The Low-Volatility Anomaly
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weeklyseries ·
2026-08-22 · 115×4
Annualized volatility vs total return, 25 large caps, calmest to wildest (~2 years)ranking ·
2026-08-22 · 25×3
Volatility thirds: median return, and the range from worst to best name in eachtable ·
2026-08-22 · 3×6
Margin for Selling Naked Options: Reg T Math
One fixed short AAPL call strike: requirement as a percent of the share price, April to June 2026series ·
2026-08-22 · 62×4
Reg T minimum branches for one uncovered AAPL put, by strike (dollars per share)ranking ·
2026-08-22 · 11×4
Uncovered call minimum per contract, strike about 5% out of the moneyranking ·
2026-08-22 · 5×3
Reg T minimum branches for one uncovered AAPL call, by strike (dollars per share)ranking ·
2026-08-22 · 12×4
The Lowest-Volatility Stocks
The calmest large caps: annualized realized volatility over the past year, lowest firstranking ·
2026-08-22 · 15×2
Maximum drawdown of the calmest names: the worst peak-to-trough fall over the past yearranking ·
2026-08-22 · 8×2
Event Contract Collateral and Max Loss
Return on collateral for each side, by contract priceranking ·
2026-08-22 · 13×4
Near the money SPY put marks, May to June 2026series ·
2026-08-22 · 41×4
Buyer and seller collateral at every contract priceranking ·
2026-08-22 · 19×4
Short dated Treasury yields, trailing 18 monthsseries ·
2026-08-22 · 18×4
A 60 cent contract, annualised across holding periodsranking ·
2026-08-22 · 7×3
How Buffer ETFs Work: Caps and Resets
A 15% cap and 9% buffer, seen from three entry pointsranking ·
2026-08-12 · 21×4
SPY calendar-year price return against a 15% cap and 9% bufferranking ·
2026-08-12 · 12×3
Remaining buffer and remaining cap by entry pointranking ·
2026-08-12 · 11×3
Compounding the index against the buffered payoff, net of a 0.79% feeranking ·
2026-08-12 · 12×3
How Futures Margin Works: SPAN and Calls
SPY typical and largest daily move, month by month since 2019series ·
2026-08-10 · 91×4
Short term Treasury yields, the reference a stock margin loan is priced offseries ·
2026-08-10 · 91×4
One day move size across six household names, five years to July 2026ranking ·
2026-08-10 · 6×3
A decade of SPY daily closing moves, sorted into size bucketsranking ·
2026-08-10 · 6×3
Pin Risk at Options Expiration Explained
How far the Friday close lands from the nearest whole dollarranking ·
2026-08-09 · 10×3
AAPL's final half hour on its tightest monthly expiration close since 2025series ·
2026-08-09 · 30×5
Probability of Touch vs Probability ITM
SPY through July 2024 against a level 2% above the July 1 closeseries ·
2026-08-07 · 28×6
SPY: touched versus finished above, 21-session forward windows since 2011table ·
2026-08-07 · 4×5
SPY option delta buckets, with the doubling rule applied (Jan to Jun 2026)ranking ·
2026-08-07 · 9×4
What Is Maximum Drawdown? Depth vs Recovery
Same fund, five lookback windows: SPY maximum drawdown by sample length to July 31, 2026ranking ·
2026-08-05 · 5×3
Completed SPY drawdowns since 2016: depth, days falling, days climbing backtable ·
2026-08-05 · 8×5
SPY underwater curve: month end close against its running peak, 2016 to 2026series ·
2026-08-05 · 127×2
Maximum drawdown against annualized volatility: eight large caps, five years to July 31, 2026ranking ·
2026-08-05 · 8×3
How Risky Is Options Trading? The Mechanics
Weekend gaps: prior close to next open, six widely held names, August 2024 to July 2026table ·
2026-08-01 · 6×5
One AAPL call through its final month: closing premium split into intrinsic value and time valueseries ·
2026-08-01 · 23×5
Same AAPL call, same window: session moves for the contract and for the stockseries ·
2026-08-01 · 23×3
AAPL contracts trading on their own expiration day: share finishing out of the money, six monthly cyclesranking ·
2026-08-01 · 6×4
0DTE Options Strategies: How They Trade
Same-day options volume by premium paid: whole US tape, July 10, 2026ranking ·
2026-07-31 · 5×4
Median gamma, theta and delta by time to expiry: near-the-money US options, July 15, 2026table ·
2026-07-31 · 4×5
How July 10's same-day SPY contracts finished: expired at zero vs. settled with valueranking ·
2026-07-31 · 2×4
SPY intraday travel: close, high and low against the open, June 1 to July 10, 2026series ·
2026-07-31 · 28×5
The Best and Worst Thousand Dollars of June 2026
The ride, session by session: daily turnover, last price, and the thousand-dollar position's markseries ·
2026-07-26 · 10×6
The loss pile by root: contracts down 90%+ from first print, share of the pile, and each root's ten-baggerstable ·
2026-07-26 · 6×6
The most expensive ticket to zero: the priciest contract that ended at two cents or lessscalar ·
2026-07-26 · 1×510
The entry receipt: the winner's first print, its second, and every penny print of its June life (one row)scalar ·
2026-07-26 · 1×110.01
The full distribution: for every jackpot, thousands of near-total losses (put/call split included)scalar ·
2026-07-26 · 1×1030,951
The five biggest first-print-to-last-print multiples of June, priced from both chairs (six liquid roots, 50+ trades)table ·
2026-07-26 · 5×9
Calibration: every month of 2026 computed identically, SPY and NVDA, open-to-close and rangetable ·
2026-07-26 · 6×6
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly
Growth of $100: a calm name (KO), the market (SPY), a wild name (NVDA), weekly
| week | ko_calm | spy_market | nvda_wild |
|---|---|---|---|
| 2024-06-10 | 99.4 | 100.1 | 102 |
| 2024-06-17 | 99.7 | 100.3 | 98.2 |
| 2024-06-24 | 101.1 | 100.3 | 95.4 |
| 2024-07-01 | 101.2 | 102.3 | 97.2 |
| 2024-07-08 | 101.2 | 103.2 | 99.8 |
| 2024-07-15 | 103.7 | 101.2 | 91.2 |
| 2024-07-22 | 106.5 | 100.4 | 87.4 |
| 2024-07-29 | 110.1 | 98.3 | 82.9 |
| 2024-08-05 | 109.1 | 98.3 | 80.9 |
| 2024-08-12 | 109.9 | 102.2 | 96.3 |
| 2024-08-19 | 110.8 | 103.6 | 99.9 |
| 2024-08-26 | 115.1 | 103.9 | 92.3 |
| 2024-09-02 | 113 | 99.6 | 79.5 |
| 2024-09-09 | 113.4 | 103.6 | 92 |
| 2024-09-16 | 113.8 | 104.7 | 89.7 |
| 2024-09-23 | 114 | 105.3 | 93.8 |
| 2024-09-30 | 111.4 | 105.6 | 96.5 |
| 2024-10-07 | 110.5 | 106.8 | 104.2 |
| 2024-10-14 | 111.8 | 107.8 | 106.7 |
| 2024-10-21 | 106.3 | 106.8 | 109.4 |
| 2024-10-28 | 103.2 | 105.3 | 104.7 |
| 2024-11-04 | 101.5 | 110.3 | 114 |
| 2024-11-11 | 98 | 108 | 109.7 |
| 2024-11-18 | 101.5 | 109.8 | 109.7 |
| 2024-11-25 | 101.8 | 111.1 | 106.9 |
| 2024-12-02 | 99.3 | 112.1 | 110.1 |
| 2024-12-09 | 100.3 | 111.4 | 103.7 |
| 2024-12-16 | 99.4 | 108.9 | 104.3 |
| 2024-12-23 | 99.2 | 109.7 | 106 |
| 2024-12-30 | 98 | 109.1 | 111.8 |
| 2025-01-06 | 97 | 107 | 105 |
| 2025-01-13 | 99.6 | 110.2 | 106.5 |
| 2025-01-20 | 98.3 | 112.1 | 110.2 |
| 2025-01-27 | 100.8 | 111 | 92.8 |
| 2025-02-03 | 101.4 | 110.8 | 100.4 |
| 2025-02-10 | 109.4 | 112.4 | 107.3 |
| 2025-02-17 | 113.4 | 110.6 | 103.8 |
| 2025-02-24 | 113.1 | 109.5 | 96.7 |
| 2025-03-03 | 113.4 | 106.2 | 87.1 |
| 2025-03-10 | 109.8 | 103.8 | 93.9 |
| 2025-03-17 | 109 | 104 | 90.9 |
| 2025-03-24 | 111.8 | 102.5 | 84.7 |
| 2025-03-31 | 111.1 | 93.2 | 72.9 |
| 2025-04-07 | 113.3 | 98.4 | 85.6 |
| 2025-04-14 | 115.9 | 97 | 78.4 |
| 2025-04-21 | 114.2 | 101.5 | 85.8 |
| 2025-04-28 | 113.8 | 104.5 | 88.4 |
| 2025-05-05 | 112 | 104 | 90.1 |
| 2025-05-12 | 114.4 | 109.6 | 104.6 |
| 2025-05-19 | 114 | 106.8 | 101.5 |
| 2025-05-26 | 114.5 | 108.7 | 104.2 |
| 2025-06-02 | 113.3 | 110.4 | 109.5 |
| 2025-06-09 | 112.8 | 110.1 | 109.7 |
| 2025-06-16 | 109.3 | 109.6 | 111.1 |
| 2025-06-23 | 111.7 | 113.4 | 121.9 |
| 2025-06-30 | 113.3 | 115.3 | 123.1 |
| 2025-07-07 | 111 | 115 | 127.4 |
| 2025-07-14 | 110.9 | 115.7 | 133.2 |
| 2025-07-21 | 109.8 | 117.4 | 134.1 |
| 2025-07-28 | 109.3 | 114.6 | 134.2 |
| 2025-08-04 | 111.7 | 117.5 | 141.3 |
| 2025-08-11 | 111.1 | 118.6 | 139.5 |
| 2025-08-18 | 111.4 | 119 | 137.6 |
| 2025-08-25 | 109.6 | 118.9 | 134.7 |
| 2025-09-01 | 107.9 | 119.3 | 129.1 |
| 2025-09-08 | 106.4 | 121.2 | 137.4 |
| 2025-09-15 | 105.5 | 122.4 | 136.4 |
| 2025-09-22 | 104.2 | 122 | 137.7 |
| 2025-09-29 | 105.8 | 123.4 | 145 |
| 2025-10-06 | 106.5 | 120.4 | 141.5 |
| 2025-10-13 | 108.7 | 122.5 | 141.6 |
| 2025-10-20 | 110.7 | 124.8 | 144 |
| 2025-10-27 | 109.4 | 125.7 | 156.5 |
| 2025-11-03 | 112 | 123.7 | 145.5 |
| 2025-11-10 | 113 | 123.9 | 147.1 |
| 2025-11-17 | 115.9 | 121.5 | 138.3 |
| 2025-11-24 | 116.1 | 126 | 136.8 |
| 2025-12-01 | 111.1 | 126.4 | 141 |
| 2025-12-08 | 112 | 125.7 | 135.3 |
| 2025-12-15 | 111.3 | 125.5 | 139.9 |
| 2025-12-22 | 111 | 127.3 | 147.3 |
| 2025-12-29 | 109.8 | 126 | 145.9 |
| 2026-01-05 | 112 | 127.9 | 142.9 |
| 2026-01-12 | 111.8 | 127.5 | 143.9 |
| 2026-01-19 | 115.7 | 127.1 | 145.1 |
| 2026-01-26 | 118.9 | 127.6 | 147.9 |
| 2026-02-02 | 125.5 | 127.3 | 143.3 |
| 2026-02-09 | 124.9 | 125.7 | 141.3 |
| 2026-02-16 | 126.8 | 127.1 | 146.7 |
| 2026-02-23 | 129.5 | 126.5 | 136.9 |
| 2026-03-02 | 122.4 | 124 | 137.4 |
| 2026-03-09 | 122.8 | 122.1 | 139.3 |
| 2026-03-16 | 118.7 | 119.6 | 133.7 |
| 2026-03-23 | 120.2 | 116.9 | 129.4 |
| 2026-03-30 | 121.8 | 120.9 | 137.1 |
| 2026-04-06 | 123 | 125.2 | 145.8 |
| 2026-04-13 | 120.3 | 130.9 | 155.9 |
| 2026-04-20 | 121.7 | 131.6 | 160.9 |
| 2026-04-27 | 124.8 | 132.9 | 153.4 |
| 2026-05-04 | 124.5 | 136 | 166.3 |
| 2026-05-11 | 128.4 | 136.3 | 174.2 |
| 2026-05-18 | 129.4 | 137.5 | 166.4 |
| 2026-05-25 | 125.5 | 139.5 | 163.2 |
| 2026-06-01 | 126.3 | 136 | 158.5 |
| 2026-06-08 | 131.2 | 136.7 | 158.6 |
| 2026-06-15 | 126.1 | 137.6 | 162.5 |
| 2026-06-22 | 131.2 | 134.4 | 148.2 |
| 2026-06-29 | 133.4 | 137.3 | 150.4 |
| 2026-07-06 | 132.6 | 139.2 | 163.1 |
| 2026-07-13 | 129.5 | 137 | 156.6 |
| 2026-07-20 | 130.6 | 136.2 | 160 |
| 2026-07-27 | 139.1 | 137.7 | 155.2 |
| 2026-08-03 | 138.2 | 142.6 | 173.1 |
| 2026-08-10 | 139.3 | 143.1 | 174 |
| 2026-08-17 | 144.6 | 141.4 | 166.5 |
the exact SQL behind every number
WITH d AS (
SELECT ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
argMax(toFloat64(close), toTimeZone(window_start, 'America/New_York')) AS c
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('KO','SPY','NVDA')
AND window_start >= now() - INTERVAL 800 DAY
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY ticker, dt
),
r AS (
SELECT ticker, dt,
c / lagInFrame(c) OVER (PARTITION BY ticker ORDER BY dt) - 1 AS ret
FROM d
),
f AS (
SELECT ticker, dt, ret FROM r WHERE ret IS NOT NULL AND ret > -0.5 AND ret < 0.5
),
cum AS (
SELECT ticker, dt,
100 * exp(sum(log(1 + ret)) OVER (PARTITION BY ticker ORDER BY dt)) AS idx
FROM f
),
wk AS (
SELECT ticker, toMonday(dt) AS week, argMax(idx, dt) AS wv
FROM cum GROUP BY ticker, week
)
SELECT week,
round(maxIf(wv, ticker = 'KO'), 1) AS ko_calm,
round(maxIf(wv, ticker = 'SPY'), 1) AS spy_market,
round(maxIf(wv, ticker = 'NVDA'), 1) AS nvda_wild
FROM wk
GROUP BY week
ORDER BY week
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