This comprehensive dataset offers minute-level data for 86 different cryptocurrency tickers in the Futures market from 2020 to 2024, fetched directly from the Binance exchange. Each entry comprises Open, High, Low, Close, Volume, and Trades, providing a granular perspective on cryptocurrency price movements and trading activity. NOTICE: CSV files were uploaded with "gzip" compression, which is why they have that "gzip" extension, but Kaggle uncompressed them when I created the dataset, so load the CSV files like usual

The global Futures Trading Services market is booming, projected to reach $28 billion by 2033 with an 8% CAGR. This in-depth analysis explores market drivers, trends, restraints, and key players, including Daniels Trading, Saxo, and Tradovate. Discover regional breakdowns and insights into software-based and web-based futures trading.

In 2022, ***** billion futures contracts were traded worldwide, up from ***** billion in 2013. The number of options contracts traded increased from **** to ***** billion contracts in the same period. Both contracts are financial derivatives, used to manage financial risk and speculate on future market performance. What are derivatives? Derivatives are financial instruments that are based on an underlying asset, such as a stock price, commodity value, or currency. There are multiple categories of derivatives, but this statistic focuses on futures and options. Futures contracts are the commitment to buy or sell the underlying at a future date for a set price. Options contracts are similar, but the holder is not required to execute the contract. Derivatives are often bought and sold on specific exchanges. What are derivatives used for? The promise of a futures contract is appealing to investors and firms who want to guarantee their expenses. For example, volatile commodities such as crude oil can rise suddenly, so a futures contract can hedge against a rise that would be damaging to a firm that relies heavily on gasoline, such as a transport company.

The volume of futures traded on the ASX 24 fluctuated greatly between January 2020 and May 2024. From a peak of ** million trades in March 2020, trades dropped as low as *** million in January 2021. In June 2025 there were over ** million trades.Futures are financial derivatives which require the buying or selling of an asset for a specified price at an agreed time in the future. Unlike options, futures obligate the buyer and seller to carry out the transaction.

This dataset offers a unified collection of futures data across various commodities, bringing together individual datasets to provide a holistic view of the commodities futures market. If your intent is to use data from multiple categories simultaneously, this collection is ideal. However, for those looking to delve deeper into specific commodities, individual datasets are also available.

Individual Categories Datasets: If you wish to explore data specific to individual categories, please refer to the datasets linked below:

• Animal Products Futures: https://www.kaggle.com/datasets/guillemservera/animal-products-futures
• Agricultural Futures: https://www.kaggle.com/datasets/guillemservera/agricultural-futures
• Fuels and Energy Futures: https://www.kaggle.com/datasets/guillemservera/fuels-futures-data
• Precious Metals Futures: https://www.kaggle.com/datasets/guillemservera/precious-metals-data
• Grains and Cereals Futures: https://www.kaggle.com/datasets/guillemservera/grains-and-cereals-futures

File Structure: - all_commodities_futures_collection.csv: A consolidated file containing futures data across various commodities. Each row includes a Category column that indicates the specific commodity type, making filtering and exploration more manageable. - individual_data/: This directory houses separate files for each commodity, allowing for more detailed explorations of specific commodities without the need to filter from the master dataset.

Learn to Extract the Data:

If you're interested in learning how to obtain this type of data on your own, you can refer to an example notebook that showcases the process for Fuels and Energy Futures. Check it out here: Downloading Fuels & Energy Data with yfinance.

Use Cases: 1. Market Analysis: Investigate price trends across different commodities and identify potential interdependencies. 2. Machine Learning: Utilize the diverse dataset for model training, testing and forecasting of futures prices. 3. Educational Purpose: Understand and teach the dynamics of different commodities in the futures market.

Image Credit:

The dataset's cover image is sourced from The Balance Money and is credited to tradeandexportme.

Data Source: All datasets within this collection have been extracted from Yahoo Finance using the yfinance Python module.

The datasets for the Role of Financial Investors on Commodity Futures Risk Premium are weekly datasets for the period from 1995 to 2015 for three commodities in the energy market: crude oil (WTI), heating oil, and natural gas. These datasets contain futures prices for different maturities, open interest positions for each commodity (long and short open interest positions), and S&P 500 composite index. The selected commodities are traded on the New York Mercantile Exchange (NYMEX). The data comes from the Thomson Reuters Datastream and from the Commodity Futures Trading Commission (CFTC).

Interest Rate Futures Market Outlook

The global Interest Rate Futures market size reached USD 5.7 trillion in 2024, according to our latest research, and is expected to grow at a robust CAGR of 8.2% during the forecast period from 2025 to 2033. By the end of 2033, the market is anticipated to reach USD 11.4 trillion. This significant growth is primarily driven by increasing demand for risk management solutions amid volatile interest rate environments, rapid financial market liberalization, and the proliferation of advanced electronic trading platforms.

One of the primary growth factors for the Interest Rate Futures market is the heightened volatility in global interest rates, fueled by central banksÂ’ dynamic monetary policies, inflationary pressures, and macroeconomic uncertainties. Financial institutions, corporates, and investors are increasingly turning to interest rate futures to hedge against potential losses from fluctuating rates, ensuring financial stability and predictability. This growing reliance on risk management tools is particularly pronounced in developed markets, where sophisticated financial instruments are integral to institutional portfolio strategies. The increasing adoption of interest rate derivatives by emerging economies, seeking to manage debt costs and attract foreign investment, further amplifies this trend.

Technological advancements in trading platforms are another major driver of market growth. The proliferation of electronic and algorithmic trading has revolutionized the accessibility, efficiency, and transparency of interest rate futures trading. Modern trading systems offer real-time data analytics, automated execution, and robust risk management features, enabling a broader range of market participants to engage in futures trading. This digital transformation has significantly reduced transaction costs and enhanced liquidity, making interest rate futures more attractive to both institutional and retail investors. Additionally, regulatory reforms mandating greater transparency and centralized clearing of derivatives have bolstered market integrity and investor confidence, further supporting expansion.

The evolving landscape of global finance, characterized by cross-border capital flows and the integration of financial markets, is also fueling the growth of the Interest Rate Futures market. As multinational corporations and institutional investors seek to optimize their global portfolios, the ability to hedge interest rate exposure across multiple jurisdictions becomes increasingly critical. The expansion of exchange-traded and over-the-counter (OTC) futures products tailored to diverse underlying assets and contract durations is enabling market participants to implement sophisticated hedging and arbitrage strategies. This trend is especially pronounced in regions like Asia Pacific and Europe, where financial market reforms and rising investor sophistication are driving demand for innovative derivatives products.

Regionally, North America continues to dominate the market, accounting for over 38% of global interest rate futures trading volume in 2024, followed by Europe and Asia Pacific. The United States, in particular, benefits from a deep and liquid market, supported by well-established exchanges such as the Chicago Mercantile Exchange (CME) and robust regulatory frameworks. Meanwhile, Asia Pacific is emerging as the fastest-growing region, with a projected CAGR of 10.3%, driven by rapid financial market development in China, India, and Southeast Asia. The increasing participation of institutional investors and the introduction of new derivatives products are expected to further accelerate growth in these regions.

In recent years, the introduction of ESG-Indexed Commodity Futures has emerged as a significant innovation within the financial markets. These futures contracts are designed to align with environmental, social, and governance (ESG) criteria, providing investors with the opportunity to hedge against commodity price volatility while simultaneously supporting sustainable practices. The growing interest in ESG-Indexed Commodity Futures reflects a broader trend towards responsible investing, as market participants increasingly seek to incorporate sustainability considerations into their trading strategies. This developmen

Swap Futures Market Outlook

According to our latest research, the global swap futures market size reached USD 1.42 trillion in 2024, with a robust compound annual growth rate (CAGR) of 18.7%. This dynamic market is projected to achieve a valuation of USD 7.82 trillion by 2033, driven by the increasing demand for transparent, standardized, and risk-mitigating financial instruments in both developed and emerging economies. Growth in the swap futures market is primarily fueled by regulatory reforms, rising volatility in interest rates and currencies, and the ongoing digitization of trading platforms.

One of the most significant growth factors for the swap futures market is the tightening of global financial regulations, especially in the aftermath of the 2008 financial crisis. Regulatory bodies such as the Commodity Futures Trading Commission (CFTC) and the European Securities and Markets Authority (ESMA) have implemented stringent requirements for over-the-counter (OTC) derivatives, promoting the adoption of exchange-traded swap futures. These regulations enhance market transparency, reduce systemic risk, and encourage market participants to shift from traditional OTC swaps to standardized swap futures contracts. As a result, financial institutions and corporate treasuries are increasingly leveraging swap futures to manage interest rate, credit, and currency risks in a more secure and compliant manner.

Technological advancements in trading platforms have also played a pivotal role in the expansion of the swap futures market. The proliferation of sophisticated electronic trading systems has facilitated faster, more efficient, and cost-effective execution of swap futures contracts. Enhanced liquidity, real-time price discovery, and improved risk management tools offered by modern trading platforms are attracting a broader spectrum of end-users, including hedge funds, asset managers, and even retail investors. Furthermore, the integration of artificial intelligence and machine learning within trading algorithms is enabling market participants to capitalize on arbitrage and speculation opportunities, further driving market growth.

Another critical factor propelling the swap futures market is the heightened volatility in global interest rates, credit spreads, and currency exchange rates. The ongoing macroeconomic uncertainties, including inflationary pressures, geopolitical tensions, and monetary policy shifts, have led to increased demand for effective hedging instruments. Swap futures provide a flexible and standardized solution for mitigating such risks, enabling corporations and institutional investors to safeguard their portfolios against adverse market movements. The growing awareness of risk management best practices and the need for efficient capital allocation are expected to sustain the upward trajectory of the swap futures market in the coming years.

From a regional perspective, North America continues to dominate the swap futures market, accounting for nearly 42% of the global market share in 2024. The region’s leadership is underpinned by a mature financial ecosystem, robust regulatory frameworks, and the presence of leading trading platforms such as the Chicago Mercantile Exchange (CME). Europe follows closely, supported by the adoption of MiFID II regulations and a strong institutional investor base. Meanwhile, the Asia Pacific region is witnessing the fastest growth, with a CAGR of 21.3%, fueled by rapid financial market development, economic expansion, and increasing participation from regional banks and corporations. Latin America and the Middle East & Africa, while still emerging, are gradually integrating swap futures into their risk management strategies, reflecting the global reach and potential of this market.

Product Type Analysis

The swap futures market is segmented by product type into interest rate swap futures, credit default swap futures, currency swap futures, commodity swap futures, and others. Interest rate swap futures represent the largest and most liquid segment, accounting for more than 55% of the total market in 2024. Their dominance is attributed to the persistent volatility in global interest rates and the need for standardized risk management solutions among banks, asset managers, and corporations. These instruments enable market participants to hedge against fluctuations in benchmark interest rates such as LIBO

Explore the dynamic Futures Trading Service market, projected to reach USD 25,000 million by 2025 with an 8.5% CAGR. Discover key drivers, trends like digital platforms, software solutions, and regional growth opportunities in this comprehensive market analysis.

This dataset contains the futures market from the following countries:

Australia -> Aus200

Brazil -> Bra50 and MinDol

Spain -> Esp35

France -> Fra40

Germany -> Ger40

Hong Kong -> HkInd

Italy-> Ita40

Netherlands -> Neth25

Switzerland -> Swi20

United Kingdom -> UK100

United States -> Usa500, UsaTec and UsaRus

There's a csv file for all those markets and one with all in one.

Note: the MinDol, Swi20 and Neth25 data were taken by it's monthly contract, because MetaTrader5 don't have their historical series (like S&P 500, that has the 'Usa500' and 'Usa500Mar24'):

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F17272056%2Fefa5c9f6d7841c496d20d467d4a1c874%2Ffutures_dailycontract.png?generation=1704756245532483&alt=media" alt="">

MT5 Library: (I used PyCharm because the i couldn't be able to use the mt5 library on GoogleColab)

import MetaTrader5 as mt5
import pandas as pd
import numpy as np
import pytz
from datetime import datetime

if not mt5.initialize(login= , server= "server", password=""):
# you can use your login and password if you have an account on a broker to use mt5
  print("initialize() failed, error code =", mt5.last_error())
  quit()


symbols = mt5.symbols_get()

list_symbols = []
for num in range(0, len(symbols)):
  list_symbols.append(symbols[num].name)

print(list_symbols)

list_futures = ['Aus200', 'Bra50', 'Esp35', 'Fra40', 'Ger40', 'HKInd', 'Ita40Mar24', 'Jp225', 'MinDolFeb24', 'Neth25Jan24', 'UK100', 'Usa500', 'UsaRus', 'UsaTec', 'Swi20Mar24']
time_frame = mt5.TIMEFRAME_D1
dynamic_vars = {}

time_zone = pytz.timezone('Etc/UTC')

time_start = datetime(2017, 1, 1, tzinfo= time_zone)
time_end = datetime(2023, 12, 31, tzinfo= time_zone)

for sym in list_futures:
  var = f'{sym}'
  rates = mt5.copy_rates_range(sym, time_frame, time_start, time_end)

  rates_frame = pd.DataFrame(rates)
  rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
  rates_frame = rates_frame[['time', 'close']]
  rates_frame.rename(columns = {'close': var}, inplace = True)
  dynamic_vars[var] = rates_frame

  dynamic_vars[sym].to_csv(f'{sym}.csv', index = False)

This dataset provides comprehensive and up-to-date information on futures related to oil, gas, and other fuels. Futures are financial contracts obligating the buyer to purchase and the seller to sell a specified amount of a particular fuel at a predetermined price and future date.

Use Cases: 1. Trend Analysis: Scrutinize patterns and price fluctuations to anticipate future market directions in the energy sector. 2. Academic Research: Delve into the historical behavior of oil and gas prices and understand the influence of global events on these commodities. 3. Trading Strategies: Develop and test trading tactics based on the dynamics of oil, gas, and other fuel futures. 4. Risk Management: Utilize the dataset for hedging and risk management for corporations involved in the extraction, refining, or trading of fuels.

Dataset Image Source: Photo by Pixabay: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

Column Descriptions: 1. Date: The date when the data was documented. Format: YYYY-MM-DD. 2. Open: Market's opening price for the day. 3. High: Peak price during the trading window. 4. Low: Lowest traded price during the day. 5. Close: Price at which the market closed. 6. Volume: Number of contracts exchanged during the trading period. 7. Ticker: The unique market quotation symbol for the future. 8. Commodity: Specifies the type of fuel the future contract pertains to (e.g., crude oil, natural gas).

Get key insights on Market Research Intellect's Futures Trading Service Market Report: valued at USD 8.5 billion in 2024, set to grow steadily to USD 12.3 billion by 2033, recording a CAGR of 5.0%.Examine opportunities driven by end-user demand, R&D progress, and competitive strategies.

Futures Market Technical Analysis Dataset This dataset contains daily price and technical indicator data for a diverse range of futures contracts across multiple market sectors, including:

Equity Index Futures: E-mini S&P 500 (ES), E-mini NASDAQ 100 (NQ), E-mini Dow Jones (YM), E-mini Russell 2000 (RTY) Energy Futures: Crude Oil (CL), Natural Gas (NG), NY Harbor ULSD (HO) Metals: Gold (GC), Copper (HG), Silver (SI), Platinum (PL) Currency Futures: Euro (EU), Japanese Yen (JY), British Pound (BP), Canadian Dollar (CD), Swiss Franc (SF) Agricultural Commodities: Corn (C), Soybeans (S), Wheat (W), Feeder Cattle (GF) Fixed Income: Various US Treasury contracts (TY, FV, US, TU) The dataset features:

Price data: open, high, low, close, and volume Target variable: likely for predictive modeling Technical indicators: Bollinger Bands (80-period) Donchian Channels (multiple timeframes: 5, 10, 20, 40, 80, 160-day and 4, 10, 20, 50-week) Moving Average Differences (multiple pairs and timeframes) Previous returns (standard and logarithmic) Turtle trading system indicators

The crude oil futures market is a financial exchange where traders can buy or sell contracts for the future delivery of crude oil. It is one of the most actively traded commodity futures markets in the world, providing opportunities for both hedging and speculation. Learn how this market operates and influences the global economy.

The WTI (West Texas Intermediate) futures market is one of the most important and widely-traded commodity futures markets in the world. Learn about how the market operates, its participants, and the factors influencing its prices. Discover various trading strategies and the role it plays in the global oil market.

ABSTRACT Objective: The present study estimates the liquidity cost of the corn future contract traded on B3 (formerly BM&FBovespa) and compare it to the CME corn future contract, through five implicit bid-ask spread measures. Originality/value: The market microstructure approach, with its focus on high frequency data, reveals characteristics of the emerging agricultural markets (also known as thin markets), which were not evident in studies with daily frequency data. Design/methodology/approach: To analyze the performance of five cost estimators, the data used in our analysis consists of intraday series of future contracts of B3 and CME from September 1, 2015, to August 30, 2016. The methodology adopted includes these estimators: Roll model (1984); Model of Thompson & Waller (1987) model of Choi, Salandro & Shastri (1988);Model of Chu, Ding & Pyun (1996) and the model of Wang, Yau & Baptiste (1997). Findings: The liquidity cost is lower in CME’s future corn market than in B3, and the estimated cost of liquidity in CME’s future corn market is 2 to 3 cents (in R$/60-kgbag) while at BM & F the cost is 6 to 16 cents (in R$/60-kgbag).

Market Overview The global futures trading software market is projected to reach a market size of USD 3601.3 million by 2033, expanding at a CAGR of 6.4%. The increasing demand for risk management tools, advancements in technology, and growing popularity of algorithmic trading are driving market growth. Additionally, the rising number of personal and commercial traders, along with the increasing availability of mobile trading platforms, further contribute to the market's expansion. Key Trends and Segments Mobile trading platforms are gaining traction due to their convenience and accessibility, while PC versions remain dominant in commercial applications. Personal and commercial traders continue to be the largest user segments, with commercial use expected to see significant growth as businesses seek advanced risk management capabilities. Key companies in the market include Straight Flush, Goldman Sachs, Morgan Stanley, J.P. Morgan, and BANK OF AMERICA. Geographically, the Asia Pacific region holds the largest market share, followed by North America and Europe. Emerging markets such as China and India are expected to present significant growth opportunities for market expansion.

The graph shows the changes in the impact factor of ^ and its corresponding percentile for the sake of comparison with the entire literature. Impact Factor is the most common scientometric index, which is defined by the number of citations of papers in two preceding years divided by the number of papers published in those years.

Swap Futures Market Outlook

According to our latest research, the global swap futures market size in 2024 is valued at USD 3.9 billion, reflecting a robust and expanding landscape driven by evolving financial risk management needs and increasing demand for transparent, standardized derivatives instruments. With a remarkable CAGR of 14.2% projected for the period 2025–2033, the market is forecasted to reach an impressive USD 12.1 billion by 2033. This growth is primarily fueled by the increasing adoption of swap futures for hedging interest rate, credit, and currency risks, as well as the growing sophistication of trading strategies among institutional investors worldwide.

A key growth factor propelling the swap futures market is the heightened regulatory scrutiny and evolving compliance requirements in global financial markets. Regulatory reforms such as the Dodd-Frank Act in the United States and the European Market Infrastructure Regulation (EMIR) in Europe have mandated greater transparency, central clearing, and standardized trading of derivatives contracts. Swap futures, as exchange-traded derivatives, offer significant advantages over traditional over-the-counter (OTC) swaps, including reduced counterparty risk, improved price discovery, and lower capital requirements. These regulatory drivers are compelling financial institutions and corporate treasuries to increasingly favor swap futures for risk management and speculative purposes, thereby accelerating market growth.

Another significant driver is the continuous innovation in trading technologies and the proliferation of electronic trading platforms. The migration from voice-based OTC trading to highly automated, electronic exchange-traded platforms has substantially enhanced the liquidity, accessibility, and efficiency of swap futures markets. Advanced algorithmic trading, real-time risk analytics, and seamless integration with clearinghouses have made swap futures more attractive to a broader spectrum of market participants, including asset managers, hedge funds, and proprietary trading firms. The resulting surge in trading volumes and open interest further reinforces the virtuous cycle of liquidity and market depth, underpinning sustained expansion in the swap futures market.

Furthermore, the shift in global interest rate environments and currency volatility has amplified the need for robust hedging solutions among corporates and institutional investors. As central banks adjust monetary policies in response to inflationary pressures and macroeconomic uncertainties, the demand for interest rate, credit, and currency swap futures as risk mitigation tools has intensified. These instruments enable market participants to efficiently manage exposures, lock in funding costs, and exploit arbitrage opportunities across diverse asset classes. The growing interconnectedness of global financial markets and the increasing complexity of risk profiles are expected to continue driving the adoption of swap futures over the coming decade.

In the realm of financial derivatives, Total Return Equity Swaps have emerged as a pivotal tool for investors seeking to gain exposure to equity returns without directly owning the underlying assets. These swaps allow parties to exchange the total return of an equity asset, including dividends and capital gains, for a predetermined interest rate or another financial instrument's return. This mechanism provides flexibility and efficiency in managing equity exposure, particularly in volatile markets. The increasing use of Total Return Equity Swaps reflects a broader trend towards sophisticated risk management strategies, enabling investors to optimize their portfolios while mitigating potential risks associated with direct equity investments.

From a regional perspective, North America currently dominates the swap futures market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The United States, in particular, has established itself as a global hub for swap futures trading, supported by advanced market infrastructure, deep liquidity pools, and a mature regulatory environment. Europe is witnessing steady growth, propelled by regulatory harmonization and increased participation from institutional investors. Meanwhile, Asia Pacific is emerging as a high-growth region, f

Futures market is an important part of the financial market, with a high degree of liquidity and leverage effect. However, the futures market is also faced with various risk factors, such as price fluctuations, market shocks, supply and demand changes. In order to better determine the risk correlation between specific futures markets, this paper uses the wavelet transform—quantile Granger causality test method to identify the risk correlation of four major futures markets in the US futures market from the end of January 2009 to the end of March 2023, such as gold, crude oil, soybeans and natural gas. It provides a new perspective and method for the risk correlation identification of the futures market. The results show that futures contracts with different maturities and price fluctuations under different quantiles have a significant impact on risk correlation. Specifically, in 1-month and 6-month futures contracts, the strongest bidirectional risk correlation exists between gold and natural gas (T-statistics -15.94 and 10.92, respectively); In the 1-month futures contract, there is also a strong bidirectional risk association between crude oil and soybeans and natural gas (T-statistics are 6.87, 17.42, -2.05, 7.35, respectively), while in the 6-month futures contract, there is a bidirectional risk association between crude oil and soybeans (T-statistics are -2.49 and 18.374, respectively). However, natural gas has unidirectional risk association with crude oil and soybean (t statistics are 2.7 and -3.35, respectively); There is a bidirectional risk correlation between gold and soybean, that is, the risk correlation between gold and soybean increases with the increase of the degree of price fluctuation; There is a one-way risk association between gold and crude oil, soybean and gold, and crude oil and natural gas (the T-statistic is greater than the critical value of 1.96). In addition, there is a strong bidirectional or unidirectional risk association between all varieties at the 0.95 quantile. The research results of this paper have certain reference value for the supervision, investment and risk management of the futures market. This paper uses the wavelet transform and quantile Granger causality test method to identify the risk correlation of the futures market, providing a new perspective and method for the risk correlation identification of the futures market, and uses relatively new data to ensure the effectiveness of the empirical analysis. However, there are some limitations in this paper, such as the applicability of wavelet transform-quantile Granger causality test method. Future studies can further expand the sample range, compare the effects of different methods, and explore the risk transmission mechanism between different varieties.