STRASMORE/EXPLORE 2,272 QUERIES 22Y EQUITIES · 12Y OPTIONS

2,272 answered market questions

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Xetra Trading Hours and Holidays 2026–2027
Weekdays, weekday closures and Xetra sessions per calendar yeartable · 2026-09-16 · 2×5 Days when the New York open lands at 14:30 Frankfurt time (three-hour overlap), 2026 and 2027series · 2026-09-16 · 4×5Preview: a 4-point series, ending lower. Xetra non-trading days 2027, from the Deutsche Börse trading calendartable · 2026-09-16 · 8×5 Xetra non-trading days 2026, from the Deutsche Börse trading calendartable · 2026-09-16 · 8×5
Why Relative Volume Differs Between Platforms
Five relative-volume definitions on one AAPL session, at 10:30 a.m. ET and at the closeranking · 2026-09-16 · 5×3Preview: 5 ranked values, smallest first. One AAPL session, four lookbacks: full-day relative volume from daily barsranking · 2026-09-16 · 4×4Preview: 4 ranked values, largest first. How the session's volume piled up against the prior 10 sessions, checkpoint by checkpointseries · 2026-09-16 · 14×4Preview: a 14-point series, ending higher. Same session, same 10-session lookback: same-time basis vs full-day basis through the dayseries · 2026-09-16 · 14×3Preview: a 14-point series, ending higher.
What Is Backtesting in Trading?
Distance from one close to the next open, liquid names, 2025 (basis points)ranking · 2026-09-16 · 5×3Preview: 5 ranked values, largest first.
What Is a High VIX? Levels and Extremes
SPY realized volatility by calendar year, with the biggest day and the count of 2%+ sessionsranking · 2026-09-16 · 23×4Preview: 16 ranked values, smallest first. SPY daily closes from the VIX record close (March 16, 2020) through March 27series · 2026-09-16 · 10×4Preview: a 10-point series, ending higher. SPY on August 5, 2024, in half-hour buckets (ET): the low and the close of eachseries · 2026-09-16 · 13×3Preview: a 13-point series, ending higher. SPY 30-day at-the-money implied volatility, sessions per VIX-style rungranking · 2026-09-16 · 4×4Preview: 4 ranked values, largest first.
Short Delivery Auction in India: NSE Rules
Rule 204 close-out deadline for a short-sale fail, by trade date (US sessions, trailing weeks)series · 2026-09-16 · 15×6Preview: a 15-point series, roughly flat. SEBI's close-out formula applied to a US tape (AAPL, trailing three weeks, illustrative)series · 2026-09-16 · 14×4Preview: a 14-point series, ending higher.
How to Backtest a Trading Strategy in Python
Three runs of backtest.py on the illustrative 60-bar fileranking · 2026-09-16 · 3×4Preview: 3 ranked values, smallest first.
Futures Tick Size and Tick Value Explained
Worked P&L examples: ticks moved x tick value x contracts (hypothetical)table · 2026-09-16 · 7×5 Outright tick size and tick value per contract, CME specifications, September 2026ranking · 2026-09-16 · 10×4Preview: 10 ranked values, smallest first. Calendar spread tick versus outright tick, dollars per contract, CME specifications, September 2026ranking · 2026-09-16 · 10×4Preview: 10 ranked values, smallest first.
Dividend Increases Expected This Month
MSFT dividend raise declarations, 2019 to 2025 (pinned)series · 2026-09-16 · 7×6Preview: a 7-point series, ending lower. Companies expected to raise their dividend this month, declared names firstseries · 2026-09-16 · 13×7Preview: a 13-point series, roughly flat. When dividend raises get declared: share by calendar month, starting from this monthranking · 2026-09-16 · 12×3Preview: 12 ranked values, smallest first. Declared vs. still expected: this month in each of the last six yearsseries · 2026-09-16 · 6×4Preview: a 6-point series, ending lower.
Weekly Market Recap: The Week in Numbers
Where the volume went: most dollars traded over the past weekranking · 2026-09-15 · 8×2Preview: 8 ranked values, largest first. The eleven S&P 500 sectors over the past weekranking · 2026-09-15 · 11×2Preview: 11 ranked values, largest first. Biggest stock losers over the past weekranking · 2026-09-15 · 7×3Preview: 7 ranked values, smallest first. The major index ETFs over the past weekranking · 2026-09-15 · 4×4Preview: 4 ranked values, largest first. Biggest stock gainers over the past weekranking · 2026-09-15 · 7×3Preview: 7 ranked values, largest first. Daily market breadth: advancers vs decliners each session (names trading $500M+)series · 2026-09-15 · 5×3Preview: a 5-point series, ending lower.
Upcoming Stock Splits Calendar
Upcoming US stock splits: announced, with a future effective datetable · 2026-09-15 · 30×5 Announced upcoming splits by directionranking · 2026-09-15 · 2×2Preview: 2 ranked values, largest first. Announced stock splits by effective month: forward vs reverseseries · 2026-09-15 · 4×4Preview: a 4-point series, ending lower.
Upcoming Ex-Dividend Dates: Stocks This Week
Three household payers at their last ex-date: prior close, ex-morning open, and the payment for scaleseries · 2026-09-15 · 3×8Preview: a 3-point series, roughly flat. Who goes ex-dividend in the next 14 days: names, cadence and implied yield by size bandtable · 2026-09-15 · 4×5 Names going ex-dividend, day by day: the next seven days of declared recordsseries · 2026-09-15 · 5×5Preview: a 5-point series, ending lower. Ex-dividend dates by calendar month: three-year average, quarterly vs monthly payersseries · 2026-09-15 · 12×4Preview: a 12-point series, ending higher. Thirteen big dividend and income funds: last ex-date, cadence, and the implied next ex-dateseries · 2026-09-15 · 13×8Preview: a 13-point series, roughly flat. Forward-declared ex-dividend records on file: the receipt behind this calendarscalar · 2026-09-15 · 1×53,507 Every mega-cap ex-dividend event of the past six months: price path from the pre-ex closetable · 2026-09-15 · 5×6 Largest companies going ex-dividend in the next 14 days: amount, pay date, indicated yieldseries · 2026-09-15 · 12×8Preview: a 12-point series, ending higher.
Unusual Volume Stocks This Week, Measured
How the whole qualifying universe traded this week, bucketed by relative volumeranking · 2026-09-15 · 7×4Preview: 7 ranked values, smallest first. Persistence check: the eight leaders' daily relative volume across the five sessionstable · 2026-09-15 · 8×5 Highest relative volume this week: trailing 5 sessions vs. the prior 40, for names trading $500M+ in the weekseries · 2026-09-15 · 8×6Preview: a 8-point series, ending lower. The board leader, day by day: daily relative volume and open-to-close change (last 15 sessions)series · 2026-09-15 · 15×5Preview: a 15-point series, roughly flat. Wild multiples the dollar floor removes: highest relative volume among names trading under $500M this weekseries · 2026-09-15 · 6×5Preview: a 6-point series, ending higher.
Unusual Options Activity: Last Session
Market-wide options volume by session, with monthly expirations labelledseries · 2026-09-15 · 25×5Preview: a 16-point series, ending higher. Calls or puts: the board's call and put contract volume on the same sessiontable · 2026-09-15 · 10×5 What follows a heavy options session: next-session absolute move vs. the same names on an ordinary daytable · 2026-09-15 · 5×6 What the session's contracts were made of: options volume by days to expiryranking · 2026-09-15 · 6×4Preview: 6 ranked values, largest first. Unusual options activity: last completed session vs. each underlying's own 20-session averagetable · 2026-09-15 · 10×8
Short Squeeze Candidates This Week
Squeeze-shaped mechanics: crowded shorts among liquid names, with a rising priceranking · 2026-09-15 · 12×4Preview: 12 ranked values, largest first. The screened names ranked by short interest against shares outstanding (not float)table · 2026-09-15 · 10×5 Every past screened name, by what it did over the next 30 daysranking · 2026-09-15 · 6×3Preview: 6 ranked values, smallest first. From the whole settlement file down to the screened list, one rule at a timeranking · 2026-09-15 · 4×2Preview: 4 ranked values, largest first. Every input behind this screen, and how many days old it isseries · 2026-09-15 · 3×3Preview: a 3-point series, ending lower. Liquid names at 5+ and 10+ days to cover, settlement by settlementseries · 2026-09-15 · 12×4Preview: a 12-point series, ending higher.
Short Selling Bans Explained: US, Germany, EU
What ESMA measured during the 2020 bans (published estimates, % versus the control group)ranking · 2026-09-15 · 4×2Preview: 4 ranked values, largest first. Every outright short selling ban since 2008, dated to the order that set ittable · 2026-09-15 · 9×5
Recent Stock Splits (Forward and Reverse)
Forward vs reverse splits executed in the last 45 daysranking · 2026-09-15 · 2×2Preview: 2 ranked values, largest first. Recent reverse stock splits (shares consolidated), last 30 daysranking · 2026-09-15 · 15×4Preview: 15 ranked values, largest first. Recent forward stock splits (shares multiplied), last 60 days, ETFs excludedranking · 2026-09-15 · 15×4Preview: 15 ranked values, largest first.
Options Expiry Days in India: NSE and BSE
Weekdays with a traded expiration: SPY, QQQ and IWM, trailing five weeksranking · 2026-09-15 · 3×4Preview: 3 ranked values, largest first.
Most Shorted Stocks Right Now, Measured
The receipts: universe size, filter bite, median crowding, and list churn at the latest printscalar · 2026-09-15 · 1×522,567 Largest short positions by shares: latest settlement, liquid namesranking · 2026-09-15 · 10×4Preview: 10 ranked values, largest first. Crowding leaders vs. their own price: about one month of sessionsseries · 2026-09-15 · 4×5Preview: a 4-point series, ending higher. GME through the January 2021 squeeze: the same three columns, settlement by settlementseries · 2026-09-15 · 10×4Preview: a 10-point series, ending lower. Today's top-3 crowding leaders, traced back eight settlementsseries · 2026-09-15 · 8×4Preview: a 8-point series, ending higher. Biggest days-to-cover increases, latest settlement vs. the prior printranking · 2026-09-15 · 8×4Preview: 8 ranked values, largest first. Highest days to cover among liquid names: latest settlement on filetable · 2026-09-15 · 10×5
Stock Market Holidays 2026–2027: NYSE & Nasdaq
Upcoming US stock market holidays and early closesseries · 2026-09-15 · 12×6Preview: a 12-point series, ending higher. Recently-passed weekday closures, recovered from the SPY tapeseries · 2026-09-15 · 4×3Preview: a 4-point series, roughly flat. Regular trading sessions over the trailing yearscalar · 2026-09-15 · 1×3252 The closure calendar ahead, at a glancescalar · 2026-09-15 · 1×610
Is the Stock Market Open Today?
This calendar year's closures: already passed (counted from the tape) plus still ahead (from the calendar)table · 2026-09-15 · 2×5 SPY across recent weekends and holiday weekends: Friday's close vs. the reopening printseries · 2026-09-15 · 11×6Preview: a 11-point series, ending lower. Every upcoming NYSE closure and early close on the calendar feed, with a countdownseries · 2026-09-15 · 12×6Preview: a 12-point series, ending higher. Unscheduled closures on the tape: zero regular-session bars on an ordinary weekdayseries · 2026-09-15 · 5×4Preview: a 5-point series, roughly flat. Market status computed at this page's refresh: weekday check, holiday check, and the ET clockscalar · 2026-09-15 · 1×70 The most recent session on the tape: bar count, same-day SPY options prints, and the last half-day observedscalar · 2026-09-15 · 1×6211 Weekdays in the trailing year when stocks traded but no Treasury yield printedtable · 2026-09-15 · 2×2
How to Read the US Equity Trade Tape
Two companies behind one symbol: TWTR on the daily barsseries · 2026-09-15 · 2×5Preview: a 2-point series, ending higher. The tape column on eight symbols, 2023-03-15ranking · 2026-09-15 · 8×3Preview: 8 ranked values, smallest first. Sessions and symbols on the tape, by yearseries · 2026-09-15 · 24×4Preview: a 16-point series, ending higher. Share of prints with a placeholder participant timestamp, one March session per year (IBM and MSFT)ranking · 2026-09-15 · 24×4Preview: 16 ranked values, smallest first. IBM's NYSE closing auction print: seconds after 4:00 p.m. ET, one March session per yearranking · 2026-09-15 · 17×4Preview: 16 ranked values, smallest first. Placeholder share by session, five large names, July to August 2015series · 2026-09-15 · 15×3Preview: a 15-point series, ending lower. The first session with a populated participant timestampscalar · 2026-09-15 · 1×26.41M Correction indicator counts on one session, fifteen large names, 2023-03-15ranking · 2026-09-15 · 5×3Preview: 5 ranked values, smallest first.
Highest Implied Volatility Stocks Right Now
SPY, the same measurement: the market's calm benchmarkscalar · 2026-09-15 · 1×313.2 ATM implied volatility across every actively traded underlying, latest sessionscalar · 2026-09-15 · 1×5969 Highest ATM implied volatility: liquid single names and funds, latest sessiontable · 2026-09-15 · 12×5
Dividend Increases & Cuts This Week
Increases against cuts, by week of declaration (complete weeks only)series · 2026-09-15 · 26×4Preview: a 16-point series, ending lower. Payers across their own share split: the raw change against the split-adjusted changeseries · 2026-09-15 · 9×7Preview: a 9-point series, ending lower. Increases, cuts and the typical raise this calendar year, by company size (bands use today's market value)table · 2026-09-15 · 4×6 Dividend increases declared in the last 7 days, largest companies first (capped at 12 rows)series · 2026-09-15 · 6×8Preview: a 6-point series, ending lower. Dividend cuts declared in the last 90 days, the deepest 14 first (one week is too thin for a table)series · 2026-09-15 · 14×6Preview: a 14-point series, ending higher.
Can You Day Trade an Index Fund? ETFs vs Funds
VOO: last traded price in each 30-minute bucket of the most recent complete session (ET, extended hours included)series · 2026-09-15 · 25×2Preview: a 16-point series, ending higher. Typical quoted spread on the three largest S&P 500 ETFs, trailing five daysranking · 2026-09-15 · 3×3Preview: 3 ranked values, smallest first.
Biggest Stock Gainers and Losers This Week
Biggest stock losers this week (names trading $1B+, leveraged/inverse ETFs excluded)ranking · 2026-09-15 · 10×4Preview: 10 ranked values, smallest first. The four major index ETFs this week, for contextranking · 2026-09-15 · 4×2Preview: 4 ranked values, largest first.
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How the session's volume piled up against the prior 10 sessions, checkpoint by checkpoint

How the session's volume piled up against the prior 10 sessions, checkpoint by checkpoint

as of series 14×4read in context →
How the session's volume piled up against the prior 10 sessions, checkpoint by checkpoint — 14 rows by 4 columns, computed from US exchange, SIP and OPRA data.
et_timesession_cumulative_millionstypical_cumulative_millionstypical_share_of_session_pct
09:458.32.78.5
10:0011.14.514.1
10:3014.57.523.8
11:001910.131.9
11:3023.412.439.2
12:0029.214.545.7
12:3032.816.351.4
13:0038.217.755.8
13:3041.219.561.5
14:0045.32166.4
14:304822.972.4
15:0050.325.179.3
15:3053.426.985.1
16:0059.331.7100
the exact SQL behind every number
WITH
    toDate('2026-09-10') AS session_day,
    [585, 600, 630, 660, 690, 720, 750, 780, 810, 840, 870, 900, 930, 960] AS checkpoints
SELECT
    formatDateTime(toDateTime(session_day, 'UTC') + checkpoints[i] * 60, '%H:%i', 'UTC') AS et_time,
    round(session_cums[i] / 1e6, 1)                                                        AS session_cumulative_millions,
    round(typical_cums[i] / 1e6, 1)                                                        AS typical_cumulative_millions,
    round(100 * typical_cums[i] / typical_cums[14], 1)                                     AS typical_share_of_session_pct
FROM
(
    SELECT
        arrayJoin(arrayEnumerate(checkpoints)) AS i,
        session_cums,
        arrayMap(k -> arrayAvg(x -> arrayElement(tupleElement(x, 2), k), arraySlice(prior, 1, 10)),
                 arrayEnumerate(checkpoints)) AS typical_cums
    FROM
    (
        SELECT
            anyIf(cums, d = session_day)                                                        AS session_cums,
            arrayReverseSort(x -> tupleElement(x, 1), groupArrayIf((d, cums), d < session_day)) AS prior
        FROM
        (
            SELECT
                d,
                arrayMap(cp -> arraySum(x -> if(tupleElement(x, 1) <= cp, tupleElement(x, 2), 0), mv),
                         checkpoints) AS cums
            FROM
            (
                SELECT d, groupArray((minute_of_day, vol)) AS mv
                FROM
                (
                    SELECT
                        toDate(toTimeZone(window_start, 'America/New_York'))      AS d,
                        toHour(toTimeZone(window_start, 'America/New_York')) * 60
                          + toMinute(toTimeZone(window_start, 'America/New_York')) AS minute_of_day,
                        max(toFloat64(volume))                                     AS vol
                    FROM global_markets.delayed_stocks_minute_aggs
                    WHERE ticker = 'AAPL'
                      AND window_start >= toDateTime(session_day - 20, 'America/New_York')
                      AND window_start <  toDateTime(session_day + 1, 'America/New_York')
                    GROUP BY d, minute_of_day
                    HAVING minute_of_day >= 570 AND minute_of_day <= 960
                )
                GROUP BY d
            )
        )
        HAVING length(session_cums) = 14 AND length(prior) >= 10
    )
)
ORDER BY i
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