AeroVironment (AVAV)

EarningsTranscriptsUpdated

As of Oct 23, 2026, Kalshi has settled 12 word markets on AeroVironment’s earnings calls since 2026, on 12 different words. Next call: Dec 8, 2026 (14 words listed).

Next: Earnings call ·

14 words listed · Occasion page

Who counts: Kalshi: company speakers + operator

Kalshi

AeroVironment: the words listed for Tue, Dec 8, how often each was said on past occasions, and the probability for this one
WordQ2’25Dec '24Q3’25Mar '25Q4’25Jun '25Q1’26Sep '25Q2’26year agoQ3’26Mar '26Q4’26Jun '26Q1’27last callTrendLast 8ScriptedAll-timeProbabilityMarket
AV Halo0 times: AV Halo, Q2’25 Dec '240 times: AV Halo, Q3’25 Mar '250 times: AV Halo, Q4’25 Jun '250 times: AV Halo, Q1’26 Sep '2518 times: AV Halo, Q2’26 Dec '25, counts as said1 time: AV Halo, Q3’26 Mar '26, counts as said4 times: AV Halo, Q4’26 Jun '26, counts as said0 times: AV Halo, Q1’27 Sep '26rising3/838%3/838%3/665%78%n=1+tx from settlement history blended with transcripts66¢ Kalshi
Space Force0 times: Space Force, Q2’25 Dec '241 time: Space Force, Q3’25 Mar '25, counts as said1 time: Space Force, Q4’25 Jun '25, counts as said1 time: Space Force, Q1’26 Sep '25, counts as said2 times: Space Force, Q2’26 Dec '25, counts as said14 times: Space Force, Q3’26 Mar '26, counts as said3 times: Space Force, Q4’26 Jun '26, counts as said0 times: Space Force, Q1’27 Sep '26rising6/875%3/838%6/669%76%transcripts from the transcript model40¢ Kalshi
Golden Dome0 times: Golden Dome, Q2’25 Dec '240 times: Golden Dome, Q3’25 Mar '250 times: Golden Dome, Q4’25 Jun '257 times: Golden Dome, Q1’26 Sep '25, counts as said1 time: Golden Dome, Q2’26 Dec '25, counts as said6 times: Golden Dome, Q3’26 Mar '26, counts as said1 time: Golden Dome, Q4’26 Jun '26, counts as said1 time: Golden Dome, Q1’27 Sep '26, counts as saidrising5/862%5/862%5/668%75%n=1+tx from settlement history blended with transcripts77¢ Kalshi
Iran / Middle East0 times: Iran / Middle East, Q2’25 Dec '240 times: Iran / Middle East, Q3’25 Mar '250 times: Iran / Middle East, Q4’25 Jun '250 times: Iran / Middle East, Q1’26 Sep '250 times: Iran / Middle East, Q2’26 Dec '2510 times: Iran / Middle East, Q3’26 Mar '26, counts as said0 times: Iran / Middle East, Q4’26 Jun '267 times: Iran / Middle East, Q1’27 Sep '26, counts as saidrising2/825%1/812%15/6623%72%transcripts from the transcript model55¢ Kalshi
BlueHalo / Blue Halo3+ times6 times: BlueHalo / Blue Halo (3+ times), Q2’25 Dec '24, counts as said12 times: BlueHalo / Blue Halo (3+ times), Q3’25 Mar '25, counts as said17 times: BlueHalo / Blue Halo (3+ times), Q4’25 Jun '25, counts as said19 times: BlueHalo / Blue Halo (3+ times), Q1’26 Sep '25, counts as said9 times: BlueHalo / Blue Halo (3+ times), Q2’26 Dec '25, counts as said12 times: BlueHalo / Blue Halo (3+ times), Q3’26 Mar '26, counts as said9 times: BlueHalo / Blue Halo (3+ times), Q4’26 Jun '26, counts as said1 time: BlueHalo / Blue Halo (3+ times), Q1’27 Sep '26, below the thresholdfalling7/888%7/888%7/6611%68%transcripts from the transcript model54¢ Kalshi
Supply Chain1 time: Supply Chain, Q2’25 Dec '24, counts as said1 time: Supply Chain, Q3’25 Mar '25, counts as said0 times: Supply Chain, Q4’25 Jun '250 times: Supply Chain, Q1’26 Sep '251 time: Supply Chain, Q2’26 Dec '25, counts as said2 times: Supply Chain, Q3’26 Mar '26, counts as said0 times: Supply Chain, Q4’26 Jun '266 times: Supply Chain, Q1’27 Sep '26, counts as saidrising5/862%4/850%26/6639%63%n=1+tx from settlement history blended with transcripts64¢ Kalshi
Red Dragon3+ times0 times: Red Dragon (3+ times), Q2’25 Dec '240 times: Red Dragon (3+ times), Q3’25 Mar '2511 times: Red Dragon (3+ times), Q4’25 Jun '25, counts as said0 times: Red Dragon (3+ times), Q1’26 Sep '253 times: Red Dragon (3+ times), Q2’26 Dec '25, counts as said7 times: Red Dragon (3+ times), Q3’26 Mar '26, counts as said11 times: Red Dragon (3+ times), Q4’26 Jun '26, counts as said2 times: Red Dragon (3+ times), Q1’27 Sep '26, below the thresholdrising4/850%3/838%4/666%53%transcripts from the transcript model41¢ Kalshi
Tailwind0 times: Tailwind, Q2’25 Dec '240 times: Tailwind, Q3’25 Mar '251 time: Tailwind, Q4’25 Jun '25, counts as said0 times: Tailwind, Q1’26 Sep '250 times: Tailwind, Q2’26 Dec '250 times: Tailwind, Q3’26 Mar '261 time: Tailwind, Q4’26 Jun '26, counts as said1 time: Tailwind, Q1’27 Sep '26, counts as saidrising3/838%3/838%3/665%51%n=1+tx from settlement history blended with transcripts64¢ Kalshi
Taiwan3 times: Taiwan, Q2’25 Dec '24, counts as said0 times: Taiwan, Q3’25 Mar '250 times: Taiwan, Q4’25 Jun '250 times: Taiwan, Q1’26 Sep '252 times: Taiwan, Q2’26 Dec '25, counts as said1 time: Taiwan, Q3’26 Mar '26, counts as said0 times: Taiwan, Q4’26 Jun '261 time: Taiwan, Q1’27 Sep '26, counts as saidfalling4/850%3/838%7/6611%47%n=1+tx from settlement history blended with transcripts48¢ Kalshi
Orbit0 times: Orbit, Q2’25 Dec '240 times: Orbit, Q3’25 Mar '250 times: Orbit, Q4’25 Jun '250 times: Orbit, Q1’26 Sep '251 time: Orbit, Q2’26 Dec '25, counts as said0 times: Orbit, Q3’26 Mar '262 times: Orbit, Q4’26 Jun '26, counts as said0 times: Orbit, Q1’27 Sep '26rising2/825%2/825%4/666%45%n=1+tx from settlement history blended with transcripts60¢ Kalshi
Robot / Robotic / Robotics0 times: Robot / Robotic / Robotics, Q2’25 Dec '241 time: Robot / Robotic / Robotics, Q3’25 Mar '25, counts as said3 times: Robot / Robotic / Robotics, Q4’25 Jun '25, counts as said0 times: Robot / Robotic / Robotics, Q1’26 Sep '255 times: Robot / Robotic / Robotics, Q2’26 Dec '25, counts as said0 times: Robot / Robotic / Robotics, Q3’26 Mar '260 times: Robot / Robotic / Robotics, Q4’26 Jun '260 times: Robot / Robotic / Robotics, Q1’27 Sep '26falling3/838%2/825%27/6641%40%n=1+tx from settlement history blended with transcripts40¢ Kalshi
Headwind0 times: Headwind, Q2’25 Dec '240 times: Headwind, Q3’25 Mar '250 times: Headwind, Q4’25 Jun '250 times: Headwind, Q1’26 Sep '250 times: Headwind, Q2’26 Dec '251 time: Headwind, Q3’26 Mar '26, counts as said0 times: Headwind, Q4’26 Jun '260 times: Headwind, Q1’27 Sep '26steady1/812%1/812%12/6618%20%n=1+tx from settlement history blended with transcripts28¢ Kalshi
NATO0 times: NATO, Q2’25 Dec '241 time: NATO, Q3’25 Mar '25, counts as said0 times: NATO, Q4’25 Jun '251 time: NATO, Q1’26 Sep '25, counts as said0 times: NATO, Q2’26 Dec '250 times: NATO, Q3’26 Mar '260 times: NATO, Q4’26 Jun '260 times: NATO, Q1’27 Sep '26falling2/825%2/825%8/6612%17%n=1+tx from settlement history blended with transcripts21¢ Kalshi
Backpackable0 times: Backpackable, Q2’25 Dec '240 times: Backpackable, Q3’25 Mar '250 times: Backpackable, Q4’25 Jun '250 times: Backpackable, Q1’26 Sep '250 times: Backpackable, Q2’26 Dec '250 times: Backpackable, Q3’26 Mar '260 times: Backpackable, Q4’26 Jun '260 times: Backpackable, Q1’27 Sep '26steady0/80%0/80%3/665%12%n=1+tx from settlement history blended with transcripts20¢ Kalshi
  • times said on that call
  • counted as said (ring)
  • no call
  • probability next time, with n
  • Select a word or a cell for its quotes
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Market prices are mid quotes from Kalshi and Polymarket, shown for context, may be delayed by several minutes and are not a signal. Quotes as of Oct 20, 2026 15:46 UTC.

Every word

1–2 of 2, most settled first
AeroVironment: every word with settled markets, most settled first
WordQ2’25Dec '24Q3’25Mar '25Q4’25Jun '25Q1’26Sep '25Q2’26Dec '25Q3’26Mar '26Q4’26Jun '26Q1’27last callTrendLast 8ScriptedAll-timeProbability
Class Actionnever said0 times: Class Action, Q2’25 Dec '240 times: Class Action, Q3’25 Mar '250 times: Class Action, Q4’25 Jun '250 times: Class Action, Q1’26 Sep '250 times: Class Action, Q2’26 Dec '250 times: Class Action, Q3’26 Mar '260 times: Class Action, Q4’26 Jun '260 times: Class Action, Q1’27 Sep '26steady0/80%0/80%0/660%12%n=1+tx from settlement history blended with transcripts
Iran0 times: Iran, Q2’25 Dec '240 times: Iran, Q3’25 Mar '250 times: Iran, Q4’25 Jun '250 times: Iran, Q1’26 Sep '250 times: Iran, Q2’26 Dec '2510 times: Iran, Q3’26 Mar '26, counts as said0 times: Iran, Q4’26 Jun '261 time: Iran, Q1’27 Sep '26, counts as saidrising2/825%1/812%2/663%58%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Appearances and settled record

latest 12

Our transcript counts matched how 12 of 12 settled words resolved (100.0%). How we check.

Citeparrot.markets, “AeroVironment (AVAV): earnings call word history”, as of Oct 23, 2026, https://parrot.markets/earnings/AVAV (CC BY 4.0)

Agents: this page as TSV at /api/v1/entity/aerovironment · words: /api/v1/history?entity=aerovironment · columnar JSON in #parrot-data · llms.txt · MCP