Categorization of mergers and acquisitions using transaction network features

Mergers and acquisitions (M&A) have occurred among tens of thousands of companies. Categorization of M&A is important to both corporate strategy and academic research. Previous research largely uses case studies and econometric data analysis to classify the motivations and types of M&A. Here, we propose understanding M&A using large-scale data to generate more applicable and generalized results. We use transaction relationships from transaction networks to better understand M&A. Based on detailed pre-analysis, including matching M&A and transaction data from Japan and clustering of transaction networks, we select several M&A observation perspectives. We use two features of transaction networks to categorize M&A cases: betweenness centrality and shortest path length. Betweenness centrality provides a view of the overall business situation from a macro perspective, and shortest path length helps to understand neighboring business environments from a micro perspective. We find several meaningful areas of concentration based on their betweenness centrality values and shortest path lengths. Finally, we re-examine M&A cases in each area, summarizing the trends identified using this categorization method. This study contributes to the M&A literature because it advances quantitative categorization of M&A cases.     

Futures report : City futures: preparing for tomorrow

This report looks at long-range planning and in particular, the Placentia Tomorrow Project. It explains how the project was set up and developed and draws together the key issues of the outcome of such a project.     

A new method for measuring CEO overconfidence: Evidence from acquisitions

This study proposes a new direct method of measuring managerial overconfidence using an acquisition setting. CEOs with significantly higher synergies forecast error (SFE), measured as the deviation between acquisition forecasted operating synergies and actual realized operating synergies, are more likely to exhibit traits of overconfidence. In support of this view, we find that synergies forecast error is positively related to takeover premium and negatively related to acquirer returns. Additionally, validation tests confirm that high SFE firms conduct more diversifying acquisitions. Reflecting, as well, the ex-ante power of the overconfidence measure in other settings, high SFE firms have a positive relation with capital expenditures, leverage, and innovation, and negative relation with equity issues.     

Towards an ontology for electronic transaction services

In this paper we present an ontology for transaction services built upon an established ontology for corporate knowledge called the Enterprise Ontology. We introduce the SmartGov platform for the ‘Smart’ deployment of online services for Public Authorities (PAs) whose requirement of a model of PAs has motivated the ontology, and describe our approach to constructing it. After presenting the ontology we then relate it to the pilot application areas in which the SmartGov platform will be trialed and evaluated. Copyright © 2003 John Wiley & Sons, Ltd.     

Security transaction taxes: issues and evidence

In reaction to the financial crisis, increased attention has recently been given to security transaction taxes (STTs) as a means of (1)?raising revenue for a variety of possible purposes and/or (2)?helping to curb financial market excesses. This paper reviews existing theory and evidence on the efficacy of an STT in fulfilling those tasks, on its potential impact, and on key issues to be faced in designing taxes of this kind.     

Making the deal real: how GE Capital integrates acquisitions

Most companies view acquisitions and mergers as onetime events managed with heroic effort--anxiety-producing experiences that often result in lost jobs, restructured responsibilities, derailed careers, and diminished power. Little wonder, then, that most managers think about how to get them over with--not how to do them better. But even as the number of mergers and acquisitions rises in the United States, studies show the performance of the resulting companies falls below industry averages more often than not. To improve these statistics, executives need to view acquisition integration as a manageable process, not a unique event. One company that has done exactly that is GE Capital Services, which has assimilated more than 100 acquisitions in the past five years alone and, in the process, has developed a formal model for melding new acquisitions into the corporate fold. Drawing on their experiences working with the company to develop the model, consultants Ron Ashkenas and Suzanne Francis, together with GE Capital's Lawrence DeMonaco, offer four lessons from the company's successful run. First, begin the integration process before the deal is signed. Second, dedicate a full-time individual to managing the integration process. Third, implement any necessary restructuring sooner rather than later. And fourth, integrate not only the business operations but also the corporate cultures. These guidelines won't erase all of the discomfort that accompanies many mergers, but they can make the process more transparent and predictable for those involved.     

The dual optimizer for the growth-optimal portfolio under transaction costs

We consider the maximization of the long-term growth rate in the Black–Scholes model under proportional transaction costs as in Taksar et al. (Math. Oper. Res. 13:277–294, 1988). Similarly as in Kallsen and Muhle-Karbe (Ann. Appl. Probab. 20:1341–1358, 2010) for optimal consumption over an infinite horizon, we tackle this problem by determining a shadow price, which is the solution of the dual problem. It can be calculated explicitly up to determining the root of a deterministic function. This in turn allows one to explicitly compute fractional Taylor expansions, both for the no-trade region of the optimal strategy and for the optimal growth rate.     

Fire sale acquisitions: Myth vs. reality

We provide empirical evidence on the conjecture that in economic crises, firms could be forced to sell at deep discounts, or fire sale prices. Using the conventional stock price near the announcement date, we find instead distressed firms in crisis periods receive a 30% higher offer premium than distressed firms in normal periods; they also receive a 34% higher premium than non-distressed firms in crisis periods. Acquirers also do not gain, at announcement and over the long-term. Acquirers, however, may perceive they realize fire sale discounts if the reference is the targets’ highest price in the previous 52 weeks.     

Selling to buy: Asset sales and acquisitions

This study explores the impact of joint corporate asset restructuring decisions, where firms sell an asset in order to fund a subsequent acquisition (selling-to-buy). We find that firms with asset sales are associated with increased acquisition probability. The effect is more pronounced for financially constrained firms. We also show that, in addition to the established improved firm efficiency from focus-increasing asset sales, financially constrained firms obtain the necessary funds to conduct focus-increasing acquisitions, improving further their efficiency. This translates into both higher long-run operating performance and stock abnormal returns at the asset sale announcement.     

Motives for partial acquisitions between firms in the spanish stock market

The paper analyses the motivations for inter-company investment on the Spanish Stock Market through the study of a sample of significant acquisitions reported to the CNMV (the Spanish Securities and Exchange Commission) by quoted firms. By analysing the sign of the cumulative abnormal returns (CAR) and of the correlations among the gains produced by the operation, an attempt is made to find out which motives predominate of the three most important ones suggested by the literature for takeovers: synergy, agency and hubris. Empirical evidence is presented that in the Spanish Stock Market the main motive for acquiring a holding is similar to synergy, especially in partial acquisitions with positive total gains. However, in the samples with negative total gains a main motive similar to hubris always appears. The analysis takes into account the size of the investment and distinguishes between the first report and subsequent ones. Results are similar to those obtained by other authors for takeovers in the US Stock Market, except that in this sample, agency motives do not appear clearly.     

Learning from repetitive acquisitions: Evidence from the time between deals

Knowledge gleaned from previous acquisitions may confer valuation expertise and other benefits. But numerous acquisitions also entail costs, due to problems of incorporating diverse units into an ever larger firm. Such benefits and costs are not directly observable from outside the firm. This article proposes a simple model to infer their relative importance, using the time between successive deals. The data requirements are minimal and allow the use of all mergers and acquisitions during 1992–2009 (more than 300,000 deals). The results provide evidence of learning gains through repetitive acquisitions, especially under CEO continuity and when successive deals are more similar.     

Shareholder voting in mergers and acquisitions: evidence from the UK

This paper examines the determinants and consequences of shareholder voting on mergers and acquisitions using a sample of resolutions approved by shareholders of UK publicly listed firms from 1997 to 2015. We find that dissent on M&A resolutions is negatively related to bidder announcement returns and positively related to shareholders’ general dissatisfaction towards the management. Shareholder dissent is an important predictor of the announcement returns of subsequent M&A deals. We also report an increase in shareholder dissent after the 2007–2008 financial crisis.     

Capturing the real value in high-tech acquisitions

Eager to stay ahead of fast-changing markets, more and more high-tech companies are going outside for competitive advantage. Last year in the United States alone, there were 5,000 high-tech acquisitions, but many of them yielded disappointing results. The reason, the authors contend, is that most managers have a shortsighted view of strategic acquisitions--they focus on the specific products or market share. That focus might make sense in some industries, where those assets can confer substantial advantages, but in high tech, full-fledged technological capabilities--tied to skilled people--are the key to long-term success. Instead of simply following the "buzz," successful acquires systematically assess their own capability needs. They create product road maps to identify holes in their product line. While the business group determines if it can do the work in-house, the business development office scouts for opportunities to buy it. Once business development locates a candidate, it conducts an expanded due diligence, which goes beyond strategic, financial, and legal checks. Successful acquires are focused on long-term capabilities, so they make sure that the target's products reflect a real expertise. They also look to see if key people would be comfortable in the new environment and if they have incentives to stay on board. The final stage of a successful acquisition focuses on retaining the new people--making sure their transition goes smoothly and their energies stay focused. Acquisitions can cause great uncertainty, and skilled people can always go elsewhere. In short, the authors argue, high-tech acquisitions need a new orientation around people, not products.     

Bond market access and acquisitions: empirical evidence from the European market

We investigate whether access to bond markets affects acquisition activity of the European firms between 1999 and 2014. Our study provides insight into the effect that the growing European bond market has on corporate investment activity. We find that access to the bond markets, measured by the existence of a credit rating, has a significant effect on the tendency of firms to make acquisitions. The effect is strongest in Continental Europe and during times of high acquisition activity. We further find that consistent with prior U.S. evidence, bond market access has an inverse effect on abnormal returns generated by the acquisitions. That finding suggests that firms with superior access to financing pursue targets of lesser quality.     

Gaining a competitive edge through acquisitions: Evidence from the telecommunications industry

I study the announcement effects of all acquisitions in the recent telecom wave on both the acquirers and their industry competitors. I find evidence of negative rival returns (? 0.55%, t-stat = 2.47) by focusing on non-horizontal acquisitions where rivals are less susceptible to experience positive returns due to increased market power or expectation that some will become future targets themselves. I find that this effect is worse for closer rivals defined as having similar size and being in the same primary service area as the acquirer. Competitor returns are positively correlated with those of the acquirers suggesting that the negative impact experienced by competitors is driven by acquisitions in which the acquirer itself is earning negative abnormal returns. Results are broadly consistent with the Competitive Advantage Hypothesis that posits acquisitions are a means of corporate restructuring in a changing environment, awarding the acquirer a competitive edge and thereby making these acquisitions costly for their non-merging competitors.     

Real-time market microstructure analysis: online transaction cost analysis

Motivated by the practical challenge in monitoring the performance of a large number of algorithmic trading orders, this paper provides a methodology that leads to automatic discovery of causes that lie behind poor trading performance. It also gives theoretical foundations to a generic framework for real-time trading analysis. The common acronym for investigating the causes of bad and good performance of trading is transaction cost analysis Rosenthal [Performance Metrics for Algorithmic Traders, 2009]). Automated algorithms take care of most of the traded flows on electronic markets (more than 70% in the US, 45% in Europe and 35% in Japan in 2012). Academic literature provides different ways to formalize these algorithms and show how optimal they can be from a mean-variance (like in Almgren and Chriss [J. Risk, 2000, 3(2), 5–39]), a stochastic control (e.g. Guéant et al. [Math. Financ. Econ., 2013, 7(4), 477–507]), an impulse control (see Bouchard et al. [SIAM J. Financ. Math., 2011, 2(1), 404–438]) or a statistical learning (as used in Laruelle et al. [Math. Financ. Econ., 2013, 7(3), 359–403]) viewpoint. This paper is agnostic about the way the algorithm has been built and provides a theoretical formalism to identify in real-time the market conditions that influenced its efficiency or inefficiency. For a given set of characteristics describing the market context, selected by a practitioner, we first show how a set of additional derived explanatory factors, called anomaly detectors, can be created for each market order (following for instance Cristianini and Shawe-Taylor [An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, 2000]). We then will present an online methodology to quantify how this extended set of factors, at any given time, predicts (i.e. have influence, in the sense of predictive power or information defined in Basseville and Nikiforov [Detection of Abrupt Changes: Theory and Application, 1993], Shannon [Bell Syst. Tech. J., 1948, 27, 379–423] and Alkoot and Kittler [Pattern Recogn. Lett., 1999, 20(11), 1361–1369]) which of the orders are underperforming while calculating the predictive power of this explanatory factor set. Armed with this information, which we call influence analysis, we intend to empower the order monitoring user to take appropriate action on any affected orders by re-calibrating the trading algorithms working the order through new parameters, pausing their execution or taking over more direct trading control. Also we intend that use of this method can be taken advantage of to automatically adjust their trading action in the post trade analysis of algorithms.