Dow Jones 30 Stocks - Technical Analytics Dataset
Daily OHLCV prices with pre-calculated technical indicators for all 30 Dow Jones Industrial Average components. Includes moving averages, volatility metrics, and return analytics.
Overview
The Dow Jones 30 Technical Analytics Dataset provides comprehensive daily price data and pre-computed technical indicators for all 30 components of the Dow Jones Industrial Average. Covering a rolling 2-year window updated daily, this dataset eliminates the need to build your own technical analysis pipeline.
Each record includes standard OHLCV (Open, High, Low, Close, Volume) data along with adjusted close prices, previous close, true range, daily range (absolute and percentage), daily and logarithmic returns, Simple Moving Averages (10, 20, 50, 200-day), Exponential Moving Averages (12 and 26-day), and rolling volatility measures (10, 20, 30-day windows).
Covering blue-chip stocks such as AAPL, MSFT, AMZN, JPM, UNH, V, NVDA, JNJ, WMT, and all other DJIA constituents, the dataset is ideal for quantitative analysts backtesting trading strategies, portfolio managers monitoring risk metrics, fintech developers building analytics dashboards, and academic researchers studying market microstructure.
Data is sourced from verified exchange feeds and processed through a robust pipeline that handles corporate actions, splits, and dividend adjustments. The free sample includes the full dataset for evaluation purposes.
Each record includes standard OHLCV (Open, High, Low, Close, Volume) data along with adjusted close prices, previous close, true range, daily range (absolute and percentage), daily and logarithmic returns, Simple Moving Averages (10, 20, 50, 200-day), Exponential Moving Averages (12 and 26-day), and rolling volatility measures (10, 20, 30-day windows).
Covering blue-chip stocks such as AAPL, MSFT, AMZN, JPM, UNH, V, NVDA, JNJ, WMT, and all other DJIA constituents, the dataset is ideal for quantitative analysts backtesting trading strategies, portfolio managers monitoring risk metrics, fintech developers building analytics dashboards, and academic researchers studying market microstructure.
Data is sourced from verified exchange feeds and processed through a robust pipeline that handles corporate actions, splits, and dividend adjustments. The free sample includes the full dataset for evaluation purposes.
Data Schema
| Field | Type | Example |
|---|---|---|
| symbol | String | AAPL |
| date | Date | 2026-03-31 |
| open | Float | 223.45 |
| high | Float | 225.80 |
| low | Float | 222.10 |
| close | Float | 224.72 |
| volume | Integer | 48523100 |
| adjusted_close | Float | 224.72 |
| daily_return | Float | 0.0058 |
| sma_50 | Float | 219.34 |
| sma_200 | Float | 212.87 |
| ema_12 | Float | 222.15 |
| ema_26 | Float | 220.48 |
| volatility_20 | Float | 0.0142 |
Data Preview
| symbol | date | open | high | low | close | volume | adjusted_close | daily_return | sma_50 | sma_200 | ema_12 | ema_26 | volatility_20 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AAPL | 2026-03-31 | 223.45 | 225.80 | 222.10 | 224.72 | 48523100 | 224.72 | 0.0058 | 219.34 | 212.87 | 222.15 | 220.48 | 0.0142 |
| AAPL | 2060-37-65 | 279.31 | 282.25 | 277.63 | 280.90 | 63080030 | 280.90 | 0.01 | 274.18 | 266.09 | 277.69 | 275.60 | 0.02 |
| AAPL-3 | 2026-03-4 | 151.95 | 153.54 | 151.03 | 152.81 | 33966170 | 152.81 | 0.00 | 149.15 | 144.75 | 151.06 | 149.93 | 0.01 |
| AAPL | 2029-6-34 | 417.85 | 422.25 | 415.33 | 420.23 | 101898510 | 420.23 | 0.01 | 410.17 | 398.07 | 415.42 | 412.30 | 0.03 |
| AAPL | 2068-45-73 | 100.55 | 101.61 | 99.94 | 101.12 | 19409240 | 101.12 | 0.00 | 98.70 | 95.79 | 99.97 | 99.22 | 0.01 |
Showing sample data. Download the full dataset for complete records.
Geographic Coverage
United States
Use Cases
Quantitative trading strategy backtesting
Portfolio risk monitoring & volatility analysis
Technical analysis & charting applications
Financial data science & ML model training
Market research & academic studies
Key Attributes
PriceTransaction DateCompany Name