Macro-Enhanced Global Manufacturing Analytics

**Overview**:

This dataset delivers an enterprise-grade, macro-enriched analytical view of the Top 50 North American–listed global manufacturers. While these companies are listed on U.S. exchanges, their operations, supply chains, and revenue exposures are fully international—making their equity behavior tightly interwoven with global macroeconomic forces. Designed for quantitative researchers, portfolio strategists, and industrial analysts, the dataset enables rigorous modeling of globally active firms through the lens of U.S.-listed market structure. By integrating high-frequency equity pricing with sector-relevant macroeconomic indicators, it transforms raw market data into a structured analytical asset optimized for forecasting, factor modeling, and supply-chain resilience assessment.

This release reflects a professional enrichment pipeline engineered by Maths with Kanchana, a Kaggle Grandmaster recognized for dataset engineering excellence, and distributed commercially by AIDC Data LLC. All data is cleaned, aligned, and merged through a strict point-in-time architecture to eliminate look-ahead bias. Each record provides a fully traceable view of asset pricing, technical indicators, and macroeconomic context—allowing practitioners to understand not only what moved, but why it moved. This dataset serves as a robust foundation for alpha research, scenario stress-testing, and multi-factor industrial analysis at institutional scale.

**Provenance**
The dataset is composed exclusively of factual market data acquired from publicly available repositories:
- Asset Pricing (Source A): Equity OHLCV data aggregated via the Yahoo Finance API, which mirrors Tier-1 exchange feeds (NYSE/Nasdaq) for adjusted closing prices.
- Macro Indicators (Source B): Commodity and rate data sourced from public institutions including the U.S. Energy Information Administration (EIA), the Federal Reserve, and CME public data channels.
All data is free of PII, ethically sourced, and compliant with redistribution requirements. Because the dataset contains only historical factual data, it falls under a Public Data Aggregation framework and is considered Public Domain for redistribution. Engineering and enrichment were performed by Maths with Kanchana (Kaggle Grandmaster). Commercial distribution, compliance review, and validation are managed by AIDC Data LLC..
Acknowledgements
Compiled and enriched by AIDC Data LLC.

**Use Cases**
This dataset enables high-value analytics and ML workflows on Databricks:
• Macro-Factor Sensitivity Modeling: Build multi-factor models using rolling correlations to Oil, Copper, and U.S. Treasury yields.
• Industrial Sector Risk Assessment: Quantify volatility, liquidity, and supply-chain exposure across the Top 50 North American–listed global manufacturers.
• Predictive Price Forecasting: Train machine learning models using macro-aligned technical signals and PIT-compliant time-series data.
• Supply Chain Stress Testing: Evaluate industrial resilience under macroeconomic shocks using integrated factor overlays.
• Quant Research and Alpha Discovery: Explore relationships between macro shifts and asset-level trend, momentum, and volatility signals.

**Column Dictionary
**Below are the 27 fields included in the dataset:
Core Asset Identifiers
• Trade_Date (date): Trading session date; primary alignment index
• Ticker (string): Asset symbol
• Sector (string): Industrial classification
Pricing (OHLCV)
• Open (decimal): Opening price
• High (decimal): Intraday high
• Low (decimal): Intraday low
• Close (decimal): Adjusted closing price
• Volume (integer): Shares traded
Derived Quantitative Metrics
• Daily_Return (decimal): Percentage price change
• Volatility_30d (decimal): 30-day rolling volatility
• SMA_50 (decimal): 50-day moving average
• SMA_200 (decimal): 200-day moving average
Technical Indicators
• RSI_14 (decimal): 14-day RSI
• MACD_12_26_9 (decimal): MACD Line
• MACDh_12_26_9 (decimal): MACD Histogram
• MACDs_12_26_9 (decimal): MACD Signal Line
• ATRr_14 (decimal): Average True Range
• BBU_20_2.0_2.0 (decimal): Bollinger Band Upper
• BBM_20_2.0_2.0 (decimal): Bollinger Band Middle
• BBL_20_2.0_2.0 (decimal): Bollinger Band Lower
• BBB_20_2.0_2.0 (decimal): Bandwidth
• BBP_20_2.0_2.0 (decimal): Percent-B

**Macro-Economic Enrichment

• Oil_Price (decimal): WTI crude price
• Copper_Price (decimal): Copper spot price
• US_10Y_Yield (decimal): Treasury yield
• Corr_Oil_30d (decimal): 30-day correlation vs oil
• Corr_Rates_30d (decimal): 30-day correlation vs 10-year yield
Technical Metadata
• Geographic Coverage: North America
• Update Frequency: Annually
• Collection Granularity: Daily
• Data Source: Public equity and macroeconomic repositories (PIT-aligned, validated)

Keywords: macroeconomics, manufacturing, equities, factor modeling, industrial analytics, time-series, technical indicators, oil, yields, Databricks