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3339913 3d257f3 3339913 2d2e42a 3339913 2d2e42a 3339913 2d2e42a 3339913 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 | """Command-line interface.
python -m algotrader.cli lab --symbol SPY --strategy sma_cross
python -m algotrader.cli arena --symbol BTC-USD --start 2018-01-01
python -m algotrader.cli strategies
"""
from __future__ import annotations
import argparse
import json
import sys
from typing import Dict, List
from . import __version__
from .lab import LabConfig, run_arena, run_lab
from .strategies import REGISTRY, get_strategy
def _parse_params(pairs: List[str] | None) -> Dict[str, float]:
params: Dict[str, float] = {}
for pair in pairs or []:
if "=" not in pair:
raise SystemExit(f"--param expects name=value, got '{pair}'")
name, _, value = pair.partition("=")
params[name.strip()] = float(value)
return params
def _add_common(parser: argparse.ArgumentParser) -> None:
parser.add_argument("--symbol", default="SPY")
parser.add_argument("--start", default="2015-01-01")
parser.add_argument("--end", default=None)
parser.add_argument("--interval", default="1d")
parser.add_argument(
"--source", default="yahoo", choices=["yahoo", "live", "auto", "cache", "synthetic"],
help="'yahoo' requires a Yahoo download. 'synthetic' is offline tests only. 'auto' falls back to the simulator.",
)
parser.add_argument("--commission-bps", type=float, default=1.0)
parser.add_argument("--slippage-bps", type=float, default=2.0)
parser.add_argument("--no-short", action="store_true", help="Long/flat only.")
def _config_from(args: argparse.Namespace, **overrides) -> LabConfig:
return LabConfig(
symbol=args.symbol,
start=args.start,
end=args.end,
interval=args.interval,
source=args.source,
commission_bps=args.commission_bps,
slippage_bps=args.slippage_bps,
allow_short=not args.no_short,
**overrides,
)
def _cmd_lab(args: argparse.Namespace) -> int:
cfg = _config_from(
args,
strategy=args.strategy,
params=_parse_params(args.param),
n_permutations=args.permutations,
permutation_method=args.null,
wf_folds=args.folds,
)
progress = None if args.quiet else (lambda f, m: print(f" [{f:5.0%}] {m}", file=sys.stderr))
report = run_lab(cfg, progress=progress)
if args.json:
payload = {
"symbol": report.market.symbol,
"source": report.market.source,
"strategy": report.strategy.key,
"params": report.params,
"metrics": report.backtest.metrics,
"benchmark_metrics": report.backtest.benchmark_metrics,
"p_value": report.permutation.p_value if report.permutation else None,
"deflated_sharpe": report.dsr.get("dsr"),
"pbo": report.pbo.get("pbo"),
"walkforward_efficiency": report.walkforward.get("efficiency"),
"cost_stress": report.cost_stress,
"verdict": {k: v for k, v in report.verdict.items()},
}
print(json.dumps(payload, indent=2, default=str))
return 0
v, m, b = report.verdict, report.backtest.metrics, report.backtest.benchmark_metrics
bar = "=" * 66
print(f"\n{bar}")
print(f" {report.strategy.name} on {report.market.symbol} [{report.market.source} data]")
print(f" {report.market.start.date()} to {report.market.end.date()} · {len(report.market.df):,} bars")
print(bar)
print(f" REALITY SCORE {v['score']:.1f} / 100 GRADE {v['grade']}")
print(f" {v['headline']}")
print(bar)
print(f" Total return {m['total_return']:>9.1%} buy & hold {b['total_return']:>8.1%}")
print(f" CAGR {m['cagr']:>9.1%} buy & hold {b['cagr']:>8.1%}")
print(f" Sharpe {m['sharpe']:>9.2f} buy & hold {b['sharpe']:>8.2f}")
print(f" Max drawdown {m['max_drawdown']:>9.1%}")
print(f" Trades {int(m.get('n_trades', 0)):>9,}")
print(bar)
if report.permutation:
print(f" Permutation p {report.permutation.p_value:>9.3f} ({report.permutation.n_permutations} shuffled markets)")
print(f" Deflated Sharpe {report.dsr.get('dsr', 0):>9.2f} (after {report.trials.get('n', 1)} variants)")
pbo = report.pbo.get("pbo")
print(f" Overfit prob. {pbo:>9.2f}" if pbo == pbo else " Overfit prob. n/a")
print(f" Walk-forward eff. {report.walkforward.get('efficiency', 0):>9.2f}")
print(f" Sharpe at 3x cost {report.cost_stress.get('sharpe_3x', 0):>9.2f}")
print(bar)
for flag in v["flags"]:
print(f" ! {flag}")
if v["flags"]:
print(bar)
print(f" {v['verdict']}\n")
return 0
def _cmd_arena(args: argparse.Namespace) -> int:
cfg = _config_from(args)
progress = None if args.quiet else (lambda f, m: print(f" [{f:5.0%}] {m}", file=sys.stderr))
table, market, _ = run_arena(cfg, n_permutations=args.permutations, progress=progress)
if args.json:
print(table.to_json(orient="records", indent=2))
return 0
print(f"\n {market.symbol} [{market.source} data] "
f"{market.start.date()} to {market.end.date()}\n")
display = table.drop(columns=["key"]).copy()
for col in ("Return", "CAGR", "MaxDD"):
display[col] = display[col].map("{:.1%}".format)
for col in ("Sharpe", "DSR", "Evidence"):
display[col] = display[col].map("{:.2f}".format)
display["p-value"] = display["p-value"].map(lambda v: "—" if v != v else f"{v:.3f}")
print(display.to_string(index=False))
print("\n Ranked by evidence = (1 - p) x deflated Sharpe, not by return.\n")
return 0
def _cmd_portfolio(args: argparse.Namespace) -> int:
from .portfolio_lab import DEFAULT_UNIVERSE, PortfolioLabConfig, run_portfolio_lab
symbols = [s.strip() for s in args.symbols.split(",") if s.strip()] if args.symbols else DEFAULT_UNIVERSE
cfg = PortfolioLabConfig(
symbols=symbols,
start=args.start,
end=args.end,
interval=args.interval,
source=args.source,
strategy=args.strategy,
params=_parse_params(args.param),
commission_bps=args.commission_bps,
slippage_bps=args.slippage_bps,
allow_short=not args.no_short,
rebalance=args.rebalance,
n_permutations=args.permutations,
wf_folds=args.folds,
)
progress = None if args.quiet else (lambda f, m: print(f" [{f:5.0%}] {m}", file=sys.stderr))
report = run_portfolio_lab(cfg, progress=progress)
if args.json:
print(json.dumps({
"symbols": report.panel.symbols,
"strategy": report.strategy.key,
"params": report.params,
"metrics": report.backtest.metrics,
"p_value": report.permutation.p_value if report.permutation else None,
"deflated_sharpe": report.dsr.get("dsr"),
"pbo": report.pbo.get("pbo"),
"walkforward_efficiency": report.walkforward.get("efficiency"),
"attribution": report.attribution,
"survivorship": report.survivorship.__dict__,
"verdict": dict(report.verdict),
}, indent=2, default=str))
return 0
v, m, b = report.verdict, report.backtest.metrics, report.backtest.benchmark_metrics
bar = "=" * 72
print(f"\n{bar}")
print(f" {report.strategy.name} on {len(report.panel.symbols)} symbols [{report.panel.interval}]")
print(f" {report.panel.index[0].date()} to {report.panel.index[-1].date()} · "
f"{len(report.panel):,} bars · rebalance {report.config.rebalance}")
print(bar)
print(f" REALITY SCORE {v['score']:.1f} / 100 GRADE {v['grade']}")
print(f" {v['headline']}")
print(bar)
print(f" Total return {m['total_return']:>9.1%} equal weight {b['total_return']:>8.1%}")
print(f" CAGR {m['cagr']:>9.1%} equal weight {b['cagr']:>8.1%}")
print(f" Sharpe {m['sharpe']:>9.2f} equal weight {b['sharpe']:>8.2f}")
print(f" Max drawdown {m['max_drawdown']:>9.1%}")
print(f" Gross / net exp. {m.get('gross_exposure', 0):>9.2f} / {m.get('net_exposure', 0):.2f}")
print(f" Avg positions {m.get('avg_positions', 0):>9.1f} turnover {m.get('turnover_ann', 0):.1f}x/yr")
print(bar)
if report.permutation:
print(f" Name-shuffle p {report.permutation.p_value:>9.3f} "
f"({report.permutation.n_permutations} shuffles of which names got which weights)")
print(f" Deflated Sharpe {report.dsr.get('dsr', 0):>9.2f} (after {report.trials.get('n', 1)} variants)")
pbo = report.pbo.get("pbo")
print(f" Overfit prob. {pbo:>9.2f}" if pbo == pbo else " Overfit prob. n/a")
print(f" Walk-forward eff. {report.walkforward.get('efficiency', 0):>9.2f}")
if report.attribution.get("available"):
print(f" Style alpha {report.attribution['alpha_annual']:>9.1%} "
f"t = {report.attribution['alpha_t_stat']:.2f}, R² = {report.attribution['r_squared']:.2f}")
print(f" Survivorship {report.survivorship.survival_rate:>9.0%} "
f"({report.survivorship.n_delisted} of {report.survivorship.n_symbols} stopped trading)")
print(bar)
for flag in v["flags"]:
print(f" ! {flag}")
if v["flags"]:
print(bar)
print(f" {v['verdict']}\n")
return 0
def _cmd_strategies(args: argparse.Namespace) -> int:
from .cross_sectional import XS_REGISTRY
for title, registry in (("Single asset", REGISTRY), ("Cross-sectional", XS_REGISTRY)):
print(f"\n {title}\n {'-' * len(title)}")
for key, strategy in registry.items():
params = ", ".join(f"{p.name}={p.default:g}" for p in strategy.params) or "no parameters"
print(f" {key:<22} {strategy.name:<28} [{strategy.family}]")
print(f" {'':<22} {strategy.description}")
print(f" {'':<22} defaults: {params}\n")
return 0
def main(argv: List[str] | None = None) -> int:
parser = argparse.ArgumentParser(
prog="algotrader",
description="Backtest a trading rule, then try to prove the result was luck.",
)
parser.add_argument("--version", action="version", version=f"algotrader {__version__}")
sub = parser.add_subparsers(dest="command", required=True)
lab = sub.add_parser("lab", help="Full reality check for one strategy.")
_add_common(lab)
lab.add_argument("--strategy", default="sma_cross", choices=sorted(REGISTRY))
lab.add_argument("--param", action="append", metavar="NAME=VALUE",
help="Override a strategy parameter. Repeatable.")
lab.add_argument("--permutations", type=int, default=250)
lab.add_argument("--null", default="permute", choices=["permute", "block"])
lab.add_argument("--folds", type=int, default=5)
lab.add_argument("--json", action="store_true")
lab.add_argument("--quiet", "-q", action="store_true")
lab.set_defaults(func=_cmd_lab)
arena = sub.add_parser("arena", help="Race every strategy on one market.")
_add_common(arena)
arena.add_argument("--permutations", type=int, default=120)
arena.add_argument("--json", action="store_true")
arena.add_argument("--quiet", "-q", action="store_true")
arena.set_defaults(func=_cmd_arena)
from .cross_sectional import XS_REGISTRY
portfolio = sub.add_parser(
"portfolio", help="Reality check for a cross-sectional (multi-asset) strategy."
)
_add_common(portfolio)
portfolio.add_argument(
"--symbols", default=None,
help="Comma-separated universe, e.g. SPY,QQQ,AAPL. Defaults to a 12-name universe.",
)
portfolio.add_argument("--strategy", default="xs_momentum", choices=sorted(XS_REGISTRY))
portfolio.add_argument("--param", action="append", metavar="NAME=VALUE")
portfolio.add_argument("--rebalance", default="M", help="D, W, M, Q, or a number of bars.")
portfolio.add_argument("--permutations", type=int, default=150)
portfolio.add_argument("--folds", type=int, default=4)
portfolio.add_argument("--json", action="store_true")
portfolio.add_argument("--quiet", "-q", action="store_true")
portfolio.set_defaults(func=_cmd_portfolio)
listing = sub.add_parser("strategies", help="List the strategy zoo.")
listing.set_defaults(func=_cmd_strategies)
args = parser.parse_args(argv)
try:
return args.func(args)
except KeyboardInterrupt:
return 130
except Exception as exc: # noqa: BLE001
print(f"error: {exc}", file=sys.stderr)
return 1
if __name__ == "__main__":
raise SystemExit(main())
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