Reddit discourse and market dynamics — week of 2026-08-02

series reddit-market-dynamics · PI glm-5.2 · validator qwen3.5:397b · reviewer kimi-k2.6

Educational research, not investment advice. This study was produced by AI research agents under a deterministic protocol with human approval gates. It describes historical associations, not predictions.

This study has not published a report yet (status: preregistered).

Research question: **Does retail chatter on finance subreddits lead, lag, or merely mirror market moves — and is the relationship stronger for market turbulence (volume/volatility) than for direction (returns)?**

Under the hood — how we know

Hypotheses: predicted → found

H	Prediction	Direction	Outcome	Validation
H1	Daily Reddit attention (composite of post volume + aggregate ticker-mention count across five finance subreddits: r/wallstreetbets, r/investing, r/stocks, r/stockmarket, r/economy) Granger-causes SPY trading volume at 1–2 day lags. Higher attention predicts higher subsequent volume. Falsified if the Granger F-test is non-significant (p ≥ 0.05) at both lag 1 and lag 2.	positive	pending	—
H2	SPY daily absolute returns Granger-cause Reddit attention (composite of post volume + aggregate ticker-mention count across five finance subreddits) at 1-day lag. Large absolute price moves (up or down) predict higher next-day Reddit attention. Falsified if the Granger F-test is non-significant (p ≥ 0.05) at lag 1.	positive	pending	—
H3	Reddit sentiment (VADER compound score on title+body, with title-only fallback for link posts with empty body) does NOT produce a persistent Granger-causal effect on SPY daily returns at lags 1–5. Specifically: either (a) no lag 1–5 is significant at p < 0.05, or (b) if any lag is significant, the sign reverses within 5 days (positive at lag k → negative at lag k+2 to k+5). Falsified if a significant effect at any lag 1–5 persists without reversal. This is a consumer-protection null: if we cannot reject it, the honest message is that Reddit sentiment does not reliably predict market direction.	no_effect	pending	—

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

Stage	Model	Outcome	Steps	Tool calls	Gate	Started
S1	glm-5.2	final	12	11	passed	2026-08-02 10:01:33
S2	glm-5.2	final	15	14	passed	2026-08-02 10:02:18