momentum devandClaude Opus 4.8
a86fa43aa7
The human's edge is concentration (4 trades on 1 name) vs the bot's 12-trade spray. Added the mechanism: TRADING_CONCENTRATE_TOP_N (only the top-N armed names by rank may enter; rank-1 full risk, rank-2+ half) + TRADING_MAX_FRESH_ENTRIES_ PER_DAY (hard daily cap). rank threaded from the armed trigger -> submit_breakout_ now -> scales both the % budget and the $500 cap by rank_risk_factor. LEFT OFF by default (both 0): activating it meaningfully requires the rank key to be QUALITY, but the armed rank is currently gap*rvol*catalyst. Verification also found the roadmap's "quality_score" is calculate_data_quality_score = bar coverage/integrity (a thin-name/liquidity proxy with a time-of-day confound), correlated only weakly (q>=0.55 = 58% win / breakeven, NOT the 71% claimed; q<0.55 = 35% win / -$2,476). So concentration waits on a sound rank key (goal #2). pure rank_risk_factor + tests. No behavior change until the env flags are set. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
71 lines
3.0 KiB
Python
71 lines
3.0 KiB
Python
"""Account-aware position sizing: risk-based, capped by buying power + liquidity.
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Critical for a small REAL account ($300) — sizing must come off real equity and
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no single position can exceed buying power.
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"""
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from strategy.risk.position_sizing import (
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PositionSizingConfig,
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calculate_position_size,
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rank_risk_factor,
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)
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CFG = PositionSizingConfig(risk_per_trade_pct=0.01)
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def test_sizes_off_small_equity():
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# $300 equity, 1% = $3 risk; entry 4.00 stop 3.80 (risk 0.20) -> 14 shares
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# (3/0.20 = 14.999.. truncates down — conservative, never over-risk)
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r = calculate_position_size(4.0, 3.80, equity=300, config=CFG)
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assert r.position_size == 14
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assert r.dollar_amount <= 300 * CFG.risk_per_trade_pct / 0.20 * 4.0 + 1e-6
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def test_value_cap_binds_on_tight_stop():
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# tight stop -> risk-based wants 150 sh ($600); cap at $120 -> 30 shares
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r = calculate_position_size(4.0, 3.98, equity=300, config=CFG, max_position_value=120)
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assert r.position_size == 30
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assert r.dollar_amount <= 120 + 1e-6
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def test_liquidity_cap_binds():
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r = calculate_position_size(4.0, 3.80, equity=300, config=CFG, max_shares=5)
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assert r.position_size == 5
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def test_default_equity_when_unset():
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# no equity passed -> falls back to config default (not zero)
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r = calculate_position_size(4.0, 3.80, config=PositionSizingConfig(default_equity=100000))
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assert r.position_size > 0
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def test_max_risk_dollars_caps_wide_stop():
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# $90k, 1% = $900 budget; entry 2.00 stop 1.69 (0.31/sh wide stop)
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uncapped = calculate_position_size(2.00, 1.69, equity=90000, config=CFG)
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assert abs(uncapped.risk_amount - 900) < 2 # risks the full % budget
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capped = calculate_position_size(2.00, 1.69, equity=90000, config=CFG, max_risk_dollars=500)
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assert capped.position_size < uncapped.position_size # sized down
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assert 490 < capped.risk_amount <= 500.5 # hard $ cap honored (~$500)
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def test_max_risk_dollars_noop_when_budget_smaller():
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# small account: 1% of $300 = $3 budget << the $500 cap -> cap doesn't bind
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r = calculate_position_size(4.0, 3.80, equity=300, config=CFG, max_risk_dollars=500)
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assert r.position_size == 14 # unchanged from the % budget
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def test_risk_amount_reports_actual_not_budget():
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# after a binding value cap, risk_amount = the SIZED position's risk, not the budget
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r = calculate_position_size(4.0, 3.98, equity=300, config=CFG, max_position_value=120)
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assert r.position_size == 30
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assert abs(r.risk_amount - 30 * 0.02) < 1e-6 # ~$0.60 actual, not the $3 budget
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def test_rank_risk_factor_concentrates():
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assert rank_risk_factor(1, 0) == 1.0 # concentration OFF -> full
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assert rank_risk_factor(5, 0) == 1.0
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assert rank_risk_factor(1, 2) == 1.0 # rank-1 full budget
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assert rank_risk_factor(2, 2) == 0.5 # rank-2 half
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assert rank_risk_factor(3, 2) == 0.0 # outside top-2 -> skip
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assert rank_risk_factor(0, 2) == 1.0 # unranked -> not concentrated
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