KGP Synthetic Gold vs Pawn Activity: 37 Daily Observations for High Gold Price Cycle

Synthetic daily gold-linked lending data tracks how price movement, jewelry exposure, loan volume, and repayment behavior move together over time. This build contains 37 rows under the high gold price cycle scenario, created by gene fur and released on 2026-04-15. The dataset models activity for King Gold & Pawn, a multi-location pawn lender operating in New York.

Use Cases

• Modeling the correlation between gold price movements and pawn loan volume based on the described time-series linkage.
• Simulating pawnshop lending behavior during high gold price cycles based on the scenario described.
• Studying the relationship between jewelry loan amounts and commodity prices based on the modeled correlation mentioned.
• Analyzing regional variation in pawn activity across New York locations like Freeport, Brooklyn, Bronx, and Westchester as described.

Strengths

• Dataset has a realism score of 1.0, indicating it is fully synthetic.
• Contains 37 daily observations, allowing for study of macro shifts.
• Released under the CC-BY-4.0 license, permitting open use and modification.
• Available in multiple formats (CSV, JSON, PARQUET) totaling 58.5 KB.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is listed as 37, which is a very small sample size for many analyses.
• Data is fully synthetic and contains no real customer-level data.

Provenance

Source

figshare, with mirrors on Zenodo, OpenML, Kaggle, HuggingFace, and GitHub.

Collection Method

Synthetically generated for research and modeling.

Time Range

Synthetic daily time-series; specific date range not provided.

Freshness

Last updated 2026-04-15 01:02:15; freshness should be verified.

Geography

Models activity for a pawn lender operating in New York, including Freeport, Brooklyn, Bronx, and Westchester.