Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample

Bitnomial Crypto Derivatives Liquidity and Funding Dataset

Question this dataset helps answer: Which Bitnomial crypto derivatives contracts show meaningful volume, open interest, and perpetual funding regimes worth monitoring for market-structure research?

This dataset helps crypto derivatives researchers, dashboard builders, and systematic-market analysts screen Bitnomial product-day liquidity using daily volume, open interest, notional activity, rolling activity fields, and same-day perpetual funding-rate summaries.

Use the public sample to check:

• Which Bitnomial products have nonzero volume and open interest by date.
• How perpetual funding-rate summaries line up with daily notional volume and open interest.
• Whether rolling 7-day activity fields are suitable for a liquidity monitor or research dashboard.

Preview vs full dataset:

• Preview: 521 rows and 39 columns
• Full: 10,428 rows and 39 columns

Full dataset access: https://thearticulated.gumroad.com/l/lpbgqx

from datasets import load_dataset

dataset = load_dataset("Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample")
df = dataset["data"].to_pandas()
print(df.head())

The full dataset includes 10,428 rows across Bitnomial crypto derivative product-day observations, making it large enough for dashboard analysis, historical filtering, liquidity-screen research, and exploratory modeling workflows.

Responsible use note

This dataset is for research, analysis, dashboard building, educational use, and exploratory modeling. It does not provide trading advice, signals, guarantees, or predictions of future outcomes.

Modeling notes

Each row represents one Bitnomial product-day volume and open-interest observation from the public VOI chart endpoint. The observation interval is daily. Rows are not trades; they are daily product-level liquidity snapshots. For perpetual products, finalized 8-hour funding intervals ending on the same UTC date are aggregated into same-day summary fields. funding_rate_mean, funding_rate_min, funding_rate_max, mark_price_mean, price_index_mean, and mark_to_index_basis_bps_mean are calculated only from finalized funding intervals available from the public funding endpoint. Daily volume and open interest are sampled from the chart endpoint as product-day values. Missing funding fields generally mean the row is not a perpetual product or the funding endpoint did not return intervals for that symbol/date. Base symbols and product types are normalized from the public API fields without guessing contract specifications.

Fields known at observation time include the product identity, date, same-day volume/open-interest values, same-day finalized funding summaries for intervals already ended, and rolling fields based on prior product observations in this exported history. Future-outcome fields are not included. Time-based splits should sort by observation_timestamp_utc; observations from the same product should not be randomly divided without product-level or time-group controls because adjacent rows share market context. Limitations include public API coverage, Bitnomial product-launch history, inactive-product rows, repeated source dates where the API returns duplicate chart records, and the absence of private order-book or account-level data.

Commercial use cases

• Build a Bitnomial crypto derivatives liquidity monitor.
• Screen products by notional volume, open interest, and rolling activity.
• Compare perpetual funding-rate regimes against product-day activity.
• Prototype feature engineering for derivatives market-structure research.
• Replace manual historical collection from separate public chart and funding endpoints.

Source notes

Data is collected from public Bitnomial exchange API endpoints and documentation pages. No login, exchange account, broker credential, or private account data is used.

This is a free preview. Load it instantly, inspect the schema, and validate quality before purchasing the full dataset.

---

What This Preview Proves

• Sample rows: 521 (full dataset: 10,428 rows)
• Columns: 39 fields, fully described below
• Format: parquet (loads in pandas, HF datasets, or any parquet reader)
• No authentication required to load this sample
• Schema and quality are identical to the paid full dataset

---

Upgrade to Full Dataset

The full production dataset contains 10,428 rows across 39 columns.

Full dataset access: https://thearticulated.gumroad.com/l/lpbgqx

After purchase, provide your Hugging Face username and request access on the full dataset page.

---

Quick Start

from datasets import load_dataset

dataset = load_dataset("Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample")
df = dataset["data"].to_pandas()
print(f"Rows: {len(df):,}, Columns: {len(df.columns)}")
print(df.head())

Or with pandas directly:

import pandas as pd
df = pd.read_parquet("hf://datasets/Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample/data/data.parquet")
print(df.head())

---

Use Cases

• Screen Bitnomial derivatives by product-day notional volume, open interest, and rolling activity.
• Compare same-day perpetual funding summaries against daily liquidity observations.
• Build dashboards, liquidity monitors, and exploratory market-structure notebooks without collecting the public endpoints by hand.

---

Column Descriptions

• record_id: Stable row identifier built from source, product ID, base symbol, product type, and observation date.
• source_platform: Source exchange or venue name.
• product_id: Bitnomial product identifier returned by the public chart endpoint.
• base_symbol: Bitnomial base symbol for the derivative product.
• product_type: Derivative product type, such as Future, Option, or Perpetual.
• observation_date: UTC date for the product-day volume and open-interest observation.
• observation_timestamp_utc: UTC timestamp at the start of observation_date.
• volume_contracts: Daily trading volume in contracts.
• notional_volume_usd: Daily notional trading volume in USD as returned by Bitnomial.
• open_interest_contracts: End-of-day open interest in contracts.
• notional_open_interest_usd: End-of-day notional open interest in USD as returned by Bitnomial.
• has_volume: Boolean flag indicating whether daily volume is above zero.
• has_open_interest: Boolean flag indicating whether open interest is above zero.
• liquidity_activity_score: Deterministic 0-100 score combining normalized notional volume and notional open interest within this build.
• volume_to_open_interest_ratio: Daily contracts traded divided by open interest contracts when open interest is positive.
• notional_volume_to_oi_ratio: Daily notional volume divided by notional open interest when notional open interest is positive.
• rolling_7d_notional_volume_usd: Seven-observation rolling sum of notional volume by product.
• rolling_7d_avg_open_interest_contracts: Seven-observation rolling average of open interest by product.
• rolling_7d_active_days: Seven-observation rolling count of days with positive volume by product.
• open_interest_1d_change_contracts: One-observation change in open interest by product.
• open_interest_1d_change_pct: Percent change in open interest by product when the prior value is positive.
• funding_interval_count: Number of finalized 8-hour funding intervals joined to this product-day for perpetual products.
• funding_rate_mean: Mean finalized funding rate for intervals ending on observation_date.
• funding_rate_min: Minimum finalized funding rate for intervals ending on observation_date.
• funding_rate_max: Maximum finalized funding rate for intervals ending on observation_date.
• funding_rate_abs_mean: Mean absolute finalized funding rate for intervals ending on observation_date.
• funding_rate_mean_annualized: Mean funding rate multiplied by 3 intervals per day and 365 days.
• mark_price_mean: Mean mark price across finalized funding intervals ending on observation_date.
• price_index_mean: Mean price index across finalized funding intervals ending on observation_date.
• mark_to_index_basis_bps_mean: Mean mark-price premium or discount versus the price index in basis points.
• interest_rate_mean: Mean interest-rate component across finalized funding intervals ending on observation_date.
• estimated_current_funding_rate: Estimated current in-progress funding rate for the base symbol at collection time when available.
• estimated_interval_start: Start timestamp for the current estimated funding interval when available.
• estimated_interval_end: End timestamp for the current estimated funding interval when available.
• is_perpetual_product: Boolean flag indicating product_type equals Perpetual.
• source_voi_url: Public Bitnomial VOI chart endpoint used for the row.
• source_funding_url: Public Bitnomial funding-rate endpoint used for perpetual funding enrichment.
• source_docs_url: Bitnomial funding-rate documentation URL.
• last_collected_at: UTC timestamp when this row was generated.

---

Dataset Structure

• Rows: 521
• Columns: 39
• Split: data
• File: data/data.parquet

---

Full Dataset Access

	Sample (this repo)	Full Dataset
Rows	521	10,428
Columns	39	39
Auth required	No	Yes (after purchase)
Price	Free	See pricing

Final CTA

Get the full dataset: https://thearticulated.gumroad.com/l/lpbgqx

---

Karmane. (2025). Bitnomial Crypto Derivatives Liquidity and Funding Dataset (Free Sample). Hugging Face. https://huggingface.co/datasets/Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample