Reddit sentiment lead-follow dynamics with market prices

Hypotheses: predicted → found

Datasets

Pre-registration amendments

• [2026-07-31 09:37:33] H1 · test_plan.params.subreddit_stratification — Collection returned only 4 distinct subreddits out of the 5 preregistered. r/stocks has 0 posts in the 2025-08-02 to 2026-06-30 window (the source profile notes r/stocks was added late to the collector). Per-subreddit stratification as robustness will cover 4 subreddits instead of 5. (stage S3)
• [2026-07-31 09:37:36] H2 · test_plan.params.sentiment_construction — Collection returned only 4 distinct subreddits (r/stocks absent). Sentiment construction and stratification must reflect the actual 4-subreddit pool. Content field is 59.5% non-null (18,579/31,215 posts have body text); posts with null content will use title text for VADER scoring as is standard for short-form social media. (stage S3)
• [2026-07-31 09:37:38] H3 · test_plan.params — Collection returned only 4 distinct subreddits (r/stocks absent). Attention measure must reflect the actual 4-subreddit pool. (stage S3)

Activity log (per-stage summaries — no raw model transcripts)

Limitations & lessons

• [limitation] Only 4 of 5 preregistered subreddits are present in the collected data. r/stocks has 0 posts in the 2025-08-02 to 2026-06-30 window (the source profile notes r/stocks was added late to the collector). All subreddit-stratified robustness analyses will cover 4 subreddits instead of 5. This reduces the representativeness of the subreddit pool.
• [limitation] Reddit content (body text) field is only 59.5% non-null (18,579 of 31,215 posts). 12,636 posts have empty content bodies — these are link posts or posts with title-only content. For VADER sentiment scoring (H2), posts with null content will need to use title text as the text input. This may reduce sentiment classification quality for title-only posts, which tend to be shorter and less sentiment-rich.
• [limitation] Ticker mentions are only 13.4% non-null (4,197 of 31,215 posts). This means the ticker-mention-based robustness specifications in H1 (above_median_ticker_mentions_t) will be based on a sparse signal — most days will have very few or zero ticker mentions. The median split on ticker mentions may be dominated by zeros, reducing the discriminative power of this robustness check.
• [limitation] Reddit archive has ~65 missing collection days across the 2025-08-02 to 2026-06-29 span (270 distinct source_dates out of ~335 calendar days). The preregistration specifies no forward-filling of Reddit gaps — missing days are dropped from the panel. After inner join with SPY/VIX trading days (~228-229), the effective sample size will be further reduced. With lag-1 boundary loss, the effective N for regression designs may approach or fall below the 150-observation downgrade threshold specified in H2.
• [limitation] VIX dataset (dataset 38) has 229 rows while SPY dataset (dataset 37) has 228 rows — a 1-row discrepancy. This likely reflects a trading day where VIX was quoted but SPY was not (or vice versa). The inner join specified in the calendar_rule will reconcile this, but the extra VIX row will be lost. Additionally, VIX volume is all 0 (expected for an index), confirming the data is structurally correct but volume is non-informative.
• [limitation] SPY and VIX data start at 2025-08-04 (first trading day; 2025-08-02 was a Saturday). Reddit data starts at 2025-08-02. The inner join will naturally exclude the non-trading-day Reddit rows, but this means the effective analysis window begins 2025-08-04, not 2025-08-02 as preregistered.
• [limitation] Yahoo Finance data was fetched with auto_adjust=True, so 'close' already contains split/dividend-adjusted prices and there is no separate 'adj_close' column. The preregistration references 'close' for log return calculations, which is functionally equivalent to 'adj_close' under auto_adjust=True. This is documented per the yfinance-auto-adjust-column-equivalence lab skill.
• [limitation] H2 VALIDATION GATE BLOCKED: The sentiment audit (audit_sentiment_subsample) could not execute because the LLM labeling service returned a billing error (402: extra usage balance empty). The preregistration requires Cohen's κ ≥ 0.70 from two independent LLM coders against VADER before H2 can be tested. Since the audit cannot run, the validation gate is not passed. Per the preregistration, H2 is dropped and only attention-based H1/H3 proceed. VADER sentiment scores (dataset 39) remain computed but UNVALIDATED — they may be used descriptively but cannot support confirmatory H2 claims.
• [defer] agent deferred in S4 H1: I have not completed the confirmatory analysis. I gathered descriptive statistics and dataset schemas but did not execute any of the four pre-registered regressions, did not construct the merged lagged panel, and did not apply the Holm correction. The test ledger still shows 0 executed tests. I will not fabricate results. DECISION: DEFER What I would need to complete S4 for H1: 1. **Merged pane
• [retrospective] S7 outcome=final; proposed 2 skill(s): ['construct-analysis-panel-before-s4-reconnaissanc', 'audit-zero-inflation-before-median-split']. RETROSPECTIVE: This study deferred because S4 reconnaissance consumed the step budget without ever constructing the merged lagged panel required for confirmatory regressions, revealing a critical sequencing gap between data exploration and analysis construction. Additionally, a preregistered median-split robustness check on ticker mentions would have been statistically degenerate due to 86.6% null values, highlighting the need to validate distributional assumptions before locking in threshold-based specifications. The LLM audit billing error that blocked H2 underscores the importance of the al