Quarterly data on the value and number of mergers, acquisitions and disposals involving UK companies with values of £1 million or more.

The Mergers and Acquisitions Survey presents information and data on the timing, value, number and methods of funding of Mergers and Acquisitions transactions involving UK businesses with deal values of £1 million and above.

The Mergers and Acquisitions Survey consists of three categories of investment:

• inward investment (acquisitions of UK companies by foreign companies);
• outward investment (UK companies acquisitions of foreign companies);
• domestic Mergers and Acquisitions (acquisitions of UK companies by other UK companies).
  

The sampling source for the Mergers and Acquisitions Survey was changed in January 2018; Bureau Van Dijk's Zephyr database is now used as the starting point for deal identification.

Linking to other business studies
These data contain Inter-Departmental Business Register (IDBR) reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

Limited metadata is available about this study but further information about how the data are used, and the latest publications, are available on the ONS Mergers and Acquisitions webpages.

Latest edition information
For the second edition (August 2023), annual inward, outward and domestic 2021 data files have been added to the study. The variable list for 2021 has also been added.

For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This database was created to accompany a report prepared by Joe Daniels, PhD, and Martine August, PhD, entitled “Acquisitions Programs for Affordable Housing: Creating non-market supply and preserving affordability with existing multi-family housing.” The database and report form part of the work performed under the HART project, and the report can be found at HART’s website: HART.ubc.ca. The database is a single table that summarizes 11 key elements, plus notes and references, of a growing list of policies from governments across the world. There are currently 108 policies included in the database. The authors expect to update this database with additional policies from time to time. The authors hope this database will serve as a resource for governments looking to become familiar with a variety of policies in order to help them evaluate what policies might be most applicable in their communities. Data Fields: List of data fields (15 total): 1. Government Order 2. Government Jurisdiction 3. Policy Name/Action 4. Acquisition Target 5. Years Active 6. Funder/Funding 7. Funding Amount (Program) 8. Funding Form 9. Affordability Standard 10. Affordability Term 11. Features/Requirements 12. Comments 13. Reference link 1 14. Reference link 2 15. Reference link 3 Description of data fields (15) 1. Government Order: - Categorizes the relative political authority in terms of one of three categories: Municipal (responsible for a city or small region), Provincial (responsible for multiple municipalities), or Country (responsible for multiple provinces; highest political authority). - This field may be used to help identify those policies most relevant to the reader. 2. Government Jurisdiction: - Indicates the name of the government. - For example, a country might be named “Canada,” a province might be named “Quebec,” and a municipality might be named “Calgary.” 3. Policy Name/Action: - Indicates the name of the policy. - This generally serves as the unique identifier for the record. However, there may be some programs that are only known by a common term; for example, “Right of First Refusal.” 4. Acquisition Target: - Describes the type of housing asset that the policy is concerned with. For example, acquiring land, acquiring existing rental buildings, renovating existing supportive housing. 5. Years Active: - The time period that the policy has been active. - Typically formatted as “[Year started] - [Year ended]”. If just a single year is listed (e.g. “2009”) that means the policy was only active that one year. - If the policy is active with no end date, then the format will be “[Year started] - ongoing.” If the policy has a specified end date in the future, that year will be listed instead: “[Year started] – [Expected final year].” 6. Funder/Funding: - The government, government agency, or organization responsible for the use of those funds made available through the policy. 7. Funding Amount (Program): - The dollar value of funds connected to the policy. - Sometimes this is the total value of funds available to the policy, and sometimes it is the actual value of funds that were used. - The funds indicated here do not necessarily correspond to the time period indicated in the ‘Years Active’ field. Additional detail will be added to clarify whenever possible. - If policy has “N/A” listed here, see ‘Features/Requirements’ for more information. 8. Funding Form: - Indicates the type of financial tools available to the policy. For example, “capital funding,” “forgivable loans,” or “rent supplements.” - If policy has “N/A” listed here, see ‘Features/Requirements’ for more information. 9. Affordability Standard: - Indicates whether the policy includes an explicit standard or benchmark of affordability that is used to guide or otherwise inform the policy’s goals. 10. Affordability Term: - Indicates whether the affordability standard applies to a specific time period. - This field may also contain other information on time periods that are relevant to the policy; for example, an operating loan guaranteed to be active for a specific number of years. 11. Features/Requirements: - Describes the broad objectives of the policy as well as any specific guidelines that the policy must follow. 12. Comments: - Author’s commentary on the policy. 13. Reference link 1: - A web address (URL) or citation indicating the source of the details on the policy. 14. Reference link 2: - A second web address (URL) or citation indicating the source of the details on the policy. 15. Reference link 3: - A third web address (URL) or citation indicating the source of the details on the policy. File list (1): 1. Property Acquisition Policy Database.xlsx

The number of M&A deals in South America increased significantly in the last decade, peaking at 2,500 in 2021. In 2024, however, the number of transactions in the region decreased to around 1,300.

This dataset contains raw, unprocessed data files pertaining to the management activity 'Mergers and Acquisitions' (M&A). The data originates from five distinct sources, each reflecting different facets of the activity's prominence and usage over time. Files preserve the original metrics and temporal granularity before any comparative normalization or harmonization. Data Sources & File Details: Google Trends File (Prefix: GT_): Metric: Relative Search Interest (RSI) Index (0-100 scale). Keywords Used: "mergers and acquisitions" + "mergers and acquisitions corporate" Time Period: January 2004 - January 2025 (Native Monthly Resolution). Scope: Global Web Search, broad categorization. Extraction Date: Data extracted January 2025. Notes: Index relative to peak interest within the period for these terms. Reflects public/professional search interest trends. Based on probabilistic sampling. Source URL: Google Trends Query Google Books Ngram Viewer File (Prefix: GB_): Metric: Annual Relative Frequency (% of total n-grams in the corpus). Keywords Used: Mergers and Acquisitions + Mergers & Acquisitions Time Period: 1950 - 2022 (Annual Resolution). Corpus: English. Parameters: Case Insensitive OFF, Smoothing 0. Extraction Date: Data extracted January 2025. Notes: Reflects term usage frequency in Google's digitized book corpus. Subject to corpus limitations (English bias, coverage). Source URL: Ngram Viewer Query Crossref.org File (Prefix: CR_): Metric: Absolute count of publications per month matching keywords. Keywords Used: ("mergers and acquisitions" OR "mergers & acquisitions") AND ("corporate" OR "strategy" OR "finance" OR "management" OR "deal" OR "implementation" OR "valuation") Time Period: 1950 - 2025 (Queried for monthly counts based on publication date metadata). Search Fields: Title, Abstract. Extraction Date: Data extracted January 2025. Notes: Reflects volume of relevant academic publications indexed by Crossref. Deduplicated using DOIs; records without DOIs omitted. Source URL: Crossref Search Query Bain & Co. Survey - Usability File (Prefix: BU_): Metric: Original Percentage (%) of executives reporting tool usage. Tool Names/Years Included: Mergers and Acquisitions (2006, 2008, 2010, 2012, 2014, 2017). (Note: Some sources list this as Mergers & Acquisitions). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., et al., various years: 2007, 2009, 2011, 2013, 2015, 2017). Note: Tool potentially not surveyed or reported before 2006 or after 2017 under this specific name. Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268. Bain & Co. Survey - Satisfaction File (Prefix: BS_): Metric: Original Average Satisfaction Score (Scale 0-5). Tool Names/Years Included: Mergers and Acquisitions (2006, 2008, 2010, 2012, 2014, 2017). (Note: Some sources list this as Mergers & Acquisitions). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., et al., various years: 2007, 2009, 2011, 2013, 2015, 2017). Note: Tool potentially not surveyed or reported before 2006 or after 2017 under this specific name. Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268. Reflects subjective executive perception of utility. File Naming Convention: Files generally follow the pattern: PREFIX_Tool.csv, where the PREFIX indicates the data source: GT_: Google Trends GB_: Google Books Ngram CR_: Crossref.org (Count Data for this Raw Dataset) BU_: Bain & Company Survey (Usability) BS_: Bain & Company Survey (Satisfaction) The essential identification comes from the PREFIX and the Tool Name segment. This dataset resides within the 'Management Tool Source Data (Raw Extracts)' Dataverse.

Stay updated with the latest Database Encryption Market News. Get insights on recent mergers, acquisitions, and key industry developments.

The Report Covers Global Data Acquisition (DAQ) System Market Analysis and is segmented by Channel (Less Than 32, 32-128, Greater Than 128), Type (Hardware, Software), End-User Vertical (Water and Waste Treatment, Power & Energy, Automotive, Education and Research, Aerospace & Defense, Paper and Pulp, Chemicals and Other End-Users), and Geography

United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: USA data was reported at 84.000 Unit in 2017. This records a decrease from the previous number of 89.000 Unit for 2016. United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: USA data is updated yearly, averaging 65.500 Unit from Dec 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 152.000 Unit in 1998 and a record low of 18.000 Unit in 1986. United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: USA data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.O037: Mergers and Acquisitions: Cross Border Activity (Annual).

The H.2A release lists all applications and notices that have been filed or will be filed shortly with the Federal Reserve System under the Bank Holding Company Act, the Change in Bank Control Act, the Home Owners' Loan Act or Regulations Y, LL, MM for which a notice has been sent to the Federal Register. The H.2A briefly describes the proposal, identifies the Reserve Bank that is processing the proposal, and lists the date for the expiration of the Federal Register comment period. Attached to the H.2 release.

MU: Foreign Co: Value: Direct: Paid By Foreign Co data was reported at 31,567.000 GBP mn in 2017. This records a decrease from the previous number of 184,656.000 GBP mn for 2016. MU: Foreign Co: Value: Direct: Paid By Foreign Co data is updated yearly, averaging 11,678.000 GBP mn from Dec 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 184,656.000 GBP mn in 2016 and a record low of 1,077.000 GBP mn in 1986. MU: Foreign Co: Value: Direct: Paid By Foreign Co data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s UK – Table UK.O035: Mergers and Acquisitions: By Source of Funding (Annual).

This dataset provides processed and normalized/standardized indices for the management activity 'Mergers and Acquisitions' (M&A). Derived from five distinct raw data sources, these indices are specifically designed for comparative longitudinal analysis, enabling the examination of trends and relationships across different empirical domains (web search, literature, academic publishing, and executive adoption). The data presented here represent transformed versions of the original source data, aimed at achieving metric comparability. Users requiring the unprocessed source data should consult the corresponding M&A dataset in the Management Tool Source Data (Raw Extracts) Dataverse. Data Files and Processing Methodologies: Google Trends File (Prefix: GT_): Normalized Relative Search Interest (RSI) Input Data: Native monthly RSI values from Google Trends (Jan 2004 - Jan 2025) for the query "mergers and acquisitions" + "mergers and acquisitions corporate". Processing: None. Utilizes the original base-100 normalized Google Trends index. Output Metric: Monthly Normalized RSI (Base 100). Frequency: Monthly. Google Books Ngram Viewer File (Prefix: GB_): Normalized Relative Frequency Input Data: Annual relative frequency values from Google Books Ngram Viewer (1950-2022, English corpus, no smoothing) for the query Mergers and Acquisitions + Mergers & Acquisitions. Processing: Annual relative frequency series normalized (peak year = 100). Output Metric: Annual Normalized Relative Frequency Index (Base 100). Frequency: Annual. Crossref.org File (Prefix: CR_): Normalized Relative Publication Share Index Input Data: Absolute monthly publication counts matching M&A-related keywords [("mergers and acquisitions" OR ...) AND (...) - see raw data for full query] in titles/abstracts (1950-2025), alongside total monthly Crossref publications. Deduplicated via DOIs. Processing: Monthly relative share calculated (M&A Count / Total Count). Monthly relative share series normalized (peak month's share = 100). Output Metric: Monthly Normalized Relative Publication Share Index (Base 100). Frequency: Monthly. Bain & Co. Survey - Usability File (Prefix: BU_): Normalized Usability Index Input Data: Original usability percentages (%) from Bain surveys for specific years: Mergers and Acquisitions (2006, 2008, 2010, 2012, 2014, 2017). Note: Not reported before 2006 or after 2017. Processing: Normalization: Original usability percentages normalized relative to its historical peak (Max % = 100). Output Metric: Biennial Estimated Normalized Usability Index (Base 100 relative to historical peak). Frequency: Biennial (Approx.). Bain & Co. Survey - Satisfaction File (Prefix: BS_): Standardized Satisfaction Index Input Data: Original average satisfaction scores (1-5 scale) from Bain surveys for specific years: Mergers and Acquisitions (2006-2017). Note: Not reported before 2006 or after 2017. Processing: Standardization (Z-scores): Using Z = (X - 3.0) / 0.891609. Index Scale Transformation: Index = 50 + (Z * 22). Output Metric: Biennial Standardized Satisfaction Index (Center=50, Range?[1,100]). Frequency: Biennial (Approx.). File Naming Convention: Files generally follow the pattern: PREFIX_Tool_Processed.csv or similar, where the PREFIX indicates the data source (GT_, GB_, CR_, BU_, BS_). Consult the parent Dataverse description (Management Tool Comparative Indices) for general context and the methodological disclaimer. For original extraction details (specific keywords, URLs, etc.), refer to the corresponding M&A dataset in the Raw Extracts Dataverse. Comprehensive project documentation provides full details on all processing steps.

ACQ_DSP_POLY: This dataset is used for depicting Acquisitions and Disposals on maps. The history of acquisition and disposals within a BLM administrative unit or special management area is often of interest. The dataset includes both existing and proposed acquisitions and disposals. Acquisitions and disposals are intersected with natural resources and special management areas to determine impact and/or feasibility of the proposed action. This dataset is not complete for all Acquisitions and Disposals on BLM lands and, in addition, only basic information about the acquisition or disposal is provided. Details of the complete rights and restrictions history are found in the following authoritative sources: case file records, Master Title Plats (MTPs), and the Legacy Rehost 2000 (LR2000) database. The case file record is the primary source, with MTPs and LR2000 as secondary sources. Moreover, this dataset will never be complete. Over time, more and more approved ACQ_DSP features will be added to the dataset, but it will never contain the complete record (found in the case files).

StarMine Mergers and Acquisition Target Model measures the likelihood of a company being acquired by analyzing textual and fundamental content.

The database contains information on mergers and acquisitions of Chinese companies worldwide for the period 2011-2017, categorized by industry. The data is extracted from Zephyr, a cross-border M&A database from BVD and is anonymized

GlobalData's “Quarterly Midstream Deals Review – Q2 2020” report is an essential source of data and trend analysis on M&A (mergers, acquisitions, and asset transactions), in the midstream oil and gas industry. The report provides detailed comparative quarter-on-quarter data, on the number of deals and their value, sub-divided into deal types by geographies. Data presented in this report is derived from GlobalData’s proprietary in-house Oil and Gas eTrack deals database and primary and secondary research. Read More

United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: Other Europe data was reported at 21.000 Unit in 2017. This records a decrease from the previous number of 23.000 Unit for 2016. United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: Other Europe data is updated yearly, averaging 0.000 Unit from Dec 1987 (Median) to 2017, with 31 observations. The data reached an all-time high of 40.000 Unit in 2008 and a record low of 0.000 Unit in 2004. United Kingdom Mergers & Acquisitions: Foreign Co: Number of Transaction: Other Europe data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.O037: Mergers and Acquisitions: Cross Border Activity (Annual).

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Databento provides upcoming and historical corporate actions impacting over 310,000 global securities, including every company announcement and 61 events like dividends, splits, mergers & acquisitions, listings, and more.

Dividends: Upcoming and past dividends, declaration, ex-dividend, record, and payment dates.

Forward and reverse splits: Capital changes like forward splits and reverse splits with effective dates.

Adjustment factors: To back-adjust end-of-day prices, EPS, P/E and other prices for all corporate actions.

Mergers and acquisitions: Ticker changes caused by mergers, acquisitions, demergers, spinoffs, and more.

IPOs and new listings: Upcoming and historical listings like initial public offerings (IPOs), with listing dates.

Listing continuity: Listing continuity events like name changes, delistings, and description changes.

Capital changes: Such as share buybacks, redemptions, bonus issues, and rights issues.

Legal actions: Legal issues like bankruptcy and class action lawsuits, with filing and notice dates.

Announcements: Machine-readable announcements from over 400 sources, timestamped to the second.

Our reference API has the following structure:

Corporate actions provides point-in-time (PIT) corporate actions events with global coverage.

Adjustment factors provides end-of-day price adjustment factors for capital events, spanning multiple currencies for the same event.

The size and share of this market is categorized based on Application (Universal, Temperature, Voltage, Torque, Speed) and Product (Multi-Channel, 16-channel, 32-channel, 56-channel, Others) and geographical regions (North America, Europe, Asia-Pacific, South America, Middle-East and Africa).