We collected data on almost the complete population of the merger control decisions by the Directorate-General Competition’s (DG COMP) of the European Commission. We started the data collection with the first year of common European merger control, 1990, and included all years up to 2014. This amounts to 25 years of data on European merger control. With regard to the scope of the decisions, we collected data in all cases where a legal decision document exists. This includes all cases settled in the first phase of an investigation (Art. 6(1)(a), 6(1)(b), 6(1)(c) and 6(2)) and all cases decided in the second phase of an investigation (Art. 8(1), 8(2), and 8(3)). Note that this also includes all cases settled under a ‘simplified procedure’, provided that a legal decision document exists. Furthermore, we also intended to collect data on cases that were either referred back to member states by DG COMP or aborted by the merging parties. While we have collected some data on such cases, data on these cases is not always available. Therefore, we cannot guarantee that the final dataset covers all of these cases. The level of observation is not a particular merger case but a particular product/geographic market combination concerned by a merger. In total, the final dataset contains 5,196 DG COMP merger decisions. For each of this decision, we record a number of observations equal to the number of product/geographic markets identified in the specific transaction. Hence, the total dataset contains 31,451 observations.

Search LSEG's Mergers and Acquisitions (M&A) Data, and find individual deal details, comprehensive market analysis, and league table rankings.

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

Intellizence is an AI platform focused on monitoring growth & sales, risk & distress signals in companies. Intellizence signals help customers to identify new business opportunities & risks as well as make timely strategic & tactical decisions.

Intellizence discovers Merger & Acquisition (M&A) deals from various public sources, de-duplicates, extracts deal details, resolves correct entities, enriches with firmographic details, ensures quality, and delivers through an API. The data is refreshed daily.

Intellizence M&A data is useful for: Monitoring Merger & Acquisition deal trends Getting intelligence about Merger & Acquisition events in customers, competitors, prospects, etc.,

Intellizence API is designed for product and data teams.

Stop searching for the M&A deals data. Power your technology platforms and models with the real-time, curated Merger & Acquisition deals data.

Save time, money & effort with one bold integration.

This data set includes information on all public merger enforcement actions brought by the Federal Trade Commission from fiscal year 1996 to fiscal year 2019. The data set contains descriptive information on the characteristics of each matter as well as URLs to the individual case pages that are published on the FTC's website and that contain public documents pertaining to each case.

In 2024, approximately ****** merger and acquisition (M&A) deals were completed worldwide. This figure is in line with those registered recently, despite representing a decrease compared to the previous years. PwC., Deloitte, and JPMorgan advised on the largest number of M&A deals in 2023. How has the value of M&A deals varied over the years? The value of M&A deals worldwide fluctuated significantly recently. A peak value of over *** trillion U.S. dollars was recorded in 2021. So-called mega-deals - M&A deals worth *** billion U.S. dollars or more - have a great influence on the market performance: In 2023, nearly 400 megadeals were worth a combined *** billion U.S. dollars. How did the world’s leading financial advisor perform? In 2023, Goldman Sachs was the leading M&A financial advisor in terms of the value of M&A deals, while PwC was leading in terms of the number of deals. While Goldman Sachs dominated the M&A scene in terms of deal value, J.P. Morgan surpassed them as the world’s leading bank in terms of revenue from investment banking in 2024.

The Database on Mergers in Europe (DOME) has been compiled at the Kiel Institute of World Economics, in order to improve the availability of data on mergers in Europe. This public domain database is set up to improve the data source for empirical research on mergers in Europe. It is based on the merger cases, which have been under examination by the European Commission since 1990. Its current version consists of 1,515 cases notified until December 31st, 2000. The information in the database includes the date of the announcement of the merger, the name, the country and the sector of the acquiring company, the target and the selling company as well as the transaction value (if disclosed). A classification is given with respect to majority ownership, joint venture, and minority ownership. Furthermore, some additional information for majority ownerships is included: capital profitability and employment growth relative to the sectoral average before and after the merger. Some notes are also given like methods of payment (share, cash), the further development after the merger (later merged with other company, later sold to other company), and possible reasons for the transaction (privatization, bankruptcy, takeover of an earlier joint venture). The sample population of DOME corresponds to the cases examined by the European Commission. This limits the generality of results from studies using DOME as the sample is biased towards large companies due to the criteria of the European Commission. However, mergers of large companies are most controversially discussed with regards to their impact on the whole economy. Furthermore, cross-border cases are over-represented in DOME. Please cite the database as follows: Kiel Institute for World Economics (2004). DOME: Database on Mergers in Europe.

Many experts speculate that US antitrust policy towards horizontal mergers has been too lenient. We estimate the price effects of Whirlpool's acquisition of Maytag to provide new evidence on this debate. We compare price changes in appliance markets most affected by the merger to markets where concentration changed much less or not at all. We estimate price increases for dishwashers and relatively large price increases for clothes dryers, but no price effects for refrigerators or clothes washers. The combined firm's market share fell across all four affected categories, and the number of distinct appliance products offered for sale fell. (JEL G34, K21, L11, L41, L68)

Detailed data on credit union merger activity over the last 3 years from the most recent quarter-end.

The value of M&As in South America grew considerably in recent years, peaking at nearly one trillion U.S. dollars in 2021. In 2024, M&A deal value in the region decreased by 20 percent compared to the previous year and amounted to 395 billion U.S. dollars.

DATA MINING THE GALAXY ZOO MERGERS STEVEN BAEHR*, ARUN VEDACHALAM*, KIRK BORNE*, AND DANIEL SPONSELLER* Abstract. Collisions between pairs of galaxies usually end in the coalescence (merger) of the two galaxies. Collisions and mergers are rare phenomena, yet they may signal the ultimate fate of most galaxies, including our own Milky Way. With the onset of massive collection of astronomical data, a computerized and automated method will be necessary for identifying those colliding galaxies worthy of more detailed study. This project researches methods to accomplish that goal. Astronomical data from the Sloan Digital Sky Survey (SDSS) and human-provided classifications on merger status from the Galaxy Zoo project are combined and processed with machine learning algorithms. The goal is to determine indicators of merger status based solely on discovering those automated pipeline-generated attributes in the astronomical database that correlate most strongly with the patterns identified through visual inspection by the Galaxy Zoo volunteers. In the end, we aim to provide a new and improved automated procedure for classification of collisions and mergers in future petascale astronomical sky surveys. Both information gain analysis (via the C4.5 decision tree algorithm) and cluster analysis (via the Davies-Bouldin Index) are explored as techniques for finding the strongest correlations between human-identified patterns and existing database attributes. Galaxy attributes measured in the SDSS green waveband images are found to represent the most influential of the attributes for correct classification of collisions and mergers. Only a nominal information gain is noted in this research, however, there is a clear indication of which attributes contribute so that a direction for further study is apparent.

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 is a repository for the code to replicate "Is There Too Little Antitrust Enforcement in the US Hospital Sector?" as published in American Economic Review: Insights.The abstract of the paper is:From 2002 to 2020, there were over 1,000 mergers of US hospitals. During this period, the Federal Trade Commission (FTC) took enforcement actions against 13 transactions. However, we find that 20% of these mergers could have been predicted, using the FTC's standard screening tools, to meaningfully lessen competition. We then show that, from 2010 to 2015, predictably anticompetitive mergers resulted in price increases over 5%. We estimate that approximately half of predictably anticompetitive mergers had to be reported to the FTC per the Hart-Scott-Rodino Act. We conclude that there appears to be underenforcement of antitrust laws in the hospital sector.

Argentina Foreign Direct Investment: Merger & Acquisitions data was reported at 3.501 USD mn in Sep 2024. This records a decrease from the previous number of 57.627 USD mn for Jun 2024. Argentina Foreign Direct Investment: Merger & Acquisitions data is updated quarterly, averaging 0.545 USD mn from Mar 2017 (Median) to Sep 2024, with 31 observations. The data reached an all-time high of 341.523 USD mn in Mar 2024 and a record low of -611.263 USD mn in Jun 2019. Argentina Foreign Direct Investment: Merger & Acquisitions data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.O001: Foreign Direct Investment: New Methodology.

This is a database containing all the HFR atomic data needed to compute the opacity of all neutral to trebly-ionized elements between Ca (Z=20) and Lr (Z=103) in the context of kilonova emission following neutron star mergers, as well as expansion and line-binned opacity tables for a grid of conditions, namely a time t = 1, 2, 3, 4, 5, 6, 7 days after the merger ; an ejecta density \rho = 1E-17, 1E-16, 1E-15, 1E-14, 1E-13 g/cm^3 ; and an ejecta temperature T = 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000 K. A table of Planck mean expansion opacities for all the elements is also provided for this grid of conditions.

The details of the computations can be found in our paper: Deprince J. et al., "Kilonova ejecta opacity inferred from new large-scale HFR atomic calculations in all elements between Ca (Z=20) and Lr (Z=103)", in press (Astronomy & Astrophysics, 2025); arXiv:2412.16688 [astro-ph.HE]. The present data have been obtained in tight collaboration between the University of Mons (UMONS) and the University of Brussels (ULB), in Belgium.

Note that the present version (v2) replaces version 1 (v1) that is obsolete. In this new version, we have corrected an error in the previous data for Pb (Z=82).

Description of the files:

1) Atomic data:

• atomic-data-lanthanides includes the atomic data for all lanthanides ;
• atomic-data-actinides includes the atomic data for all actinides ;
• atomic-data-other includes the atomic data for all other elements from Z=20.

All the three compressed files include two types of files, namely outglv and outggf files:

• outglv files: energy level lists. The first column gives the value of the energy level E_i (in 1000 cm^{-1}), and the second columns indicates the corresponding value of the total angular momentum J_i ;
• outggf files: transition lists. The three columns gives, for each line, the transition wavelengths (in A), the energy of the transition lower level E_i (in 1000 cm^{-1}), and the corresponding oscillator strength, gf.

2) Opacity tables :

• exp-opacity-table contains, for each element, the expansion opacity as a function of the wavelength for the above-mentionned grid of conditions. The first column gives the wavelength at which the opacity is computed, and the following ones correspond to the expansion opacities for the conditions (t,\rho,T) mentioned in the first three rows ;
• lb-opacity-table contains, for each element, the line-binned opacity as a function of the wavelength for the above-mentionned grid of conditions. The first column gives the wavelength at which the opacity is computed, and the following ones correspond to the line-binned opacities for the conditions (t,\rho,T) mentioned in the first three rows ;
• table_planck_opacity.txt is a table of Planck mean expansion opacities of all element for the above-mentionned grid of conditions. Each line gives, for a given element labeled by its atomic number Z in the first column, the Planck mean opacities for the conditions indicated in the first three rows.

We analyze a large merger in the Swedish market for analgesics (painkillers). The merging firms raised prices by 40 percent, and some outsiders raised prices by more than 10 percent. We confront these changes with predictions from a merger simulation model. With basic supply side assumptions, the models correctly or moderately underpredict the merging firms' price increase. However, they predict a larger price increase for the smaller firm, which was not the case in practice, and they underpredict the outsiders' responses. We consider several supply side explanations: a plausible cost increase after the merger and the possibility of partial collusion.

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

Horizontal mergers have a large impact by inducing a long-lasting change in market structure. Only in an industry with substantial entry barriers is a merger not immediately counteracted by post-merger entry. To evaluate the duration of the effects of a merger, I use the model of Abbring and Campbell (2010) to estimate demand thresholds for entry and for exit. These thresholds, along with the process for demand, are estimated using data from the ready-mix concrete industry. Simulations predict that a merger from duopoly to monopoly generates between 9 and 10 years of monopoly in the market.

The main objective of this research paper is to analyse the market growth of ecommerce which attracts the merger and acquisition in India. Through this paper we willtry to find out reasons of merger and acquisition from the experience of Indian ecommerce sector. Internet growth has led to a host of new developments, such asdecreased margins for companies as consumers turn more and more to the internet tobuy goods and demand the best prices .The industry is growing rapidly and there is still ahuge potential for growth