United Kingdom Hedge Fund Market was valued at USD 1.21 Trillion in 2024 and is expected to reach USD 1.80 Trillion by 2030 with a CAGR of 6.8% during the forecast period.

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.

US aluminum futures refers to standardized contracts for the future delivery of aluminum on the commodities exchange in the United States. This article explores the role of aluminum futures in managing price risk, the primary exchange for trading, contract specifications, pricing factors, and the diverse range of market participants involved. Find out how aluminum futures provide a regulated and transparent marketplace for managing price risk and supporting the functioning of the aluminum industry.

United States Hedge Fund Market was valued at USD 2.54 Trillion in 2024 and is expected to reach USD 3.56 Trillion by 2030 with a CAGR of 5.8% during the forecast period.

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.

Resilience quantifies the ability of a system to remain in or return to its current state following disturbance. Due to inconsistent terminology and usage of resilience frameworks, quantitative resilience studies are challenging, and resilience is often treated as an abstract concept rather than a measurable system characteristic. We used a novel, spatially-explicit stakeholder engagement process to quantify social-ecological resilience to fire, in light of modeled social-ecological fire risk, across the non-fire-adapted Sonoran Desert Ecosystem in Arizona, USA. Depending on its severity and the characteristics of the ecosystem, fire as a disturbance has the potential to drive ecological state change. As a result, fire regime change is of increasing concern as global change and management legacies alter the distribution and flammability of fuels. Because management and use decisions impact resources and ecological processes, social and ecological factors must be evaluated together to predict resilience to fire. We found highest fire risk in the central and eastern portions of the study area, where flammable fuels occur with greater density and frequency and managers reported fewer management resources than in other locations. We found lowest fire resilience in the southeastern portion of the study area, where combined ecological and social factors, including abundant fuels, few management resources, and little evidence of past institutional adaptability, indicated that sites were least likely to retain their current characteristics and permit achievement of current management objectives. Analyzing ecological and social characteristics together permits regional managers to predict the effects of changing fire regimes across large, multi-jurisdictional landscapes and to consider where to direct resources. This study brought social and ecological factors together into a common spatial framework to produce vulnerability maps; our methods may inform researchers and managers in other systems facing novel disturbance and spatially-variable resilience.

The global financial derivatives market is experiencing robust growth, driven by increasing market volatility, the need for sophisticated risk management tools, and the expansion of investment opportunities across diverse asset classes. The market, encompassing forwards, futures, options, and swaps used for hedging, speculative arbitrage, and other purposes, is projected to maintain a healthy Compound Annual Growth Rate (CAGR). While precise figures for market size and CAGR are not provided, a reasonable estimation based on industry reports and observed market trends suggests a substantial market value, likely in the hundreds of billions or even trillions of dollars, depending on the chosen valuation methodology (e.g., notional value vs. market value of outstanding contracts). Key drivers include the growing complexity of global financial markets, regulatory changes demanding more robust risk mitigation strategies, and the increasing adoption of algorithmic trading and high-frequency trading, which rely heavily on derivative instruments. Geographic growth is uneven, with North America and Europe currently holding significant market share, while Asia-Pacific shows considerable potential for future expansion due to increasing financial market sophistication and economic growth in emerging economies like China and India. However, the market also faces certain restraints. These include stringent regulatory oversight aimed at mitigating systemic risk, which can increase compliance costs and limit certain trading strategies. Furthermore, the inherent complexity of many derivatives products requires specialized expertise, potentially limiting accessibility for smaller investors and businesses. Market fluctuations and unforeseen global events (e.g., geopolitical instability, economic recessions) can impact market sentiment and trading volumes. The competitive landscape is highly concentrated, with major global investment banks and specialized financial institutions dominating the market. However, the increasing adoption of fintech solutions and the emergence of new market participants, especially in the areas of exchange-traded derivatives and over-the-counter (OTC) markets, are likely to reshape the market dynamics over the forecast period. The segmentation by derivative type (forwards, futures, options, swaps) and application (hedging, speculative arbitrage, others) provides a granular view of market dynamics, enabling strategic decision-making for businesses operating within this dynamic sector.

High price volatility among various commodities and the recent lowering of interest rates has fueled strong growth among commodity contracts intermediation brokers. While the national economy has continued to recover following a period of high inflationary pressures, recent rate cuts by the Federal Reserve and continued price volatility of oil and agricultural products strengthened commodity contracts’ popularity. Short-term contracts and future continue to facilitate interest among brokers, with revenue growing at a CAGR of 4.6% to an estimated $21.8 billion through the end of 2024, including an estimated 2.3% boost in 2024 alone. Profit continues to remain steady, as higher price volatility and lower interest rates continue to facilitate favorable market conditions for commodity traders. Banks, once outsized players in the industry, have significantly downsized or completely ended their commodity trading activities. This has put significant downward pressure on revenue as these institutions have been forced to limit proprietary trading due to the Volcker rule, enacted prior to the current period. The decreased presence of banks in the industry has allowed smaller players to enter the industry, exacerbating fragmentation among various service groups. The inflationary spike played a key role in buoying growth, with recent geopolitical conflicts in the Middle East and Europe strengthening commodity price volatility. Moving forward, commodity contract intermediaries face a less certain landscape, as anticipated declines in global oil prices and the agricultural price index will dampen the popularity of long-term commodity trades. Increased demand for metal and energy products and the low inventories of metal commodities are expected to sustain a significant revenue stream for brokers. However, further uncertainty surrounding rising tensions in the Middle East will impact the types of trades made by commodity traders. Greater automation and adoption of new technologies such as blockchain will offer a workflow enhancement in the longer term. Nonetheless, an expected decline in global oil prices is poised to cause revenue to fall at a CAGR of 1.0% to an estimated $20.8 billion through the end of 2029.

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.

This data publication contains transcripts from an expert foresight panel discussing the future of wildland fire management in a series of structured, text-based, asynchronous online discussions. Panelists included seven leading academic and professional futurists plus two wildfire professionals. This expert foresight panel discussed the potential for high-impact future developments in wildland fire management, the likelihood and impact of these developments, and policies that encourage positive developments in wildland fire management. These discussions are included here as twenty-seven documents, each devoted to a single topic, grouped in three rounds of week-long correspondence between panel members from June through December of 2013. Round one consisted of discussions on the following topics: climate change, monitoring, serious games, bioengineering, new firefighting technologies, insurance, risk assessment, economic and political context, value change, fire-resistant designs and materials, public education and engagement, and policy tools. The second round of discussions required the panelists to react to three mini-scenarios, each scenario described a wide range of plausible social, economic, and technological contexts for fire management in the future. The third round included four discussion threads based on the ideas and concepts examined during the first two rounds of discussion.The purpose of convening an expert foresight panel to discuss wildland fire management was to anticipate and discuss present and future developments in wildland fire management, to identify the strengths and weaknesses of current national fire policy, and to anticipate the future trajectory of national fire policy in light of recent developments in several important areas related to wildland fire management.Original metadata date was 6/14/2016. Minor metadata updates on 12/19/2016.

The data are supplied commercially and format may change over time. The Chicago Mercantile Exchange dataset consisted of csv files containing columns of tick times with associated trade prices. The Cantor Fitzgerald database was available in ASCII format, comma delimited with varying numbers of fields over the time frame. The data were cleaned to extract the time stamp of trades and transaction price. Thomson Datastream is a large provider of economic and financial data available by commercial subscription

0.05 quantile detail components of 6-month futures contracts for gold, crude oil, soybean and natural gas Granger causal t statistic value matrix rolling window estimation.

Rolling window estimate of Granger causal t statistic value matrix for 0.5 quartile approximate component of 1-month futures contracts for gold, crude oil, soybean and natural gas.

The global Execution Services market is experiencing robust growth, driven by increasing trading volumes, the proliferation of algorithmic trading, and a rising demand for sophisticated order management systems. The market, valued at approximately $15 billion in 2025, is projected to grow at a compound annual growth rate (CAGR) of 8% from 2025 to 2033, reaching an estimated $28 billion by 2033. This expansion is fueled by several key trends, including the increasing adoption of high-frequency trading (HFT) strategies, the growing popularity of alternative trading systems (ATS), and the continued migration to electronic trading platforms. The segment breakdown reveals significant growth across all service types (Pre-trade, Trade, and Post-trade) with Equities and Futures trading consistently leading in application-based market share. Regulatory changes and increasing cybersecurity concerns are key factors that will influence the pace of growth in the coming years. Furthermore, the geographic distribution of the market shows strong performance in North America and Europe, driven by established financial markets and advanced technological infrastructure. However, Asia-Pacific is anticipated to witness substantial growth due to the expansion of its capital markets and increasing adoption of electronic trading. The competitive landscape is characterized by a mix of large multinational financial institutions and specialized technology providers. These companies are constantly innovating to provide superior execution capabilities, including advanced analytics, risk management tools, and customized solutions for diverse client needs. This intense competition is driving further efficiency improvements and market fragmentation, thus accelerating innovation and shaping the future of the Execution Services market.

The bond fund sales market has been experiencing steady growth in recent years, driven by factors such as low interest rates, increasing demand for fixed income investments, and growing awareness of bond funds among investors. The market is expected to continue expanding over the next decade, with a projected CAGR of XX% during the 2025-2033 forecast period. Key trends in the bond fund sales market include the rising popularity of ETFs and index funds, as well as the increasing demand for ESG-compliant and impact-oriented bond funds. These trends are being driven by factors such as technological advancements, regulatory changes, and growing investor demand for sustainable investments. The market is also expected to benefit from the growth of wealth management and retirement planning, as more individuals seek to manage their financial futures.

Middle Island is the most easterly of the Marine Futures sampling areas, and is located in the Recherche Archipelago, which comprises over 150 islands east of Esperance. This collection comprises datasets describing habitat mapping, biodiversity and human uses in the Middle Island area. Habitat mapping consists of four Google earth detailed and basic biota and substratum maps for Middle Island. There are two baited remote underwater video systems (BRUVS) datasets and five interactive Microsoft Excel charts each of which contribute to biodiversity analysis. The baited videos illustrate the fish diversity over an array of habitats found throughout the Middle Island study location. The interactive Microsoft Excel charts combine the biodiversity and mapping products to give the user an interactive and visual display of which organisms are found in what habitats. A Human Uses report containing an appendix of the Middle Island study location is also included.

0.05 quartile detail components of gold, crude oil, soybean and natural gas 1-month futures contracts Granger causal t statistic value matrix rolling window estimation.

The Marine Futures project has mapped and sampled benthic and fish diversity in around 200 square kilometres off Jurien Bay, including around the offshore islands.

Habitat mapping consists of five Google earth detailed and basic biota and substratum maps for Jurien Bay.

There are two baited remote underwater video systems (BRUVS) datasets and six interactive Microsoft Excel charts each of which contribute to biodiversity analysis.

The baited videos illustrate the fish diversity over an array of habitats found throughout the Jurien Bay study location.

The interactive Microsoft Excel charts combine the biodiversity and mapping products to give the user an interactive and visual display of which organisms are found in what habitats.

A Human Uses report containing an appendix of the Jurien Bay study location is also included.