ed19985c95
The hardcoded WeightedByRealizedSharpe path from C7 is now joined by
a stack-based bytecode interpreter that consumes Strategy::flatten()
output, unlocking RegimeSwitch / Portfolio / non-default Ensemble /
single-Leaf compositions specified via policy-grid YAML.
cuda/decision_policy.cu — new kernel `decision_policy_program`:
Stack-based VM with parallel (value, attribution_mask) stacks.
Opcodes mirror src/policy/mod.rs::OpCode exactly:
NoOp / PushScalar / EvalRegime / BranchIfRegime
EmitPerHorizonSize (computes sized intent from alpha[h] +
IsvKellyState[h] using same Kelly + ISV-cap formula as the
hardcoded default)
AggMean / AggWeightedSharpe / AggMaxConfidence (pop n values,
push aggregated, OR attribution masks)
ApplyConflict (v1 no-op, reserved for Portfolio)
WriteOrder (terminal — converts top-of-stack to market_target +
open_horizon_masks attribution if currently flat)
AggWeightedSharpe recovers the source horizon from a single-bit
attribution mask to look up recent_sharpe; multi-bit masks (nested
aggregators that collapsed horizons) fall back to uniform weight.
decision_policy_default extended with a program_lens param: skips any
backtest whose plen > 0 (the program kernel handled it). The two
kernels run sequentially in step_decision_with_latency with mutual
exclusivity on each backtest slot.
LobSimCuda gains:
upload_program(b, &Program) — uploads a Strategy::flatten() output
to backtest b's slot in program_table_d, updates program_lens_d.
set_regime(b, regime_id) — writes regimes_d for OP_EVAL_REGIME /
OP_BRANCH_IF_REGIME consumption.
BacktestHarnessConfig.strategies (Vec<Strategy>) — empty means every
cell uses the hardcoded default; non-empty len must equal n_parallel
and each strategy is flattened + uploaded at construction.
bin/fxt-backtest --policy-grid <yaml> path now actually plumbs through
to the kernel (was parsed-but-ignored in C9). Empty grid keeps the
default behaviour.
New fixture decision_program_h4_only: uploads Strategy::Leaf(h4_only)
flattened to (EmitPerHorizonSize, WriteOrder) — 2 instructions, 16
bytes — and verifies the bytecode kernel produces equivalent end-state
to the hardcoded default (3 lot buy at vwap=5500). Proves the VM
dispatcher works end-to-end.
12/12 GPU fixtures green. 33 lib unit tests + 3 Ring 2 fuzz tests
still green.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
41 lines
1.8 KiB
JSON
41 lines
1.8 KiB
JSON
{
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"name": "decision_program_h4_only",
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"n_backtests": 1,
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"comment": "Uploads a custom Strategy bytecode program (single Leaf at horizon 4) that bypasses the hardcoded WeightedByRealizedSharpe default. Should produce equivalent end-state when h4 is the only weighted horizon.",
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"warm_start_isv_kelly": [
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[
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{ "pnl_ema_win": 0.0, "pnl_ema_loss": 0.0, "win_rate_ema": 0.0, "n_trades_seen": 0, "realised_return_var": 0.0, "recent_sharpe": 0.0 },
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{ "pnl_ema_win": 0.0, "pnl_ema_loss": 0.0, "win_rate_ema": 0.0, "n_trades_seen": 0, "realised_return_var": 0.0, "recent_sharpe": 0.0 },
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{ "pnl_ema_win": 0.0, "pnl_ema_loss": 0.0, "win_rate_ema": 0.0, "n_trades_seen": 0, "realised_return_var": 0.0, "recent_sharpe": 0.0 },
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{ "pnl_ema_win": 0.0, "pnl_ema_loss": 0.0, "win_rate_ema": 0.0, "n_trades_seen": 0, "realised_return_var": 0.0, "recent_sharpe": 0.0 },
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{ "pnl_ema_win": 2.0, "pnl_ema_loss": 0.5, "win_rate_ema": 0.8, "n_trades_seen": 50, "realised_return_var": 0.25, "recent_sharpe": 1.0 }
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]
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],
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"upload_h4_leaf_program": true,
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"events": [
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{
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"type": "snapshot",
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"bid_px": [5499.75, 5499.50, 5499.25, 5499.00, 5498.75, 5498.50, 5498.25, 5498.00, 5497.75, 5497.50],
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"bid_sz": [100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0],
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"ask_px": [5500.00, 5500.25, 5500.50, 5500.75, 5501.00, 5501.25, 5501.50, 5501.75, 5502.00, 5502.25],
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"ask_sz": [100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
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},
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{
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"type": "decision",
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"alpha_probs": [0.5, 0.5, 0.5, 0.5, 0.9],
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"target_annual_vol_units": 50.0,
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"annualisation_factor": 1.0,
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"max_lots": 5,
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"ts_ns": 1000000000
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}
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],
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"expected_pos": [
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{
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"position_lots": 3,
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"vwap_entry": 5500.00,
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"vwap_tol": 0.01,
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"realized_pnl_tol": 0.001
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}
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]
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}
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