BankNifty Index and Component Stocks Historical Price Dataset
A structured historical financial dataset containing BankNifty index prices along with its constituent bank stock prices, designed for quantitative analysis, portfolio modeling, and algorithmic trading research.
Dataset Metrics
Data Format
Dataset Schema (10 features)
| Name | Type | Nullable | Description |
|---|---|---|---|
| Date | string | No | |
| BN_Open | float | No | |
| BN_High | float | No | |
| BN_Low | float | No | |
| BN_Close | float | No | |
| HDFCBANK_Close | float | Yes | |
| ICICIBANK_Close | float | Yes | |
| SBIN_Close | float | Yes | |
| AXISBANK_Close | float | Yes | |
| Volume | integer | Yes |
License & Compliance
About This Dataset
This dataset includes daily historical trading data for: BankNifty Index Major component banks (e.g., HDFC Bank, ICICI Bank, SBI, Axis Bank, etc.) OHLC prices (Open, High, Low, Close) Trading Volume The dataset has been cleaned and validated through a comprehensive EDA workflow including: Duplicate removal Chronological ordering Missing value handling OHLC logical validation (Low ≤ Open/Close ≤ High) Volume anomaly detection Negative price elimination Outlier validation using statistical thresholds Schema standardization The dataset is optimized for: Quantitative trading strategies Portfolio risk modeling Index-component correlation analysis Volatility forecasting ML-based financial modeling Backtesting frameworks
Data Quality
Structured time-series format, No duplicate timestamps, Validated OHLC consistency, Clean numeric fields, Chronologically ordered, ML & quantitative finance ready
Use Cases
BankNifty price prediction Multi-asset portfolio simulation Volatility modeling Correlation matrix analysis Hedge strategy development Technical indicator modeling Backtesting trading systems
Limitations
Historical dataset (not live feed) Limited to BankNifty and its listed components Does not include macroeconomic indicators
Methodology
Data Preparation & Validation Process Structural Validation Schema consistency checks Column normalization Data type standardization Time-Series Integrity Chronological sorting Duplicate date removal Trading gap validation Financial Sanity Checks OHLC logical validation Negative/zero price elimination Volume anomaly detection Statistical Validation Outlier detection (z-score method) Distribution review Zero-variance detection ML Optimization Return calculation validation Numeric formatting consistency Export in CSV format for Python/R integration
Geographic Coverage
Source Information
Governance & Review
Usage & Restrictions
License: CC BY 4.0 — This dataset is licensed for use by the purchasing entity. Refer to the specific license terms for permitted use.
Access Control: Download links are time-limited and single-use. All access is logged for audit purposes.