Stock Price Volatility Features
This dataset provides granular, daily-level historical stock price data, calculated volatility features over multiple time windows, and annotated significant events impacting stocks. It is ideal for financial modeling, risk analytics, and event-driven market research, enabling robust analysis of price dynamics and volatility patterns.
Sample rows
preview · 8 of 200 rows · all 13 columns| stock_idstring | event_impactstring | volatility_30dfloat | event_typestring | datedate | open_pricefloat | close_pricefloat | high_pricefloat | low_pricefloat | volumeinteger | volatility_1dfloat | volatility_7dfloat | event_descriptionstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AAPL | blank | blank | none | 2023-08-04 | 192.45 | 191.88 | 193.22 | 190.9 | 71250000 | 1.18 | 1.25 | blank |
| TSLA | positive | 4.89 | earnings | 2024-03-28 | 188.62 | 196.31 | 198.32 | 187.23 | 113400000 | 3.72 | blank | Q1 earnings beat expectations, strong EV demand. |
| GOOGL | neutral | 2.17 | dividend | 2024-01-18 | 144.67 | 143.95 | 145.31 | 142.85 | 23300000 | 0.86 | blank | Quarterly dividend issued to shareholders. |
| NFLX | negative | blank | earnings | 2023-10-20 | 418.9 | 409.32 | 421.23 | 407.81 | 17200000 | 2.61 | 2.93 | Q3 earnings miss, subscriber growth slows. |
| IBM | blank | blank | none | 2023-11-03 | 127.65 | 128.21 | 129.02 | 127.03 | 8800000 | 0.95 | 1.02 | blank |
| BMW.DE | blank | blank | none | 2024-04-12 | 92.1 | 93.21 | 94.02 | 91.91 | 420000 | 0.42 | 0.79 | blank |
| SBUX | neutral | 1.39 | dividend | 2023-09-29 | 97.85 | 98.03 | 98.41 | 97.11 | 15350000 | 0.66 | blank | Announced quarterly dividend payout. |
| AMZN | positive | blank | merger | 2024-02-02 | 173.01 | 180.58 | 182.02 | 172.11 | 87290000 | 4.13 | 5.02 | Announced acquisition of logistics startup. |
| NOK | blank | 0.58 | none | 2023-12-19 | 3.54 | 3.52 | 3.56 | 3.5 | 2230000 | 0.13 | blank | blank |
| HSBC | neutral | blank | other | 2024-03-06 | 42.19 | 42.13 | 42.55 | 41.97 | 1900000 | 0.23 | 0.91 | Regulatory review of international operations. |
| ZM | unknown | 0 | other | 2023-05-15 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Trading suspended due to compliance investigation. |
| UBER | positive | blank | split | 2024-01-04 | 62.4 | 65.21 | 66.34 | 62.03 | 38430000 | 2.91 | 3.82 | Announced 2-for-1 stock split for Q1. |
| SNAP | negative | 6.02 | earnings | 2023-07-27 | 13.17 | 12.39 | 13.56 | 12.17 | 24300000 | 3.03 | blank | Q2 earnings miss, ad revenues dropped. |
| ARCA-ETF | blank | 2.81 | none | 2024-02-28 | 72.5 | 71.77 | 73.22 | 71.34 | 940000 | 1.28 | blank | blank |
| MSFT | blank | blank | none | 2023-12-08 | 374.03 | 376.15 | 377.53 | 373.9 | 33540000 | 1.03 | 1.13 | blank |
| XOM | neutral | 1.32 | dividend | 2024-03-15 | 119.67 | 120.08 | 121.11 | 119.33 | 7400000 | 0.74 | blank | Dividend announcement for Q1 payouts. |
| BAC | blank | blank | none | 2024-04-01 | 37.28 | 37.02 | 37.56 | 36.97 | 12870000 | 0.41 | 1.01 | blank |
| GE | neutral | 1.22 | dividend | 2023-11-17 | 97.16 | 97.02 | 97.67 | 96.89 | 2600000 | 0.56 | blank | Paid Q4 dividend to all shareholders. |
| TSLA | positive | 7.08 | merger | 2023-06-20 | 203.77 | 201.19 | 205.95 | 200.43 | 104200000 | 4.51 | 4.96 | Tesla merger with SolarTech finalized. |
| AAPL | blank | blank | none | 2024-02-27 | 181.34 | 179.81 | 182.31 | 179.62 | 57200000 | 1.31 | 1.47 | blank |
What the 200 rows show
from the 200-row samplePositive (event impact) stands out: mean volatility_
- 1.6median volatility_
30d - 93.7median open_
price - 93.2median close_
price - 95.0median high_
price - 92.5median low_
price - 10,888,500median volume
Median 1.6, from 0.0 to 8.2.
- string 4
- integer 1
- float 7
- date 1
Columns
13 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 4 columns | |||
stock_id | string | Unique identifier for the stock, such as ticker symbol (e.g., AAPL, MSFT) | AAPL |
event_type | string | Type of significant event affecting the stock (e.g., earnings, dividend, merger, split, none)6 values · optional | none |
event_description | string | Brief description of the event, if any, affecting the stock on the given dateoptional | Q1 earnings beat expectat… |
event_impact | string | Estimated impact of the event on volatility or price (e.g., positive, negative, neutral, unknown)positive · negative · neutral · unknown · optional | positive |
| Numbers 8 columns | |||
open_price | float | Opening price of the stock on the given date0 or more | 192.45 |
close_price | float | Closing price of the stock on the given date0 or more | 191.88 |
high_price | float | Highest price of the stock on the given date0 or more | 193.22 |
low_price | float | Lowest price of the stock on the given date0 or more | 190.9 |
volume | integer | Number of shares traded on the given date0 or more | 71250000 |
volatility_1d | float | 1-day historical volatility calculated for the stock on the given date0 or more · optional | 1.18 |
volatility_7d | float | 7-day historical volatility calculated for the stock on the given date0 or more · optional | 1.25 |
volatility_30d | float | 30-day historical volatility calculated for the stock on the given date0 or more · optional | 4.89 |
| Dates and times 1 column | |||
date | date | Trading date for the recorded price and volatility features | 2023-08-04 |
Use it for
A finance dashboard
Volatility_
30d by event_ impact and a breakdown of event_ type. Excel, Power BI or Tableau. Why do the 17 positive rows have a mean volatility_
30d of 5.4? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Stocks200AAPL—TSLA4.89positiveGOOGL2.17neutral
A software demo
Believable stocks with date, open_
price and close_ price to fill a screen in front of a buyer.
This dataset200 rows13 columns
Yours1,000 rows13 columns
blueprint · stock-price-volatility-features
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 13 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
- Daily open/close/high/low prices
- Volatility metrics calculated
- Event-based flags for major news
- Multiple tickers included
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
- stock-price-volatility-features