Global X - Robotics & Artificial Intelligence ETF (BOTZ) Options History
Historical options analytics archive for BOTZ with monthly max pain, implied volatility, gamma exposure, and put/call data.
109 months of complete options data available.
BOTZ monthly aggregates
Month-by-month rollups derived from the daily snapshot archive for BOTZ. Volatility and put/call columns are averages across trading days within the month; max pain, net GEX, and net DEX are the end-of-month values (last trading day of the month).
| Month | Days | Avg ATM IV | Avg IV Rank | End Max Pain | End Net GEX | End Net DEX | Avg P/C |
|---|---|---|---|---|---|---|---|
| 2026-06 | 21 | 30.8% | 61.8% | $37.00 | $195.0K | -$4.8M | 0.31 |
| 2026-05 | 20 | 28.5% | 52.2% | $39.00 | $497.8K | -$13.6M | 0.21 |
| 2026-04 | 21 | 29.9% | 50.0% | $33.00 | $184.6K | -$6.6M | 0.24 |
| 2026-03 | 22 | 32.8% | 39.6% | $34.00 | -$259.7K | $7.6M | 0.38 |
| 2026-02 | 19 | 28.8% | 30.8% | $35.00 | $502.5K | -$8.8M | 0.47 |
| 2026-01 | 20 | 23.2% | 22.4% | $38.00 | $312.9K | -$5.5M | 0.17 |
This archive aggregates BOTZ's daily end-of-day options snapshots into monthly summaries, spanning 2017-06 through 2026-06. Each month rolls up the underlying snapshot archive, which provides continuous end-of-day coverage from 2007 to present: implied-volatility levels, IV rank, and the put/call ratio are time-averaged across the month; total call and put volume are summed; and dealer positioning (net gamma and delta exposure) and the max-pain strike are taken at the month's final trading day. The result is a long-horizon view of how BOTZ option pricing, volatility regime, and dealer hedging pressure evolved month over month, useful for backtesting strategy assumptions and for studying volatility-regime shifts around earnings and macro events. The most recent aggregated month (2026-06) shows an average ATM implied volatility near 30.8%, a month-end max-pain strike around $37.00, an average put/call ratio of 0.31.
2026
Jan | Feb | Mar | Apr | May | Jun
2025
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2024
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2023
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2022
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2021
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2020
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2019
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2018
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
2017
Jun | Jul | Aug | Sep | Oct | Nov | Dec
Frequently asked BOTZ history questions
- How much options history is available for BOTZ?
- This archive holds 109 months of BOTZ options analytics, spanning 2017-06 through 2026-06. Each entry is a monthly rollup of BOTZ's daily end-of-day options snapshot record, which provides continuous coverage from 2007 to present. Use the year-grouped links on this page to jump to any specific month within the BOTZ archive.
- What data does each monthly BOTZ aggregate contain?
- Every monthly row summarizes that month of BOTZ option activity: time-averaged ATM implied volatility and IV rank, the month-end max-pain strike, end-of-month net dealer gamma (GEX) and delta (DEX) exposure, the average put/call ratio, and total call and put volume. For example, 2026-06 recorded an average ATM implied volatility near 30.8%, an average IV rank of 61.8%, a month-end max-pain strike around $37.00, an average put/call ratio of 0.31.
- How is the BOTZ options-history archive built and how often does it update?
- The archive is derived from BOTZ's daily end-of-day options snapshots, which capture spot, the full listed chain, implied volatility, and dealer-positioning exposures each trading day. Those daily records are rolled up into the monthly summaries shown here and refreshed as new end-of-day data lands. Traders use the long-horizon view to backtest strategy assumptions, study how BOTZ's volatility regime shifts around earnings and macro events, and compare current dealer positioning against historical norms.