Vega exposure leaders (with vanna, charm and vomma)
End-of-day data as of the Oct 29 close.
Names with the largest vega exposure in the assumed dealer book: the change in the book's option value for +1 vol point. Table also shows vanna (how the book's delta changes per vol point, the IV-driven hedging), vomma (how its vega changes per vol point), and charm flow (the dollars of the underlying the book's hedger trades per calendar day as time passes), all sortable. Vega, vanna, and vomma are the IV-sensitivity cluster; charm flow is a time effect that matters most around macro-event windows. Sibling to the gamma- and delta-exposure screeners.
Top 50 by Vega
The live vega-family leaderboard loads after the page hydrates. Default sort by absolute vega of the assumed dealer book; the live table allows re-sort by |vanna|, |charm flow|, or |vomma|.
Methodology
Vega, vanna, charm flow and vomma of the assumed dealer book at a dealer share of 1 (dealers long every call and short every put of open interest), over the expirations after the data date, computed nightly from the end-of-day chain. Default sort by |vega| descending; the live table re-sorts by |vanna|, |charm flow| or |vomma|. Eligibility: open interest of those expirations ≥ 50,000, spot ≥ $5.
Frequently Asked Questions
Why group these four Greeks?
Vega (dP/dIV, option-price sensitivity to implied volatility), vanna (cross spot times IV, how delta changes with IV moves, equivalently how vega changes with spot), and vomma (the change of vega with IV, the curvature of option value in IV) form the IV-sensitivity cluster. Charm flow (the delta rebalancing time alone forces, per calendar day) is a time effect rather than a pure IV-sensitivity Greek, but it is grouped with the others on this leaderboard because all four drive non-linear dealer-book behavior around macro events and earnings: periods where spot, IV, and time interact unpredictably. Gamma and delta have their own dedicated leaderboards; this screener is the remainder.
What does high net vega tell me?
High absolute vega exposure means the value of the assumed dealer book moves a lot with implied volatility on this name: positive when its long calls' vega outweighs its short puts', negative when the puts' outweighs. Where real dealers are short vega, they face pressure to buy options into vol expansions, amplifying the move; long vega, to sell into spikes, dampening it. Names with consistently high vega exposure are structurally important for vol-driven flow, and shifts in their net vega can precede or coincide with notable IV moves on the broader market when the name is a vol-leader (mega-cap tech ahead of earnings, broad-market ETFs ahead of FOMC).
When does vanna matter most?
Vanna is most relevant during macro-event windows (FOMC meetings, earnings releases, scheduled macro prints) where spot price and implied volatility can move in opposite directions. A typical vanna-driven flow: when IV drops post-event, a book's delta moves by its vanna times the IV change: on the assumed book, short the far out-of-the-money puts (whose vanna is negative, so the short position's is positive), the IV drop lowers the book's delta and its hedger buys, often producing flow that looks unrelated to price action but follows mechanically from the IV change. Vanna hedging is a known driver of post-event price moves on indexes and large-cap stocks where the option-book vanna is substantial.
Is charm just theta?
No. They are distinct first- and second-order time derivatives. Theta is option dollar-value decay (how much the option price drops per day, holding everything else constant). Charm is the change in delta from time alone: out-of-the-money deltas drift toward 0 and in-the-money ones toward 1 or -1, so the spot hedge needs to adjust mechanically as time passes. Charm is strongest on short-dated books, especially around weekly expirations and FOMC weeks where dealer hedges are repositioning rapidly. Charm-driven flow tends to be predictable in its timing (it follows the calendar) but unpredictable in its market impact, depending on inventory at each strike.
How fresh is the data on this screener?
All public screener data refreshes once per trading day after the 4:00 PM ET market close, typically available by 5:30 PM ET. The platform uses end-of-day OPRA aggregates which are licensed for free public display. Authenticated API-tier users with their own Tradier, tastytrade, Schwab, or moomoo BYOK credentials can pull intraday data through the streaming endpoints (Schwab streaming requires a Schwab app approved for Accounts and Trading).
Where does the underlying data come from?
End-of-day OPRA aggregates for the options data, exchange-published stock prices for the spot reference, and a calibrated implied-volatility surface computed from the listed chain. Ranking metrics like IV rank, GEX, and unusual-activity counts are computed nightly from these primary inputs. Methodology details are in each screener's "How it's computed" section above.
Are these stocks recommended trades?
No. The screener is a ranked list of names that meet a quantitative filter at the close of the prior trading session, a research starting point, not a buy or sell signal. Whether any name on the list represents a tradeable opportunity depends on the underlying catalyst, your strategy, current market context, and risk tolerance. The platform does not give trade advice; the lists are descriptive, not prescriptive.
How often does the ranking change?
The ranking refreshes every trading day after the close. Names move on and off the list as their underlying metric (IV rank, gamma exposure, volume, etc.) crosses thresholds. Most screeners show meaningful day-over-day churn at the top of the list during active markets and lower turnover during low-volatility regimes. The "biggest change" screeners specifically target fast-moving names.
Is the screener tradeable in real-time during market hours?
The screener itself ranks on end-of-day data. To trade names on the list during market hours, use your own broker's real-time chain data; the platform's per-ticker pages link directly to real-time chains for authenticated users. The screener's job is to surface the universe of candidates that met yesterday's filter; the trade decision uses live data.
Can I export the ranked list?
Pro and API tier users can export rankings via the API (REST endpoint per screener slug returns a JSON list with all metric columns) or pull them programmatically through the Python SDK. Free users have the full ranking visible on the page; programmatic access requires authentication. Daily snapshots are also available for backtesting research through the API tier.