How to check the whole market in one question with ChatGPT or Claude

A starting list for research. It does not recommend any trade.

At the Nov 5 close, defensive sectors led the month: consumer staples, health care and real estate each rose more than 9%. Technology fell 19.4% and QQQ 14.6%, and every fund sat below its 52-week high. In the 200-day variation, SPY closed 0.4% above its average while QQQ, IWM and XLK closed below theirs.

US stocks, ETFs and futures. The free plan runs 20 queries a day on daily bars; Pro adds intraday.

Paste these into the same chat, after the first answer, so your AI knows which results you mean.

• Which technology stocks fell the most in the past week?

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• Show the same table for the past three months.

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• Chart XLK and XLP over the past six months.

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A market overview puts the main index funds and the sector funds side by side, so one table shows whether the market rose or fell, which parts led and which lagged. SPY follows the S&P 500, QQQ the Nasdaq-100, IWM the Russell 2000 small companies and DIA the Dow. Eleven sector ETFs split the S&P 500 into technology, financials, health care, energy, industrials, consumer discretionary, consumer staples, utilities, materials, real estate and communication services.

The rule Monk.trade uses: the 15 named ETFs, checked on the last completed session. The 1-week change compares that close with the close 5 sessions earlier, and the 1-month change with the close 21 sessions earlier. Distance from the 52-week high compares the close with the highest price reached in the last 252 sessions.

• Futures snapshot

  “Using Monk.trade, compare S&P 500, Nasdaq-100, crude oil, gold and 10-year Treasury futures (ES, NQ, CL, GC, ZN) at the last completed day. Show the 1-week and 1-month change and the distance from the 52-week high, sorted by the 1-month change.”

  Open in ChatGPT ↗Open in Claude ↗

  MonkQL

  from futures "ES", "NQ", "CL", "GC", "ZN"
  let chg_1w = 100 * (close[1] / close[7] - 1)
  let chg_1m = 100 * (close[1] / close[26] - 1)
  show name, close[1] as last_close, chg_1w unit percent, chg_1m unit percent, 100 * (close[1] / highest(high, 312)[1] - 1) as from_high unit percent
  sort chg_1m desc
  

• Above or below the 200-day average

  “Using Monk.trade, for SPY, QQQ, IWM, DIA and the 11 sector ETFs, show the last completed close, the 200-day average, the percent gap between them and whether each closed above it.”

  Open in ChatGPT ↗Open in Claude ↗

  MonkQL

  from "SPY", "QQQ", "IWM", "DIA", "XLK", "XLF", "XLV", "XLE", "XLI", "XLY", "XLP", "XLU", "XLB", "XLRE", "XLC"
  let s200 = sma(close, 200)
  show close[1] as last_close, s200[1] as avg_200d, 100 * (close[1] / s200[1] - 1) as vs_200d unit percent, close[1] > s200[1] as above
  sort vs_200d desc
  

• Chart SPY and QQQ with the 200-day average

  “Using Monk.trade, chart SPY and QQQ on daily bars for the past 300 sessions with the 200-day average.”

  Open in ChatGPT ↗Open in Claude ↗

  MonkQL

  from "SPY", "QQQ"
  plot sma(close, 200)
  chart 300
  

• Nothing on this page is a signal to buy or sell. Prices can keep moving against you, and you can lose money.
• The query reads the bar before the newest, which is the last completed session while the market is open. Before the open or after the close the newest bar is already complete, so the query reads the session before it. This example ran during the Nov 6 session and read Nov 5. Ask your AI to use the newest session instead.
• Changes are price only and leave out dividends. Funds that pay more, such as utilities, consumer staples and real estate, returned more than the table shows.
• Mutual funds and target-date funds are not covered. An ETF that follows the same index, such as SPY for an S&P 500 fund, can stand in for one.
• Each row is worked out on its own, so one query cannot measure how closely two funds move together. Ask for a chart to compare them by eye.
• The 52-week high is the highest price reached during a day in the last 252 sessions, which can sit above the highest close.
• Futures daily bars cover one UTC calendar day, and each week has a short Sunday bar, so the futures variation counts six bars as a week, 25 as a month and 312 as a year. Continuous contracts switch to the next expiration as one nears, and the price gap at the switch can distort a change.