Algorithmic Trading Market Snapshots

This dataset provides granular, high-frequency market snapshots across multiple instruments and exchanges, capturing bid/ask quotes, trade data, and engineered features such as spread, mid-price, and order book imbalance. It is ideal for quantitative researchers, algorithmic traders, and data scientists seeking to train models, backtest trading strategies, or detect market anomalies in real or simulated environments.

  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Backtesting and evaluating algorithmic trading strategies

Sample rows

preview · 8 of 200 rows · all 17 columns
snapshot_idstringbid_pricefloatanomaly_flagbooleansymbolstringtimestampdatetimeexchangestringbid_sizefloatask_pricefloatask_sizefloatlast_trade_pricefloatlast_trade_sizefloatvolume_1mfloatvolume_5mfloatopen_interestfloatmid_pricefloatspreadfloatimbalancefloat
SNAP-0001171.3falseAAPL2024-04-09T09:30:00ZNASDAQ5200171.344800171.32200870039000blank171.320.040.04
SNAP-0002171.36falseAAPL2024-04-09T09:31:12ZNASDAQ6100171.396100171.391001200041000blank171.3750.030
SNAP-0003172.01falseAAPL2024-04-09T09:32:25ZNASDAQ8900172.058200172.033501340044300blank172.030.040.04
SNAP-0004173.2falseAAPL2024-04-09T15:59:59ZNASDAQ15000173.2413000173.2112001560064000blank173.220.040.07
SNAP-000566500.15falseBTCUSD2024-04-09T10:02:10ZBINANCE0.8466501.440.9166501.20.133.1512.4985066500.7951.29-0.04
SNAP-000666555.28falseBTCUSD2024-04-09T10:17:05ZBINANCE1.7766557.612.0266556.330.032.419.88987066556.4452.33-0.07
SNAP-000766620.11falseBTCUSD2024-04-09T15:45:19ZBINANCE0.4566621.80.2966621.320.283.9114.21988366620.9551.690.22
SNAP-0008252.14falseTSLA2024-04-09T11:20:30ZNASDAQ6500252.166200252.15112740028500blank252.150.020.02

What the 200 rows show

from the 200-row sample
  • 6%anomaly_flag = true
  • 309.9median bid_price
  • 12exchanges
  • 4,900median bid_size
  • 314.6median ask_price
  • 5,000median ask_size
bid_price200 rows, in bands of 10k
08016015413256020040k70kbid_price →

Median 309.9, from 0.0 to 66,620.

symbol200 rows · top 10 of 14 values
  1. BTCUSD37
  2. AAPL27
  3. ETHUSD20
  4. TSLA19
  5. MSFT18
  6. NQH2415
  7. SPY13
  8. CLN2412
  9. EURUSD10
  10. AZN.L8
17 columns by typefrom the column list below
  • string 3
  • float 12
  • datetime 1
  • boolean 1

Columns

17 columns in four groups
blueprint · 17 columns
columntypedescriptionexample
Text 3 columns
snapshot_idstringUnique identifier for each market snapshot recorduniqueSNAP-0001
symbolstringTicker symbol of the traded instrument (e.g., AAPL, BTCUSD)AAPL
exchangestringName or code of the exchange where the instrument is traded12 exchangesNASDAQ
Numbers 12 columns
bid_pricefloatHighest price a buyer is willing to pay for the instrument at the snapshot time0 or more171.3
bid_sizefloatTotal quantity available at the best bid price0 or more5200
ask_pricefloatLowest price a seller is willing to accept for the instrument at the snapshot time0 or more171.34
ask_sizefloatTotal quantity available at the best ask price0 or more4800
last_trade_pricefloatPrice at which the most recent trade was executed prior to the snapshot0 or more171.32
last_trade_sizefloatQuantity of the most recent trade prior to the snapshot0 or more200
volume_1mfloatTotal traded volume for the instrument in the previous 1 minute0 or more · optional8700
volume_5mfloatTotal traded volume for the instrument in the previous 5 minutes0 or more · optional39000
open_interestfloatTotal number of outstanding derivative contracts (if applicable) at the snapshot time0 or more · optional9850
mid_pricefloatMidpoint between the best bid and ask prices at the snapshot time0 or more · optional171.32
spreadfloatDifference between ask_price and bid_price at the snapshot time0 or more · optional0.04
imbalancefloatOrder book imbalance calculated as (bid_size - ask_size) / (bid_size + ask_size)-1 to 1 · optional0.04
Dates and times 1 column
timestampdatetimePrecise date and time when the snapshot was taken (in UTC)2024-04-09T09:30:00Z
True or false 1 column
anomaly_flagbooleanIndicates if the snapshot is flagged as anomalous for model training or detectionoptionalfalse

Use it for

  • anomaly flag6%12 of 200 rows

    A finance dashboard

    The anomaly_flag rate, bid_price and a breakdown of symbol. Excel, Power BI or Tableau.

  • Why do 12 of 200 rows have anomaly_flag = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable snapshots with timestamp, symbol and exchange to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 17 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows17 columns
Yours1,000 rows17 columns

blueprint · algorithmic-trading-market-snapshots

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 17 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each snapshot covers multiple stock symbols
  • Features include price, volume, bid/ask spread
  • Market anomalies randomly inserted
  • Timestamps at sub-second intervals
  • Label if price spike/drop detected
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
algorithmic-trading-market-snapshots

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