Semi-analytic models are best suited to compare galaxy formation and evolution theories with observations. These models rely heavily on halo merger trees, and their realistic features (i.e., no drastic changes on halo mass or jumps on physical locations). Our aim is to provide a new framework for halo merger tree gener…
On-device research index
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
168,695 papers · 148 categories
Trend · papers per month
40 results for “mergers”
Company mergers and acquisitions are often perceived to act as catalysts for corporate growth in free markets systems: it is conventional wisdom that those activities lead to better and more efficient markets. However, the broad adoption of this perception into corporate strategy is prone to result in a less diverse an…
Study examines market reactions and spillovers in Japanese bank mergers using multiple methods.
problem Understanding valuation and spillover effects of bank mergers in the Japanese banking sector.
method Combines event study, VAR models, IRFs, and PSM to analyze two M&A events.
result Significant positive market reaction and prolonged positive spillovers detected.
This article extends, in a stochastic environment, the Yagil (1987) model which establishes, in a deterministic dividend discount model, a range for the exchange ratio in a stock-for-stock merger agreement. Here, we generalize Yagil's work letting both pre- and post-merger dividends grow randomly over time. If Yagil fo…
Pakistan examines digital mergers using traditional competition tools.
problem Regulating digital mergers in a developing country.
method Empirical comparative analysis of CCP's M&A decisions.
result CCP uses same decision factors for digital and traditional M&As.
Optimal execution strategy for merger & acquisition contracts with price impact.
problem Optimal execution and pricing of financial derivatives in M&A deals.
method Indifference utility arguments, considering linear and nonlinear contracts.
result Linear contracts are more expensive and vulnerable to manipulation.
New method resolves ambiguity in measuring black hole merger angular momentum.
problem Ambiguity in measuring angular momentum during black hole mergers.
method Quasilocal mass and optimal isometric embedding theory.
result New definition of angular momentum free of supertranslation ambiguity.
The present work has as principal objective analyze the evolution of the process of privatization, mergers and acquisitions of the big companies in the country in the last decades, to understand the conductive threads that formed the structural changes of the economy, in order world oligopólicas to insert it to the glo…
Study examines how mergers and acquisitions affect Indian banks' financial performance and capital structure.
problem Impact of mergers and acquisitions on Indian banks' financial performance and capital structure.
method Statistical analysis using paired t-test on selected banks' annual reports.
result Mergers and acquisitions significantly impact financial performance and capital structure of Indian banks.
The article improves the display of acceptable exchange ratios for merging companies.
problem Determining feasible exchange ratios for merging companies.
method Exploits a diagrammatic approach to display the bargaining region.
result Shares face upper and lower bounds for acceptable exchange ratios.
Gravitational waves are predicted by the general theory of relativity. In [6] D. Christodoulou showed that gravitational waves have a nonlinear memory. We proved in [3] that the electromagnetic field contributes at highest order to the nonlinear memory effect of gravitational waves. In the present paper, we study this …
New algorithm clusters GRBs into two groups: short and long duration.
problem Determining the number of clusters in gamma-ray bursts.
method Completely parameter-free clustering algorithm.
result Clusters indicate two main groups: short and long duration GRBs.
The FCA improved insider trading regulation after 2012, reducing abnormal returns.
problem Regulation of insider trading before and after the UK Financial Services Act 2012.
method Event study methodology using abnormal returns analysis.
result Abnormal returns were reduced after the FCA took over from the FSA.
Mass algorithm predicts M&A deals from patent data.
problem Hard to automatically predict M&A deals due to complex human skills.
method Machine learning-based similarity measure (MASS) applied to patent data.
result MASS outperforms LightGCN in forecasting M&A deals.
Empirical researchers are increasingly faced with rich data sets containing many controls or instrumental variables, making it essential to choose an appropriate approach to variable selection. In this paper, we provide results for valid inference after post- or orthogonal -Boosting is used for variable selection.…
A concept of martingale-fair index of return, consistent with Arbitrage Free Pricing Theory, is introduced. An explicit formula for the average rate of return of a group of investment/pension funds in a discrete time stochastic model is derived and several properties of this index are shown. In particular, it is proven…
We introduce deep learning models to estimate the masses of the binary components of black hole mergers, , and three astrophysical properties of the post-merger compact remnant, namely, the final spin, , and the frequency and damping time of the ringdown oscillations of the fundamental bar mo…
Predicting Status of Pre and Post M&A Deals Using Machine Learning and Deep Learning Techniquesq-fin.GN
Paper predicts M&A deal success using ML and DL techniques.
problem Predicting the success of M&A deals to avoid costly mistakes.
method Data preprocessing with ML techniques, feedforward neural networks, and sentiment scores integration.
result Methodology outperforms benchmark models in preliminary tests.
Economy of scales in R&D with block-busterscond-mat.stat-mech
Are large scale research programs that include many projects more productive than smaller ones with fewer projects? This problem of economy of scale is particularly relevant for understanding recent mergers in particular in the pharmaceutical industry. We present a quantitative theory based on the characterization of d…
A Deep Learning Method for Predicting Mergers and Acquisitions: Temporal Dynamic Industry Networksq-fin.ST
Deep learning predicts M&A events in industry networks.
problem Predicting M&A behaviors in competitive industries with complex interdependencies.
method Temporal Dynamic Industry Network (TDIN) model using temporal point processes and deep learning.
result Effective M&A event prediction and actionable recommendations.
Constructs solutions of Einstein equations for black holes gluing along timelike geodesics.
problem Constructing solutions of Einstein equations for black holes gluing along timelike geodesics.
method Constructs solutions of the Einstein equations describing a mass Kerr black hole traveling along a timelike geodesic .
result Constructs true solutions of the Einstein equations for black holes gluing along timelike geodesics.
Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock ma…
A novel clustering method uses torque balance to group objects.
problem Grouping similar objects in various scientific fields.
method Inspired by gravitational interactions, a parameter-free clustering algorithm based on mass and distance.
result The algorithm effectively clusters objects regardless of their shape, size, or density.
Study analyzes COFCO's acquisition of Mengniu Dairy, revealing financial and non-financial impacts.
problem Understanding the impact of COFCO's acquisition of Mengniu Dairy.
method Analyzes financial and non-financial contributions of Mengniu Dairy to COFCO.
result Provides insights for future corporate M&A activities in the dairy industry.
As part of Basel II's incremental risk charge (IRC) methodology, this paper summarizes our extensive investigations of constructing transition probability matrices (TPMs) for unsecuritized credit products in the trading book. The objective is to create monthly or quarterly TPMs with predefined sectors and ratings that …
Stock markets are not what we think they are: the key roles of cross-ownership and corporate treasury stockcond-mat.other
We describe and document three mechanisms by which corporations can influence or even control stock prices. (i) Parent and holding companies wield control over other publicly traded companies. (ii) Through clever management of treasury stock based on buyback programs and stock issuance, stock price fluctuations can be …
We present the first estimation of the mass and spin magnitude of Kerr black holes resulting from the coalescence of binary black holes using a deep neural network. The network is trained on a dataset containing 80\% of the full publicly available catalog of numerical simulations of gravitational waves emission by bina…
This paper provides a holistic study of how stock prices vary in their response to financial disclosures across different topics. Thereby, we specifically shed light into the extensive amount of filings for which no a priori categorization of their content exists. For this purpose, we utilize an approach from data mini…
The article calculates the near horizon limit of Wang--Yau quasi-local mass.
problem Calculating the near horizon limit of quasi-local mass.
method Utilizing the properties of the mean curvature vector and optimal embedding equation.
result Existence and uniqueness of optimal embedding and continuity of quasi-local mass.
The goal of this study is to present the development of a machine learning based approach that utilizes phase space alone to separate the Gaia DR2 stars into two categories: those accreted onto the Milky Way from those that are in situ. Traditional selection methods that have been used to identify accreted stars typica…
Formally constructs metrics near timelike geodesics in vacuum spacetimes.
problem Constructing metrics near timelike geodesics in spacetimes.
method Constructs a family of metrics depending on a small parameter ε, solving the Einstein vacuum equations modulo O(ε^∞).
result The rescalings near the geodesic tend to a fixed subextremal Kerr metric.
Towards Competent AI for Fundamental Analysis in Finance: A Benchmark Dataset and Evaluationq-fin.ST
Paper proposes FinAR-Bench to evaluate LLMs in financial analysis tasks.
problem Inaccurate financial analysis by LLMs leading to investment and regulatory issues.
method Proposes FinAR-Bench, a benchmark dataset with three steps: key info extraction, financial indicator calculation, and logical reasoning.
result LLMs perform better in key info extraction and indicator calculation but struggle with logical reasoning.
Predicting startup success using Crunchbase data and deep learning.
problem Predicting startup success in a volatile entrepreneurial ecosystem.
method Novel deep learning model integrating funding metrics, founder features, and industry category.
result Achieved 14 times capital growth and identified high-potential startups.
We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor-the debt-to-asset ratio R-in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market …
Machine learning classifies gravitational wave signals to test General Relativity.
problem Testing General Relativity with gravitational wave signals from binary black hole mergers.
method Convolutional Neural Networks (CNNs) trained on whitened waveforms and response function type observables.
result CNNs improve classification sensitivity by a factor of approximately 33 compared to whitened waveforms.
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriescs.LG
New algorithm detects unique events in time series data.
problem Detecting anomalous events in unknown properties.
method Model-free, unsupervised detection using Temporal Outlier Factor (TOF).
result TOF outperforms traditional outlier detection methods.
--- the companies populating a Stock market, along with their connections, can be effectively modeled through a directed network, where the nodes represent the companies, and the links indicate the ownership. This paper deals with this theme and discusses the concentration of a market. A cross-shareholding matrix is co…
The M and A transactions represent a wide range of unique business optimization opportunities in the corporate transformation deals, which are usually characterized by the high level of total risk. The M and A transactions can be successfully implemented by taking to an account the size of investments, purchase price, …
Gravitational wave memory increases faster than Brownian motion in early universe and astrophysical sources.
problem Detecting gravitational wave memory from early universe and astrophysical sources.
method Investigated gravitational wave sources in early universe and astrophysical settings, showing memory increases faster than Brownian motion.
result Gravitational wave memory increases following a power law, faster than the scaling law of Brownian motion.
Twitter Permeability to financial events: an experiment towards a model for sensing irregularitiesq-fin.ST
Research shows Twitter is permeable to financial events, influencing its content and sentiment.
problem Investigating how Twitter reacts to financial events.
method Conducted experiments on a specific financial event (Tesco PLC and Booker Group PLC merger announcement).
result Twitter is permeable to financial events, affecting its content and sentiment.