportunity": {
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"entry_threshold": 1.5,
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"watch_threshold": 0.6,
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"min_trigger_score": 0.45,
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"min_setup_score": 0.35,
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"overlap_penalty": 0.6,
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"top_n": 10,
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"scan_limit": 50,
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"kline_limit": 48,
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"weights": {},
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"model_weights": {},
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},
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"portfolio": {
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"add_threshold": 1.5,
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"hold_threshold": 0.6,
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"trim_threshold": 0.2,
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"exit_threshold": -0.2,
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"max_position_weight": 0.6,
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},
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"signal": {
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"lookback_interval": "1h",
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},
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"market": {
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"default_quote": "USDT",
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},
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}
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def test_generate_signals_from_klines_buy_when_entry_and_not_held(self) -> None:
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config = self._config()
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closes = list(range(20, 40))
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klines = {"BTCUSDT": self._klines(closes)}
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result = strategy_service.generate_signals_from_klines(config, klines_by_symbol=klines, held_positions=[])
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self.assertIn("buy", result)
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self.assertIn("sell", result)
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self.assertIn("hold", result)
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def test_generate_signals_from_klines_sell_when_exit_signal(self) -> None:
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config = self._config()
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closes = list(range(40, 20, -1))
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klines = {"BTCUSDT": self._klines(closes)}
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held = [{"symbol": "BTCUSDT", "notional_usdt": 1000.0}]
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result = strategy_service.generate_signals_from_klines(config, klines_by_symbol=klines, held_positions=held)
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symbols = [s["symbol"] for s in result["sell"]]
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self.assertIn("BTCUSDT", symbols)
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def test_generate_signals_respects_max_position_weight(self) -> None:
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config = self._config()
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config["portfolio"]["max_position_weight"] = 0.01
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closes = list(range(20, 40))
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klines = {"BTCUSDT": self._klines(closes)}
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held = [{"symbol": "BTCUSDT", "notional_usdt": 9999.0}]
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result = strategy_service.generate_signals_from_klines(config, klines_by_symbol=klines, held_positions=held)
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buy_symbols = [s["symbol"] for s in result["buy"]]
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self.assertNotIn("BTCUSDT", buy_symbols)
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@mock.patch("coinhunter.services.portfolio_service.audit_event")
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@mock.patch("coinhunter.services.opportunity_service.audit_event")
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def test_generate_trade_signals_dispatches_to_services(self, mock_audit_opp, mock_audit_pf) -> None:
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mock_client = MagicMock()
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mock_client.klines.return_value = self._klines(list(range(20, 44)))
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mock_client.ticker_stats.return_value = [
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{
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"symbol": "BTCUSDT",
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"lastPrice": "30.0",
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"priceChangePercent": "5.0",
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"quoteVolume": "1000000",
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"highPrice": "31.0",
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"lowPrice": "29.0",
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}
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]
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mock_client.account.return_value = {"balances": [{"asset": "BTC", "free": "0.5", "locked": "0.0"}]}
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mock_client.exchange_info.return_value = {"symbols": [{"symbol": "BTCUSDT", "status": "TRADING"}]}
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config = self._config()
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result = strategy_service.generate_trade_signals(config, spot_client=mock_client)
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self.assertIn("buy", result)
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self.assertIn("sell", result)
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self.assertIn("hold", result)
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