GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market

Battle Count: 74

Highly relevant for quantitative trading. GIFsentiment provides a novel, high-frequency (daily and intraday 30-minute) sentiment signal that predicts S&P 500 returns with economically meaningful magnitudes: +27.3 bps contemporaneous and -126.5 bps next-month reversal (annualized -16.3%). The signal is incremental to five established sentiment measures. It also predicts volatility (+0.089 next-week), trading volume (+0.160 log contemporaneous), and fund flows (equity inflows +0.005, bond outflows -0.031 next-week). Effects are stronger for small-cap and high-volatility stocks, suggesting applicability to factor-based strategies. The intraday analysis (Table 6) with 10,493 observations at 30-minute intervals provides actionable short-term signals. However, implementation requires proprietary Stocktwits data access and real-time GIF sentiment calibration infrastructure.

Moderate-to-high complexity. Requires: (1) Large-scale data collection from Stocktwits API (65M+ posts with cashtags, GIF URLs, timestamps, self-declarations); (2) GIF deduplication and tracking via Giphy IDs; (3) Forward-expanding window sentiment calibration for 463K+ unique GIFs; (4) Daily aggregation with appearance-weighting; (5) Integration with multiple external data sources (CRSP, TAQ, EPFR, NOAA, EPU, ADS, RavenPack); (6) Moving block bootstrap and Nelson-Kim randomization for inference; (7) Real-time pipeline for intraday 30-minute sentiment construction. The econometric methods are standard, but the data engineering pipeline for visual content analysis at scale is non-trivial. No open-source code is provided.

The paper provides detailed variable definitions (Table A2), data sources (Stocktwits, EPFR, NOAA, Oxford COVID tracker, Baker-Bloom-Davis EPU, Aruoba-Diebold-Scotti ADS, RavenPack, COMPUSTAT, CRSP, TAQ), and construction formulas (Equations 1-6). However, the raw Stocktwits GIF data (65 million posts, 5.5 million with visuals, 463,227 unique GIFs) is proprietary and not publicly available. No code repository is provided. The GPT-4o validation procedure is described but not reproducible without API access. The moving block bootstrap and Nelson-Kim randomization procedures are standard but require implementation.