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T04 · Momentum

Value and Momentum Everywhere

Clifford S. Asness et al. (3 authors), 2013 · The Journal of Finance

9%
pass@1 across 16 systems
5/16
systems with ≥1 successful attempt
2/5
2/5 attempts passed for the best system
80 attempts · 16 systems × 5
Claude Code + Opus 5
40%
Claude Code + Opus 4.8
40%
Claude Code + Opus 4.7
0%
Codex + GPT-5.6-sol
0%
Codex + GPT-5.5
20%
OpenCode + Kimi-K3
20%
OpenCode + Opus 4.7
0%
OpenCode + GPT-5.5
20%
OpenCode + Sonnet 4.6
0%
OpenCode + Qwen3.7-Max
0%
OpenCode + GLM-5.2
0%
OpenCode + DeepSeek V4-Pro
0%
OpenCode + GLM-5.1
0%
OpenCode + Qwen 3.6 Plus
0%
OpenCode + MiniMax-M3
0%
OpenCode + MiniMax M2.7
0%
all checkers pass Type-A clean, Type-B fail fail checking timeout no result / incomplete
Strategy

What the paper asks for.

Within and across eight asset classes, simple value (5-year reversal) and 12-2 momentum signals each earn premia, and a 50/50 value-momentum combo aggregated by inverse-volatility across markets produces a high-Sharpe long-short factor that dominates either signal alone.

Type
technical
Implementation
pandas
Rebalance
monthly
Long-short
yes
Declared task setup
Data
One-command fetcher for WRDS-sourced task data
Operational scope
Use executable country and cross-asset proxy series, harmonized return mappings, and a common overlap window for the value-momentum strategy.
Six-stage quantitative strategy pipeline
  1. 01 Data loading
  2. 02 Feature engineering
  3. 03 Model fitting
  4. 04 Signal generation
  5. 05 Portfolio construction
  6. 06 Execution
Checker suite

19 properties · 80 attempts.

Each row is one requirement the strategy must satisfy. The bar reports the share of observed checker verdicts that pass; missing checker output is not converted into a property verdict.

TYPE A · DOMAIN-LEVEL (9)
  • A1
    no backfill
    §§I.B “book values are lagged 6 months”
    stage · data loading
    39/75
  • A2
    no global normalize
    §Eq (1) “w_it^S = c_t × (rank(S_it) − (1/N_t) Σ_j rank(S_jt))”
    stage · feature eng
    71/75
  • A3
    no future data access
    §§I.B (stocks) “book values are lagged 6 months”
    stage · feature eng
    62/75
  • A4
    causal consistency
    §execution_plan.trigger.delay_bars=1 “monthly rebalancing based on value-momentum combination trade signal... delay_bars: 1”
    stage · signal gen
    70/75
  • A5
    no survivorship bias
    §§I.A “354 firms in Jan 1972, 676 firms in Jul 2011”
    stage · data loading
    53/75
  • A7
    data frequency alignment
    §§I.B “book values are lagged 6 months”
    stage · data loading
    57/75
  • A8
    transaction timing
    §execution_plan.trigger “frequency: monthly, price_type: close, delay_bars: 1”
    stage · execution
    66/75
  • A9
    signal delay test
    §spec.indicators.momentum_12m “Past 12-month cumulative raw return on the asset, excluding the most recent month's return”
    stage · feature eng
    38/75
  • A10
    e2e metric consistency
    §Table III / §II “Global Combo factor Sharpe = 1.45”
    25/75
TYPE B · PAPER-SPECIFIC (10)
  • B1
    value signal stocks formula
    §§I.B “Book values are lagged 6 months to ensure data availability to investors at the time, and the most recent market values are used to compute the ratios.”
    provenance · paper-explicit
    stage · feature eng
    75/75
  • B2
    momentum 2 to 12 skip recent
    §§I.B “the return over the past 12 months skipping the most recent month”
    provenance · paper-explicit
    stage · feature eng
    32/75
  • B3
    signal rank weight eq1
    §Eq (1) “w_it^S = c_t (rank(S_it) − Σ_i rank(S_it)/N)”
    provenance · paper-explicit
    stage · portfolio construction
    71/75
  • B4
    combo 50 50 formula
    §Eq (3) “50/50 equal combination (COMBO) factor of value and momentum”
    provenance · paper-explicit
    stage · portfolio construction
    75/75
  • B5
    value signal commodity neg5y log
    §§I.B “log of the spot price 5 years ago (actually, the average spot price from 4.5 to 5.5 years ago), divided by the most recent spot price”
    provenance · paper-explicit
    stage · feature eng
    59/75
  • B6
    value signal bond 5y yield change
    §§I.B “For bonds, we use the 5-year change in the yields of 10-year bonds as our value measure”
    provenance · paper-explicit
    stage · feature eng
    53/75
  • B7
    inverse vol aggregation
    §§I, p612 “weighting each market by the inverse of their ex post sample standard deviation”
    provenance · paper-explicit
    stage · portfolio construction
    48/75
  • B8
    universe stocks exclusions
    §§I.A “We exclude ADRs, REITs, financials, closed-end funds, foreign shares, and stocks with share prices less than $1 at the beginning of each month”
    provenance · paper-explicit
    stage · data loading
    52/75
  • B9
    book value lag 6 months
    §§I.B “Book values are lagged 6 months to ensure data availability to investors at the time”
    provenance · paper-explicit
    stage · data loading
    45/75
  • B10
    begin of month price cutoff 1usd
    §§I.A “stocks with share prices less than $1 at the beginning of each month”
    provenance · paper-explicit
    stage · data loading
    72/75
What this task reveals

The lowest-passing observed requirement is e2e metric consistency: 25 of 75 observed checker verdicts pass. The full property list above shows whether errors concentrate in domain-level validity or the paper-specific strategy logic.

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