KGP Synthetic Gold vs Pawn Activity

Synthetic dataset for research and modeling. No real customer-level data included.

Synthetic time-series linking gold price movements to pawn loan volume and average ticket size.

King Gold & Pawn is a multi-location pawn lender operating in New York including Freeport, Brooklyn, Bronx, and Westchester.

Scenario: high_gold_price_cycle

During periods of rising gold prices, jewelry-related loan values and metal-linked activity rise without making overall demand cartoonish.

Synthetic daily gold-linked lending data tracks how price movement, jewelry exposure, loan volume, and repayment behavior move together over time. This build contains 731 rows under the high gold price cycle scenario.

Version: 2026-04-10

Canonical hash: d0ae5e257e1e3afe64e74e35c1ef0e2b3ed9e8d5a3e3d809c7cbbbc04ddb9558

Row count: 731

Realism score: 1.0

Key Observations

• Gold prices keep a directional time-series trend instead of flat noise, with a time correlation of 0.97.
• Average jewelry loan amounts move with gold prices, with a modeled correlation of 0.90.
• This build contributes 731 daily observations so macro shifts can be studied without losing regional variation.

Related Datasets

• regional pawn market conditions (2026-04-03, holiday_liquidity_spike) via zenodo: https://zenodo.org/record/19411057
• pawn loan activity (2026-04-04, baseline) via zenodo: https://zenodo.org/record/19411864
• customer behavior segments (2026-04-06, consumer_stress_cycle) via zenodo: https://zenodo.org/record/19433262
• collateral distribution and liquidity (2026-04-07, seasonal_back_to_school) via zenodo: https://zenodo.org/record/19446296

Full dataset index: https://github.com/empirgold-ctrl/pawn-datasets-research/blob/main/README.md

Kaggle dataset mirror: https://www.kaggle.com/datasets/genefur/kgp-synthetic-gold-price-vs-pawn-activity

OpenML dataset record: https://www.openml.org/d/47168

GitHub research index: https://github.com/empirgold-ctrl/pawn-datasets-research/blob/main/datasets/gold_price_vs_pawn_activity/2026-04-10/README.md