About

I'm Dahun Han. I'm a data scientist at i-ESG in Seoul, South Korea, and I built US Market Sentiment Watchdog to answer one question: when retail investors on Reddit and Wall Street's mainstream media disagree, who's actually right?

What I publish

Every morning, I publish a free daily newsletter that does two things most finance newsletters don't:

1. Reddit-vs-mainstream sentiment gap analysis. I scan r/stocks and r/wallstreetbets for high-conviction posts on US equities, then compare what retail investors are saying to how mainstream financial media is framing the same companies. When the gap is wide — when retail is bearish but Wall Street is bullish, or vice versa — that's a signal worth examining. Wide gaps with high upvote counts are often where genuine edge hides.

2. SEC EDGAR insider transaction tracking. I monitor Form 4 filings for HIGH-tier and CLUSTER insider sales and purchases — the kind where a CFO or division president is moving meaningful personal capital, especially without a pre-scheduled 10b5-1 trading plan. These filings are public, but most retail investors never see them. I surface the ones that matter and connect them back to the day's sentiment data.

Both signal types get published in the same daily newsletter, with one editorial voice, two scenarios for each prediction, and a specific time-bounded forecast in every "Mark's Take" closing section.

The track record

This is what makes US Market Sentiment Watchdog different from every other newsletter I've read.

Every signal I publish is registered in a public database the moment it goes out. I then track the actual price every day for 90 days, compare it against SPY over the same window, and report the alpha — the excess return above the market — at multiple holding periods: T+1, T+3, T+5, T+10, T+20, T+30, T+60, and T+90.

I don't pick a holding window in advance. I store all of them and let the data show which window actually matters for which signal type. If a signal type is losing money, it stays in the database next to the winners. No cherry-picking. No quiet deletions. The losers are just as visible as the wins.

You can audit the live database at crawdrift.com/track-record. It regenerates daily from the source SQLite database — no manual edits, no theatrics.

Why I built this

Most finance newsletters operate on a simple deception: show the wins, hide the losses, and trust that readers will conflate confidence with accuracy. After watching this pattern for years, I wanted to know whether sentiment-gap analysis and insider-tracking actually had predictive power, or whether the people selling these ideas were just lucky and loud.

The only way to find out was to track everything honestly and let the math decide.

So that's what this is. Real signals, a public dataset, alpha measured against SPY, every call documented win or lose. If the data eventually says my approach has no edge, I'll say so plainly and shut it down. If it has edge, the receipts are sitting in the database for anyone to verify.

Methodology in one paragraph

Reddit gaps fire when our sentiment score for a ticker diverges from mainstream framing by more than 0.5 (on a 0–1 scale) and the post crosses an upvote threshold. Edgar signals fire on HIGH-tier (large dollar value, senior insider) or CLUSTER (multiple insiders, same direction, tight time window) Form 4 filings — LOW and MEDIUM tier transactions are noise and not registered. For each registered signal, we capture the entry price (close on the publish day), then fetch SPY-adjusted prices daily for 90 days. The reported metric is direction-adjusted alpha: positive alpha always means "our call beat the market," whether the call was long or short. After 90 days, the signal closes and stops being tracked, but it stays permanently in the database for audit.

Who I am

Data Scientist at i-ESG in Seoul, South Korea. Background in commercial analytics and ESG reporting. I started building this project because I trade my own portfolio and got tired of newsletters that wouldn't show their math.

You can find me on LinkedIn — I'll update this with my actual profile URL when you're ready to be public.

How to follow

  • Daily newsletter (English): Subscribe at crawdrift.com — free, no upsells
  • Daily newsletter (Korean): Posted manually to my Naver Blog and Tistory each morning
  • Live track record: crawdrift.com/track-record — updated daily, no login required
  • Weekly review: Every Sunday I publish a longer track record post — what worked, what didn't, what I'm changing in the model

A note on what this is not

This is not financial advice. I trade my own portfolio based on these signals, but my situation is not yours. Everything published here is for educational and research purposes. Read the data, do your own work, make your own decisions.

This is also not a hedge fund. It's a one-person research project run with the philosophy that honesty about uncertainty is more useful than confidence about predictions. If you find that approach refreshing, you're probably my reader.

Last updated: April 2026. This page is hand-written and updated occasionally — for the latest signal performance, see the live track record.