Up to 6,000 jobs are to go at HP worldwide in the next three years as the US computer and printer maker increasingly adopts AI to speed up product development.
Announcing a lower-than-expected profit outlook for the coming year, HP said it would cut between 4,000 and 6,000 jobs by the end of October 2028. It has about 56,000 employees. The news drove its shares lower by 6%.
“As we look ahead, we see a significant opportunity to embed AI into HP to accelerate product innovation, improve customer satisfaction and boost productivity,” said the California company’s chief executive, Enrique Lores.
He said teams working on product development, internal operations and customer support would be affected by the job cuts. He added that this would lead to $1bn (£749m) annualised savings by 2028, although the cuts will cost an estimated $650m.
News of the job cuts came as a leading educational research charity warned that up to 3m low-skilled jobs could disappear in the UK by 2035 because of automation and AI. The jobs most at risk are those in occupations such as trades, machine operations and administrative roles, the National Foundation for Educational Research said.
HP had already cut between 1,000 and 2,000 staff in February as part of a restructuring plan.
It is the latest in a run of companies to cite AI when announcing cuts to workforce numbers. Last week the law firm Clifford Chance revealed it was reducing business services staff at its London base by 10% – about 50 roles – attributing the change partly to the adoption of the new technology.
The head of PwC also publicly walked back plans to hire 100,000 people between 2021 and 2026, saying “the world is different” and AI had changed its hiring needs.
Klarna said last week that AI-related savings had helped the buy now, pay later company almost halve its workforce over the past three years through natural attrition, with departing staff replaced by technology rather than by new staff members, hinting at further role reductions to come.
Several US technology companies have announced job reductions in recent months as consumer spending cooled amid higher prices and a government shutdown.
Executives across industries are hoping to use AI to speed up software development and automate customer service. Cloud providers are buying large supplies of memory to meet computing demand from companies that build advanced AI models, such as Anthropic and OpenAI, leading to a rise in memory costs.
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Analysts at Morgan Stanley have warned that soaring prices for memory chips, driven by rising demand from datacentres, could push up costs and dent profits at HP and rivals such as Dell and Acer.
“Memory costs are currently 15% to 18% of the cost of a typical PC, and while an increase was expected, its rate has accelerated in the last few weeks,” Lores said.
HP announced better-than-expected revenues of $14.6bn for its fourth quarter. Demand for AI-enabled PCs continues to climb, and they made up more than 30% of HP’s shipments in the fourth quarter to 31 October.
The contract covers development and pre-series vehicles as well as two production batches with a term until 2032. In a first batch, equipment for 274 vehicles was ordered; further options for additional systems are planned. In addition to supplying hardware and software, HENSOLDT is providing a comprehensive logistics support package – including training, documentation, spare parts supply and long-term system support.
“With this order, HENSOLDT is underpinning its role as a pioneer of a new technological era in defence and sustainably strengthening the modernisation of the German reconnaissance forces,” said Oliver Dörre, CEO of HENSOLDT AG. “In the age of networked operations, data is the new ammunition. The LUCHS 2 thus represents a clear paradigm shift: We are developing systems whose capabilities are no longer static, but can be further developed in a software-defined, modular manner throughout their entire life cycle. In this way, we are creating genuine information superiority, increasing the Bundeswehr’s capacity to act and, at the same time, securing Europe’s technological sovereignty.”
CERETRON – the brain of the LUCHS 2
CERETRON is the central mission system in LUCHS 2. It integrates the platform’s numerous different sensors for various spectra, processes their data in real time and uses it to generate a consistent tactical situation picture in the vehicle. With the help of AI-supported image processing, CERETRON automatically detects, identifies and tracks objects and persons, thus providing decision-relevant information directly to the crew and command structures.
Thanks to its NGVA-compliant, software-defined architecture, CERETRON is scalable and adaptable: new capabilities, functions and algorithms can be integrated without interfering with the vehicle hardware, thereby expanding the system’s performance throughout its entire life cycle. Sensor extensions can be added to the hardware as needed and then integrated into the software. At the same time, CERETRON reduces the cognitive load on the crew by automatically processing, prioritising and presenting information in a comprehensible manner. The resulting situation picture is available to every user on the platform in the relevant form – a central principle of software-defined defence and a significant advantage for quick, safe decisions in the field.
Multispectral sensor integration for maximum reconnaissance
In the LUCHS 2, a broad portfolio of sensors is natively integrated into CERETRON. This enables consistent end-to-end data management and an unprecedented depth of automated sensor fusion.
BAA IV – Long-range reconnaissance
Besides the combined thermal imaging and daylight sensors with laser rangefinder and target illuminator, the multispectral observation and reconnaissance system can also integrate an optional short-wave infrared (SWIR) camera for optimum visibility in poor weather conditions (rain, fog, etc.).
SETAS – All-round visibility and protection in real time
The See-Through Armour System (SETAS) offers all-round visibility day and night. The crew remains protected in the vehicle while still being able to keep an eye on their surroundings at all times. SETAS detects threats early in real time.
The mission system also includes a radio direction finder (RDF), laser warning system, and acoustic sensors that detect and partially locate respective signals to not only warn the crew immediately of threats, but to enable them to respond optimally.
Christina Canitz, Head of Optronics Division at HENSOLDT, said: “For the LUCHS 2, we are combining our core optronic and sensor capabilities into a powerful overall system. It is crucial that the crew can see, recognise and make safe decisions under all conditions. With this range of capabilities, we are creating clear operational added value for the Bundeswehr’s reconnaissance forces.”
MDOcore – the backbone of multi-domain missions
CERETRON can be seamlessly integrated into HENSOLDT’s new multi-domain software suite MDOcore, transferring data and situational information to make it available to higher user levels. MDOcore is HENSOLDT’s software-centred integration framework that networks sensors, effectors and cognitive systems across all domains – land, air, sea, cyber and space – and weapon systems, thus forming the technological backbone of future networked defence architectures.
The number of electric passenger cars in the EU reached 4.4 million in 2023, accounting for 1.73% of all passenger cars. Compared with 2022, the total number of electric cars went up by 1.4 million.
In 121 (56.28%) out of the 215 regions at level 2 of the nomenclature of territorial units for statistics (NUTS 2) with available data, the share of electric cars in the total passenger cars was below the EU average. For most EU countries, this share was relatively homogeneous across regions, suggesting that factors such as national subsidies and incentives or other national factors likely played an important role in the adoption of these vehicles.
A total of 17 regions reported that electric cars made up at least 4.00% of all passenger cars (darkest shade of blue on the map):
with all its 5 regions, Denmark led the distribution along with Sweden (5 out of 8 regions), including the capital regions of Hovedstaden and Stockholm
3 regions in the Netherlands, among them the capital region of Noord-Holland
2 regions in Belgium, including the capital region of Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest
the Finnish capital region of Helsinki-Uusimaa
and Luxembourg
Source dataset: tran_r_elvehst and tran_r_vehst
At the top end of the distribution, the central Dutch region of Flevoland recorded by far the highest share of electric cars in 2023, at 17.07%. This unusually high figure may reflect the presence of vehicle leasing companies based in the region, which register large fleets of electric vehicles and thereby inflate the number of electric cars relative to the size of the regional car population. The Swedish capital region of Stockholm (10.74%) was the only other region in the EU to record a double-digit share. It was followed by Hovedstaden in Denmark (8.64%) and Prov. Vlaams-Brabant in Belgium (7.60%).
At the lower end of the distribution, 46 regions reported that electric cars accounted for fewer than 0.25% (lightest shade of yellow on the map) of all passenger cars in 2023. This group was largely concentrated in Czechia (5 out of 8 regions), Greece (11 of 13), Poland (14 of 17) and Slovakia (3 of 4). There was also a cluster in southern Italy (6 regions). The remainder of the group consisted of 4 regions from Spain, 2 regions from Romania, as well as a single region from Croatia.
The use of electric passenger cars reflects income levels, price differences between electric and other vehicles, subsidies and incentives, infrastructure investment, battery technology, fuel prices, urban policies, the availability and cost of public transport, and environmental consciousness.
Would you like to know more about transport statistics at the regional level?
You can read more about transport statistics in the Eurostat regional yearbook – 2025 edition, also available as a set of Statistics Explained articles, as well as in the transport section of the interactive publication Regions in Europe and the Statistical Atlas.
The development process for offshore wind projects in the Philippines begins by the developer obtaining a Certificate of Endorsement with the DOE. This is accompanied by other registrations and approvals, such as business registration with the Securities and Exchange Commission and tax registration with the Bureau of Internal Revenue. The developer is also required to post a performance bond, being 2% (or 1% if not using a port administered by the Philippine Ports Authority) of the project cost per MW, multiplied by the offered capacity in MW according to the GEA-5 Terms of Reference.¹⁶
The next stage of the development process is pre-development. The developer must obtain an OWESC from the DOE as well as endorsements or permits from other agencies (including the DENR and National Commission on Indigenous Peoples) to ensure the project is environmentally sound, socially accepted, and technically feasible. Upon receipt of a Certificate of Confirmation of Commerciality from the DOE, the project commences its construction and commissioning phase. At this point, the Wind Energy Operating Contract (“WEOC”) is issued granting legal authority to generate and sell electricity.
The project must receive a further Certificate of Endorsement from the DOE and may enter several other agreements. For example, a Connection Agreement with the National Grid Corporation of the Philippines is required to connect to the grid. The project may also register with WESM via the Philippine Electricity Market Corporation, obtain a Certificate of Compliance and Feed-in Tariff eligibility from the Energy Regulatory Commission (“ERC”), and enter a REPA with the payment agent National Transmission Corporation (“TransCo”) if supplying under a Green Energy Auction Program.
GEA-5 Auction
On 11 June 2025, the DOE officially launched GEA-5 focussed exclusively on fixed-bottom OSW technology with an installation target of 3300MW between 2028-2030.¹⁷ Prior Green Energy Auction rounds did not include OSW, so this marks a major shift signalling the country’s intent to tap into its vast OSW potential. Fixed-bottom offshore wind was chosen due to its established global track record, cost-effectiveness and scalability.
Whilst the DOE acknowledges the future potential of floating offshore wind, the decision to prioritise fixed-bottom technology reflects a strategic effort to build early momentum. Current technical capabilities, regulatory frameworks, and infrastructure readiness make it the most viable pathway for successful deployment at this stage. If successful, GEA-5 is expected to attract significant foreign investment and position the Philippines as a regional leader in OSW.
The allocation framework methodology for GEA-5 incorporates price and non-price criteria, including price competitiveness, project readiness and capacity.¹⁸ In terms of the auction timeline, the DOE is yet to publish the Notice of Auction and the green energy auction reserve price is pending finalisation, so further delays are expected.
Figure 2: Prescribed timeline for GEA-5 (D = Day).¹⁹
Activity
Tentative Timeline
DOE Issuance/Posting of List of Winning Bidders/Notice of Award
D99 + 1 working day
Auction Proper
D68 + 1 working day
Pre-Bid Conference
D49 + 2 working days
Notification to Qualified Bidders on successful registration and to Qualified Suppliers who failed the evaluation
D38 + 1 working day
Last day of Registration
D32 + 3 working days
Start of Registration of Qualified Suppliers
D31 + 1 working day
Publication of Notice of Auction and Terms of Reference
“This recognition highlights Arkema’s ability to leverage material chemistry for sustainability, in partnership with leaders in boating, composites, and recycling. Together, we are building a viable circular model for a more responsible future,” says Pierre Gérard, R&D Expert in Composite Materials at Arkema, who was deeply involved in establishing this alliance.
The alliance will also be a central feature of the 2025 Paris Boat Show from November 26 to December 1 at the Parc des Expositions du Bourget. On Beneteau’s stand in Hall 3, visitors will discover an educational pathway dedicated to circular boatbuilding, in partnership with the five other major players in the alliance. This initiative reflects Beneteau’s commitment, as a global leader in boating, to innovate toward more recyclable boats with a lower environmental footprint.
International stock markets tracked Wall Street gains and U.S. stock futures pointed to a higher open ahead of the Thanksgiving holiday. The higher close in the prior session was broad-based, even as AI chip giant Nvidia’s shares fell amid potential competition in AI semiconductors from Google.
Also in investors’ focus, delayed U.S. economic data that again boosted expectations for a Federal Reserve rate cut next month.
In light of recent media coverage about the resumption of Gemini sailings through Suez / the Red Sea and the timing of such, the Gemini partners Hapag-Lloyd and A.P. Moller – Maersk share the following update:
At the launch of the Gemini Cooperation in February 2025, A.P. Moller – Maersk and Hapag-Lloyd introduced a Cape of Good Hope network due to the on-going disruptions in the Red Sea.
Gemini’s ambition has always been to return to a Suez-based East-West network once security conditions in the region permit. However, as the safety of crew, vessels and cargo remains our top priority, we currently have no specific timing to change the Gemini East-West network to sailing through the Red Sea.
Considering the Gaza ceasefire progress, we closely monitor developments in the region, and we are continuously conducting detailed security assessments. When security conditions warrant it, and in keeping with the Gemini trademark of industry-leading schedule reliability, Hapag-Lloyd and A.P. Moller – Maersk will carefully coordinate with our respective customers and important stakeholders to ensure an orderly transfer to a Suez-based network with minimal disruption to our customer´s supply chains.
We will keep you updated on the Gemini network should any changes occur.
What’s a conversation we’re not having enough when it comes to AI and the future of work?
There is no shortage of headlines and articles on AI and the future of work. But too often, this discourse focuses solely on job losses, coupled with sensational headlines. While technologies continue to evolve rapidly, meaning that we can’t yet drew firm conclusions, it is also true that we need to look at the labour market effects much more carefully. This entails understanding how AI impacts not only the quantity of jobs but also the quality of them and the nature of work, in terms of wages, working conditions and rights more broadly. The larger issue of inequality is also crucial.
2. In your view, what are the current and potential future impacts of automation on developing economies?
Currently, the impact of digitalization and AI in developing economies is less than in advanced economies, primarily due to the digital divide and differences in the structure of economies. While the possible negative effects on jobs are less (but not zero), we also know, as shown by ILO research, that the digital divide prevents developing countries from taking advantage of the benefits from new technologies, such as AI.
But there are two caveats to this view that developing countries are not being affected by AI. First, digital tools and platforms are growing rapidly, even if the use of generative AI is more confined to small part of the population – see the rise of digital payment systems, such as M-PESA in Eastern Africa, and the rapid emergence of digital labour platforms, both location-based and online, which are creating opportunities and challenges in all countries. Second, emerging technologies, such as AI, continue to evolve so we cannot assume that the situation today will hold in the coming months and years. We need to continue to monitor the situation.
Residents use M-pesa services at a local kiosk in Kibera slum, Nairobi, Kenya
3. How do these impacts influence groups in vulnerable situations, such as women, youth, and migrants?
A key lesson from centuries of technological change is that there are both winners and losers as economies and labour markets adjust. ILO research has shown that women are more susceptible to the automation effects of AI due to their overrepresentation in occupations that are most exposed, such as administrative jobs. Recent data on actual labour market trends (as opposed to potential effects) is telling us that we should be worried about how generative AI is impacting young people – evidence is emerging to suggest that there is a more negative effect of AI on young labour market entrants in such countries as the US. At the same time, there are range of use cases that can help certain groups access new learning and employment opportunities. For example, under the PROSPECTS programme, the ILO is supporting young people in remote areas of Kenya through digital skills training and mentoring programmes to access online job opportunities.
4. While we talk about the quantity of jobs impacted by AI, what would you say about the quality of jobs impacted?
As already mentioned, we need to focus on not only implications of AI for job quantity but quality as well, which is where the largest effects are likely to emerge. AI impacts tasks and won’t eliminate most jobs entirely. But these changes can lead to effects on wages, depending on how demand for the occupation shifts, and working conditions due to the impact of AI in the workplace.
We already see the use of algorithmic management tools, which are getting supercharged by AI, for recruitment, allocating tasks, monitoring and evaluating workers. While this has the potential to improve productivity, it poses challenges in terms of workers’ agency and the nature of their jobs. Key is transparency on the use of these tools, matched by dialogue to ensure that new technologies can be beneficial to both the enterprise and their workers.
5. There’s often a regional divide in how AI is deployed and its benefits are distributed. How can we bridge that gap—both nationally and globally?
A digital divide exists both within and between countries due to differences in access to digital infrastructure and skills. The share of the population using the Internet in 2024 reached 93 per cent in high-income countries compared with just 27 per cent of the population in low-income economies. Even in advanced economies, such as in the European Union, access to AI is uneven with higher rates of adoption in richer countries and larger firms. Within countries, access to broadband (optic fibre) Internet and training programmes is more limited in rural areas. In response, greater investments are needed in infrastructure and skilling to ensure that these gaps are reduced. Support is also needed to ensure that there are opportunities for developing economies to build their own AI ecosystems in terms of both development and deployment of new technologies in different languages and adapted to country-specific contexts.
The share of the population using the Internet in 2024 reached 93 per cent in high-income countries compared with just 27 per cent of the population in low-income economies.
6. What kind of policy frameworks do we need to ensure that AI benefits all workers?
From an ILO perspective, the Decent Work Agenda remains key for assessing both the benefits and challenges arising from the development and deployment of AI. In practice, responding to the opportunities and challenges posed by AI will involve applying existing policies and regulations, while adapting and developing new strategies and governance frameworks where needed, in line with international labour standards and through social dialogue (e.g., to address the platform economy).
There are three areas we need to look at: first, address the negative impact of AI through redeployment, social protection and active labour market policies (e.g., employment services); second, enhance digital skilling and upskilling to support access to new technologies, along with measures to assist small businesses to overcome the digital divide and take advantage of opportunities; and third, strengthen governance mechanisms to ensure rights are protected in the workplace (e.g., safeguarding against discriminatory algorithms).
7. If you could deliver just one message to global policymakers about AI and employment, what would it be?
AI is creating both new opportunities and challenges in the world of work and to ensure that the benefits are broadly shared, we need to assess the impact of AI on both the quality and quantity of jobs, and respond through employment policies and other measures, backed by the latest evidence and social dialogue.
Prepared by Paolo Alberto Baudino, Oscar Schwartz Blicke and Maurizio Michael Habib
Published as part of the Financial Stability Review, November 2025.
Hedge funds represent a relatively small segment of the euro area investment fund sector and comprise both AIF and UCITS hedge funds. The total assets of euro area hedge funds stood at around €660 billion in the third quarter of 2025, equivalent to roughly 3% of the investment fund sector’s total assets. In the EU, hedge funds may fall either under the Alternative Investment Fund Managers Directive (AIFMD)[1] or the Undertakings for Collective Investment in Transferable Securities (UCITS) Directive.[2] AIF hedge funds are usually marketed to wealthy investors and are predominantly held by euro area investment funds. They offer limited liquidity, by allowing redemptions only quarterly or even annually (often with advance notice), for example, and by imposing lock-up periods on initial investments. By contrast, UCITS hedge funds are more accessible to retail investors and other non-bank sectors – with euro area households and insurance corporations each holding around 15% of the shares in such funds. As these funds often allow investors to redeem shares on a high-frequency basis, the sector is more exposed to fund share redemptions during market turmoil. UCITS hedge funds account for about 30% of the overall hedge fund sector in terms of shares issued (Chart A, panel a) as well as total assets.
Chart A
UCITS hedge funds exhibit higher retail participation and use derivatives more intensively than do AIF hedge funds
a) Investor base and shares issued by euro area hedge funds, by fund type
b) Euro area hedge funds’ financial leverage and gross derivatives exposure, by fund type
c) Gross derivatives exposures of euro area UCITS hedge funds and derivative type distribution
(Q3 2025; percentages, € billions)
(Q3 2025; total assets divided by shares issued, derivative gross notional divided by shares issued)
(Q3 2025, derivative gross notional divided by shares issued)
Sources: ECB (EMIR, IVF, SHS), Morningstar Direct[3] and ECB calculations. Notes: the sample of euro area UCITS and AIF hedge funds is derived from the ECB’s investment fund list classification. AIF stands for alternative investment fund. Panel a: the investor base is proxied by information available for traded securities. The latest available information on the investor base refers to Q2 2025. For a discussion of different measures of leverage for hedge funds, see the article entitled “Leveraged investment funds: A framework for assessing risks and designing policies”, Macroprudential Bulletin, Issue 26, ECB, 2025. Panel c: hedge fund strategies follow the Morningstar Direct classification. HFs stands for hedge funds.
As UCITS hedge funds have relatively high derivatives exposure and leverage, they warrant attention from a financial stability perspective. Both UCITS and AIF hedge funds employ a wide range of investment strategies, including leveraged trades, to achieve positive absolute returns. Because of regulatory constraints on borrowings,[4] UCITS hedge funds make less use of financial leverage than AIF hedge funds do, with a total assets/equity ratio of 1.3 for UCITS hedge funds versus 1.7 for AIF hedge funds. However, synthetic leverage through derivatives is more pronounced in UCITS hedge funds, with gross notional derivatives exposure reaching up to 12 times equity for fund categories such as global macro strategies (Chart A, panels b and c).[5] In addition, UCITS hedge funds hold a lower proportion of highly liquid assets (e.g. cash and sovereign bonds) than AIF hedge funds do.[6] This leaves them more vulnerable to liquidity risk from redemption shocks or margin calls. Although some research has been carried out on the performance of UCITS hedge funds, this box sheds light on their liquidity and leverage-related risks, given their importance for financial stability.[7]
Procyclical flows and larger redemptions from leveraged funds in times of stress can lead to asset sales and mounting liquidity pressures during periods of high market volatility. Evidence from a panel of 457 UCITS hedge funds shows that their flows are procyclical, positively correlated with past returns (Chart B, panel a) and in line with the findings for other fund categories.[8] Although the analysis does not indicate that leverage generally amplifies the flow procyclicality of UCITS hedge funds, it does show larger outflows from leveraged UCITS hedge funds in periods of market stress (Chart B, panel b). Since fund share redemptions may force funds to sell assets when markets are under pressure, leveraged funds could be required to close larger positions, thereby amplifying stress.
The use of derivatives by UCITS hedge funds can intensify liquidity pressures via margin calls. Derivatives positions, which can be used for hedging or for leverage, are subject to margin requirements. During periods of elevated price volatility and significantly negative returns, margin calls on these derivatives positions tend to increase (Chart B, panel c), further straining a fund’s liquidity.[9] This exacerbates the challenges faced by leveraged UCITS hedge funds, as they have to manage liquidity to meet both margin calls and redemption requests simultaneously. Interaction between these factors can heighten liquidity strains and contribute to broader market stress underadverse market conditions.[10]
Chart B
Flows into UCITS hedge funds tend to be procyclical, while margin calls may intensify liquidity risk
a) Average fund-level flows into euro area UCITS hedge funds, by lagged return level
b) Average fund-level flows into euro area UCITS hedge funds, by synthetic gross leverage level
c) Average fund-level daily posted variation margin of euro area UCITS hedge funds, by negative return level
(Jan. 2019-Oct. 2025; standardised values, log of derivative gross notional as a percentage of TNA)
(Jan. 2020-Oct. 2025; percentages of TNA, percentages)
Sources: ECB (EMIR), EPFR Global, Morningstar Direct[11] and ECB calculations. Notes: Panel a: the sample is based on funds that have been classified as UCITS hedge funds in the ECB’s investment fund list since 2009, to limit survivorship bias. The analysis is restricted to funds pursuing major hedge fund-like strategies, as classified by Morningstar Direct, and which have substantial representation in the sample. These strategies include global macro, systematic trend, options trading, market neutral and long/short strategies. Fund-level returns are calculated by aggregating the returns for each fund’s share classes, weighted by the total net assets (TNA) of each share class. Fund-level flows and TNA are obtained by aggregating the corresponding values across all the share classes within each fund. Flows are expressed as percentages of TNA and standardised to remove trends from the data. Panel b: stress episodes are defined as months in which the VIX exceeds the 90th percentile of our sample. Synthetic leverage is proxied by the gross notional value of derivatives excluding interest rate and FX contracts, which are extensively used for hedging, as a share of fund-level TNA. Panel c: average posted variation margin (VM) is calculated as the mean of fund-level daily margin amounts posted as percentages of fund TNA.
A robust stress-testing framework for leveraged UCITS hedge funds is essential to ensure their resilience and limit the risks to financial stability in turbulent market conditions. The combination of outflows and margin calls on derivatives positions can intensify liquidity pressures for UCITS hedge funds during periods of stress. This raises concerns about the ability of such funds to manage the challenges and contributes to broader financial instability. These dynamics highlight the need for strengthened risk management and comprehensive stress-testing practices to safeguard financial stability during episodes of market turmoil.
Finally, authorities should be equipped with suitable tools to limit excessive leverage in UCITS hedge funds and mitigate the build-up of risks during periods of market stress. While authorities have tools that enable them to contain excessive leverage in AIFMD-compliant funds, they do not have such tools for UCITS hedgefunds. The Eurosystem suggests introducing discretionary powers that would allow authorities to impose stricter leverage limits on these funds when they pose risks to financial stability.[12] It also recommends that all UCITS hedge funds should be required to report their leverage using the commitment approach.
