jgrusewski 1f6a8436d3 feat: v9 Differential Sharpe Ratio reward — optimize for consistency, not PnL ...

Fundamental shift: reward optimizes Sharpe ratio contribution per trade
instead of directional PnL magnitude. Targets Sharpe 5+ via many small
consistent gains (spread capture, execution quality) instead of few
large directional bets.

DSR implementation (Moody & Saffell, 2001):
- Per-episode EMA statistics in portfolio state slots [3]-[5]
- DSR = (B*R - 0.5*A*R²) / (B - A²)^1.5 at trade completion
- 10-trade warmup, clamped [-5, +5]
- w_dsr=5.0 (primary reward signal)

Reward hierarchy restructured:
- DSR: 5.0 (NEW — primary, rewards Sharpe consistency)
- Directional PnL: 2.0 (was 10.0 — demoted to secondary)
- Order credit: 1.0 (was 0.1 — spread capture amplified 10×)
- Urgency credit: 0.5 (was 0.1 — fill quality amplified 5×)
- Inventory penalty: -0.005×|pos|/max_pos per bar (NEW)
- Dense micro-reward: 0.0 (removed — noisy direction signal)

Expected: WinRate increases (many small spread captures), per-trade
variance decreases, Sharpe rises from consistency not prediction.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-12 14:33:56 +02:00

..

backtesting

refactor: collapse 9-level to 7-level ExposureLevel — eliminate degenerate Flat variants

2026-04-11 11:54:09 +02:00

common

fix: switch tracing to stderr (unbuffered) — stdbuf has no effect on Rust

2026-04-02 16:29:55 +02:00

config

fix(ci): clippy test-gate uses --lib, fix pre-existing lint errors

2026-03-12 19:10:18 +01:00

ctrader-openapi

fix: tune log levels across workspace — demote noisy warn to debug/trace

2026-03-14 11:35:15 +01:00

data

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

database

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

market-data

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ml

feat: v9 Differential Sharpe Ratio reward — optimize for consistency, not PnL

2026-04-12 14:33:56 +02:00

ml-asset-selection

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-backtesting

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-checkpoint

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-core

cleanup: remove ALL GpuVarStore from DQN path + re-enable bottleneck_dim=16

2026-04-11 14:42:54 +02:00

ml-data

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ml-data-validation

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-dqn

WIP: training quality fixes + VarStore elimination (INCOMPLETE — needs xavier_init_params_buf)

2026-04-11 21:03:05 +02:00

ml-ensemble

feat(ensemble): GPU-native ensemble reduce kernel, remove CPU fallbacks

2026-03-29 22:35:37 +02:00

ml-explainability

feat(ensemble): GPU-native ensemble reduce kernel, remove CPU fallbacks

2026-03-29 22:35:37 +02:00

ml-features

test(data): per-file vs global front-month filter — documents quarterly roll bug

2026-04-08 21:31:46 +02:00

ml-hyperopt

refactor: LHS is the correct algorithm for small budgets, not a fallback

2026-03-29 19:18:47 +02:00

ml-labeling

fix(clippy): ml-supervised + ml-core + thin crates — 34 errors fixed

2026-03-19 00:39:03 +01:00

ml-observability

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-paper-trading

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-ppo

refactor: collapse 9-level to 7-level ExposureLevel — eliminate degenerate Flat variants

2026-04-11 11:54:09 +02:00

ml-regime

refactor(cuda): eliminate all CPU fallbacks — CUDA mandatory across ML stack

2026-03-16 21:01:28 +01:00

ml-regime-detection

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-risk

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-security

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-stress-testing

fix(clippy): achieve zero warnings across entire workspace

2026-03-10 13:18:57 +01:00

ml-supervised

cleanup: remove half crate dependency from entire workspace

2026-04-10 18:54:14 +02:00

ml-universe

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

ml-validation

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

model_loader

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

risk

refactor: eliminate candle from entire workspace — tests, examples, Cargo.toml

2026-03-18 00:53:47 +01:00

risk-data

fix: tune log levels across workspace — demote noisy warn to debug/trace

2026-03-14 11:35:15 +01:00

storage

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trading_engine

fix(ml): BF16/F32 boundary alignment, GPU-resident ops across all ML crates

2026-03-15 11:59:31 +01:00

trading-data

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training_uploader

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