perf: limit atr calculations to trailing window

[christianarriaga1234-coder]

Summary

Optimizes repeated ATR-style calculations by limiting each helper to the trailing candle window actually used by the formula. This keeps the public return values and warmup behavior intact while avoiding full-history scans on every strategy tick.

Type

• Bug fix
• New strategy
• New feature
• Refactor
• Documentation
• Tests
• Chore / dependency update

Related Issue

Refs #2

Changes

• Limit ATR helpers in risk sizing, volatility, momentum, and smart-money strategies to the last period + 1 candles.
• Limit the simplified ADX calculation to the trailing period needed for its final ATR/+DM/-DM values.
• Add regression tests that compare the optimized helpers against legacy full-history implementations on 5,000 candles.

Testing

• pytest tests/ passes locally
• New tests added for new code
• Manually tested (describe how): direct Python assertions for shared/tests/test_atr_tail_window.py passed.
• python -m py_compile app/strategies/quant_algos/risk_sizing.py app/strategies/quant_algos/volatility_algos.py app/strategies/quant_algos/momentum_algos.py app/strategies/quant_algos/smart_money.py shared/tests/test_atr_tail_window.py
• git diff --check on changed paths

Benchmark: synthetic 10,000-candle history, 2,000 repeated ATR calls. Legacy full-history scan: 8.428651s. Optimized trailing-window scan: 0.011347s. Speedup: 742.80x with equality asserted before timing.

Checklist

• No secrets, API keys, or private keys committed
• Type hints on all new public functions
• docs/connections/service-map.md updated (if adding a new call path)
• docs/architecture/data-model.md updated (if changing DB schema)
• New strategy registered in app/strategies/signals.py (if adding a strategy)
• New strategy added to strategy index in app/onchain_logger.py (if adding a strategy)
• Breaking changes documented in PR description

Screenshots (if UI change)

N/A

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