wangdx25/oil032_sample

OIL-032 — Synthetic Energy Derivatives Dataset (Sample) (TsFile)

Apache TsFile version of xpertsystems/oil032-sample.

Overview

A free, schema-identical preview of XpertSystems.ai's enterprise energy derivatives dataset for options pricing ML, vol surface modeling, futures curve analytics, hedging strategy optimization, Greeks-based risk modeling, CFTC positioning analysis, crack spread arbitrage, rare event impact modeling, and trader behavior classification. The sample covers 1,100 futures contracts across 6 energy underlyings (WTI, Brent, Henry Hub NG, Heating Oil, RBOB, LNG) over 180 days with 28,548 option chains, complete Black-Scholes pricing + full Greeks, and 106,959 rows across 11 tables.

• Tables: 11 TsFile table(s), 106,959 rows in total.
  • calendar_spreads: 546 rows, 2022-01-03 00:00:00 → 2022-04-03 00:00:00.005000 (UTC)
  • crack_spreads: 92 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00 (UTC)
  • derivatives_labels: 1,098 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.005000 (UTC)
  • futures_contracts: 1,098 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.005000 (UTC)
  • hedging_positions: 1,000 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.003000 (UTC)
  • market_liquidity: 29,646 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.161000 (UTC)
  • open_interest: 29,646 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.161000 (UTC)
  • options_chain: 28,548 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.155000 (UTC)
  • rare_market_events: 11 rows, 2022-01-03 00:00:00 → 2022-03-31 00:00:00 (UTC)
  • trader_behavior: 1,000 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.003000 (UTC)
  • volatility_surfaces: 14,274 rows, 2022-01-03 00:00:00 → 2022-04-04 00:00:00.077000 (UTC)

Schema (TsFile structure)

calendar_spreads.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (12): spread_id (string), underlying (string), front_contract_id (string), back_contract_id (string), front_month (string), back_month (string), front_price (double), back_price (double), spread_value (double), spread_zscore (double), regime (string), arbitrage_flag (int64)

crack_spreads.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (9): crack_spread_id (string), crude_contract (string), gasoline_contract (string), distillate_contract (string), wti_price_per_bbl (double), rbob_price_per_gal (double), heating_oil_price_per_gal (double), three_two_one_crack_spread (double), refinery_margin_regime (string)

derivatives_labels.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (10): label_id (string), contract_id (string), underlying (string), volatility_regime (string), hedging_priority (string), liquidity_risk_label (string), arbitrage_watch_label (string), severity_score (double), implied_volatility_mean (double), avg_abs_delta (double)

futures_contracts.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (15): contract_id (string), underlying (string), contract_month (string), expiry_date (string), tenor_months (int64), spot_price (double), futures_price (double), carry_rate (double), convenience_yield (double), volume (int64), open_interest (int64), bid_ask_spread (double), curve_state (string), inventory_index (double), macro_risk_index (double)

hedging_positions.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (17): hedge_id (string), underlying (string), option_id (string), trader_type (string), position_qty (int64), target_delta (double), delta_exposure (double), gamma_exposure (double), vega_exposure (double), theta_exposure (double), hedge_ratio (double), hedge_efficiency (double), basis_risk_score (double), notional_usd (double), initial_margin_usd (double), margin_utilization_rate (double), rebalance_signal (string)

market_liquidity.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (11): liquidity_id (string), underlying (string), volume (int64), open_interest (int64), bid_ask_spread (double), instrument_type (string), instrument_id (string), mid_price (double), market_depth (double), liquidity_stress_score (double), slippage_bps (double)

open_interest.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (9): open_interest_id (string), instrument_id (string), instrument_type (string), underlying (string), open_interest (int64), volume (int64), commercial_share_pct (double), speculative_share_pct (double), participant_concentration_index (double)

options_chain.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (18): option_id (string), contract_id (string), underlying (string), option_type (string), expiry_date (string), tenor_days (int64), strike_price (double), moneyness (double), underlying_futures_price (double), implied_volatility (double), option_price (double), delta (double), gamma (double), vega (double), theta (double), bid_ask_spread (double), open_interest (int64), volume (int64)

rare_market_events.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (10): event_id (string), underlying (string), event_type (string), severity_score (double), price_shock_pct (double), volatility_multiplier (double), liquidity_depth_reduction_pct (double), bid_ask_widening_multiplier (double), margin_call_probability (double), recovery_days (int64)

trader_behavior.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (9): behavior_id (string), underlying (string), trader_type (string), observed_action (string), reaction_latency_sec (int64), risk_limit_utilization_pct (double), panic_liquidation_probability (double), dealer_gamma_pressure (double), speculative_flow_intensity (double)

volatility_surfaces.tsfile

• Time (INT64, milliseconds) — the source trade_date column.
• TAG: none — the table is stored as a single device.
• FIELD (8): surface_node_id (string), underlying (string), tenor_days (int64), moneyness (double), implied_volatility (double), option_price_mean (double), vega_mean (double), open_interest_total (int64)

Conversion notes

• One TsFile per source CSV (11 tables); each table is stored as a single device, so the rig / well / tank / equipment / sensor identifiers stay ordinary FIELDs.
• Time = the table's own clock column as INT64 milliseconds (event timestamps, sample or inspection dates, and daily record dates). The clock columns used here are trade_date.
• No column is dropped. Rows that share a timestamp are ordered by a 1 ms step in stable source order, so daily tables keep their exact calendar day.

Usage

Read this dataset with the Java SDK. It is written with the zstd compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (pip install tsfile) implements only UNCOMPRESSED, SNAPPY, GZIP and LZ4; opening this file with it yields no rows.

Read a converted file with the Apache TsFile Java SDK (org.apache.tsfile:tsfile):

import org.apache.tsfile.file.metadata.IDeviceID;
import org.apache.tsfile.read.TsFileReader;
import org.apache.tsfile.read.TsFileSequenceReader;
import org.apache.tsfile.read.common.Path;
import org.apache.tsfile.read.expression.QueryExpression;
import org.apache.tsfile.read.query.dataset.QueryDataSet;
import org.apache.tsfile.write.schema.MeasurementSchema;

import java.util.ArrayList;
import java.util.List;

String path = "calendar_spreads.tsfile";
try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path);
     TsFileReader reader = new TsFileReader(sequenceReader)) {
    // Devices are enumerated as IDeviceID objects. Tables with TAG columns
    // have multi-segment device ids that cannot be rebuilt from their string
    // form, so always use getAllDevices() rather than getAllDeviceIds().
    for (IDeviceID device : sequenceReader.getAllDevices()) {
        List<Path> paths = new ArrayList<>();
        for (MeasurementSchema schema : reader.getMeasurement(device)) {
            String name = schema.getMeasurementName();
            if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
                paths.add(new Path(device, name, true));
            }
        }
        QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
        while (dataSet.hasNext()) {
            System.out.println(dataSet.next());
        }
    }
}

Source & license

• Original dataset: xpertsystems/oil032-sample
• Source card title: OIL-032 — Synthetic Energy Derivatives Dataset (Sample)
• License: cc-by-nc-4.0 (as declared by the original dataset).