KGP Synthetic Collateral Liquidity for Seasonal Back-to-School Scenario

Synthetic collateral mix data shows how value, liquidity, and seasonality differ across core pawn inventory categories and subcategories. This build contains 48 rows under the seasonal back to school scenario. The dataset was created by gene fur and published on figshare on 2026-04-12.

Use Cases

• Modeling seasonal liquidity shifts based on the described back-to-school demand scenario.
• Analyzing collateral value distribution based on the described inventory categories and value bands.
• Comparing resale liquidity scores across categories like jewelry, electronics, and tools as mentioned in the description.
• Simulating pawn shop inventory mixes based on the normalized collateral shares totaling 100%.

Strengths

• Data is explicitly synthetic, containing no real customer-level data, which may address privacy concerns.
• The 48-row scenario is designed to show meaningful spread in values and liquidity instead of flat averages.
• Collateral shares are normalized to 100.00% of total inventory, ensuring internal consistency for the mix.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 59.1 KB, which limits the scope of analysis.
• Row count for the full dataset is unknown, which may limit suitability assessment.

Provenance

Source

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

Collection Method

Synthetically generated for research and modeling.

Time Range

Scenario date: 2026-04-12.

Freshness

Last updated 2026-04 12 00:14:56.

Geography

Based on the operations of King Gold & Pawn in New York locations including Freeport, Brooklyn, Bronx, and Westchester.