Cross-border Merger and Acquisitions (M&As) are an increasingly important strategy adopted by firms in order to create value in fiercely competitive global markets. Cross-border M&A value creation, that is, wealth creation for shareholders from cross-border M&As, is therefore of considerable theoretical and practical importance. However, our understanding of the sources of cross-border M&A value creation remains limited. Researchers have found that the most commonly researched variables have little effect on cross-border M&A value creation. We therefore still do not understand the processes behind cross-border M&As. In this is dissertation I examine the main effects of host country regulatory, economic and physical infrastructure institutions on cross-border M&A value creation. I further examine the moderating effects of host country political institutions on the relationship between host country regulatory institutions and cross-border M&A value creation. Moreover, I investigate the effects of institutional distance between host and home country on cross-border M&A value creation. I argue that the effects of institutional distance (regulatory and economic distance) on cross-border M&A value creation are not symmetric, but rather the effects are contingent upon the direction of the distance. My hypotheses are tested on a sample of 6141 cross-border M&As between 1995 and 2003. Results of this analysis show that acquirers are more likely to create value by acquiring targets in countries with less advanced regulatory institutions. Further, my results indicate that host country political institutions positively moderate the relationship between host country regulatory institutions and cross-border M&A value creation. Host country economic institutions have an inverted U-shaped relationship with cross-border M&A value creation, and host country physical infrastructure institutions have a positive relationship with cross-border M&A value creation. Additionally, results show that there is an inverted U-shaped relationship between institutional distance and cross-border M&A value creation. The findings suggest that the effects of regulatory and economic institutional distance on cross-border M&A value creation are not symmetric. The effects are contingent upon the direction of the distance. That is whether the level of host country institutions is higher or lower than that of home country institutions. Implications for management and public policy are discussed.

The focus of this doctoral research is on advancing knowledge of what managers can do to address the issues of corporate cultural differences in mergers and acquisitions (M&A). Despite decades of experience, the rate of M&A failure remains high globally. The root causes of these failures have pointed to inadequate strategic deal theses, excessive purchase prices paid, and poor pre- and post-integration management. Human and cultural factors have also been blamed for these failures. Significant research effort has been expended in raising the importance of human factors and the issue of culture fit in M&A. However, research results have remained ambiguous. Extant organisational M&A culture research has largely focused on examining the role of culture in M&A and its impact on M&A performance. How to address organisational culture differences in M&A is much less studied. Only a small handful of scholars, consultants and practitioners have attempted to prescribe corporate culture alignment guidelines that are either too generic or prescriptive. Managers remain unclear as to how to manage cultural differences in M&A.The research sets out to address how managers can effectively moderate the effects of corporate cultural differences on M&A performance in domestic M&A. It aims to develop a practical M&A corporate culture alignment model for managers tasked with addressing the effects of corporate cultural differences in M&A. It also focuses on addressing the issues of single-layered acculturation of corporate cultures in isolation from the perplexing issues of double-layered acculturation between national and corporate cultures in cross-border transactions. The researcher adopted a qualitative case study research method to deliver on the research objectives within the doctoral research timeframe. He selected a sample of four domestic M&A case studies in Thailand where he is located. Each case study was free of issues related to national cultural differences. The researcher was able to draw rich information and insights from interviewing a total of 50 senior executives, middle managers and staff across case studies. The main research findings provide managers with an improved understanding of the roles of corporate culture on M&A performance and a practical and repeatable five-phase M&A corporate culture alignment model (‘5-D’). The model offers a planned step-by-step change approach, key objectives, and suggested tools and templates that help guide managers to effectively moderate the effects of corporate culture differences in domestic M&A from pre-to post-M&A stages. The model also provides strategic choices and implementation guidelines for managers to consider in addressing the emergent nature of acculturation and change in M&A integration situations. The effectiveness of this exploratory model shall be further tested in future qualitative and quantitative studies. The empirical testing of the research recommendations has already begun with a number of recent M&A projects in Asia outside of this research.

Nichtstationarität ist eines der häufigsten, jedoch nach wie vor ungelösten Probleme in der Zeitreihenanalyse und ein immer wiederkehrendes Phänomen, sowohl in theoretischen als auch in angewandten Arbeiten. Die jüngsten Fortschritte in der ökonometrischen Theorie und in Methoden des maschinellen Lernens haben es Forschern ermöglicht, neue Ansätze für empirische Analysen zu entwickeln, von denen einige in dieser Arbeit erörtert werden sollen. Kapitel 3 befasst sich mit der Vorhersage von Mergers & Acquisitions (M&A). Obwohl es keinen Zweifel daran gibt, dass M&A-Aktivitäten im Unternehmenssektor wellenartigen Mustern folgen, gibt es keine einheitlich akzeptierte Definition einer solchen "Mergerwelle" im Zeitreihenkontext. Zur Messung der Fusions- und Übernahmetätigkeit werden häufig Zeitreihenmodelle mit Zähldaten verwendet und Mergerwellen werden dann als Cluster von Zeiträumen mit einer ungewöhnlich hohen Anzahl von solchen Mergers & Acqusitions im Nachhinein definiert. Die Verteilung der Abschlüsse ist jedoch in der Regel nicht normal (von Gaußscher Natur). In jüngster Zeit wurden verschiedene Ansätze vorgeschlagen, die den zeitlich variablen Charakter der M&A-Aktivitäten berücksichtigen, aber immer noch eine a-priori-Auswahl der Parameter erfordern. Wir schlagen vor, die Kombination aus einem lokalem parametrischem Ansatz und Multiplikator-Bootstrap an einen Zähldatenkontext anzupassen, um lokal homogene Intervalle in den Zeitreihen der M&A-Aktivität zu identifizieren. Dies macht eine manuelle Parameterauswahl überflüssig und ermöglicht die Erstellung genauer Prognosen ohne manuelle Eingaben. Kapitel 4 ist eine empirische Studie über Sprünge in Hochfrequenzmärkten für Kryptowährungen. Während Aufmerksamkeit ein Prädiktor für die Preise von Kryptowährungenn ist und Sprünge in Bitcoin-Preisen bekannt sind, wissen wir wenig über ihre Alternativen. Die Untersuchung von hochfrequenten Krypto-Ticks gibt uns die einzigartige Möglichkeit zu bestätigen, dass marktübergreifende Renditen von Kryptowährungenn durch Sprünge in Hochfrequenzdaten getrieben werden, die sich um Black-Swan-Ereignisse gruppieren und den saisonalen Schwankungen von Volatilität und Handelsvolumen ähneln. Regressionen zeigen, dass Sprünge innerhalb des Tages die Renditen am Ende des Tages in Größe und Richtung erheblich beeinflussen. Dies liefert grundlegende Forschungsergebnisse für Krypto-Optionspreismodelle und eröffnet Möglichkeiten, die ökonometrische Theorie weiterzuentwickeln, um die spezifische Marktmikrostruktur von Kryptowährungen besser zu berücksichtigen. In Kapitel 5 wird die zunehmende Verbreitung von Kryptowährungen (Digital Assets / DAs) wie Bitcoin (BTC) erörtert, die den Bedarf an genauen Optionspreismodellen erhöht. Bestehende Methoden werden jedoch der Volatilität der aufkommenden DAs nicht gerecht. Es wurden viele Modelle vorgeschlagen, um der unorthodoxen Marktdynamik und den häufigen Störungen in der Mikrostruktur zu begegnen, die durch die Nicht-Stationarität und die besonderen Statistiken der DA-Märkte verursacht werden. Sie sind jedoch entweder anfällig für den Fluch der Dimensionalität, da zusätzliche Komplexität erforderlich ist, um traditionelle Theorien anzuwenden, oder sie passen sich zu sehr an historische Muster an, die sich möglicherweise nie wiederholen. Stattdessen nutzen wir die jüngsten Fortschritte beim Clustering von Marktregimen (MR) mit dem Implied Stochastic Volatility Model (ISVM) auf einem sehr aktuellen Datensatz, der BTC-Optionen auf der beliebten Handelsplattform Deribit abdeckt. Time-Regime Clustering ist eine temporale Clustering-Methode, die die historische Entwicklung eines Marktes in verschiedene Volatilitätsperioden unter Berücksichtigung der Nicht-Stationarität gruppiert. ISVM kann die Erwartungen der Anleger in jeder der stimmungsgesteuerten Perioden berücksichtigen, indem es implizite Volatilitätsdaten (IV) verwendet. In diesem Kapitel wenden wir diese integrierte Zeitregime-Clustering- und ISVM-Methode (MR-ISVM) auf Hochfrequenzdaten für BTC-Optionen an. Wir zeigen, dass MR-ISVM dazu beiträgt, die Schwierigkeiten durch die komplexe Anpassung an Sprünge in den Merkmalen höherer Ordnung von Optionspreismodellen zu überwinden. Dies ermöglicht es uns, den Markt auf der Grundlage der Erwartungen seiner Teilnehmer auf adaptive Weise zu bewerten und das Verfahren auf einen neuen Datensatz anzuwenden, der bisher unerforschte DA-Dynamiken umfasst. / Nonstationarity is one of the most prevalent, yet unsolved problems in time series analysis and a reoccuring phenomenon both in theoretical, and applied works. Recent advances in econometric theory and machine learning methods have allowed researchers to adpot and develop new approaches for empirical analyses, some of which will be discussed in this thesis. Chapter 3 is about predicting merger & acquisition (M&A) events. While there is no doubt that M&A activity in the corporate sector follows wave-like patterns, there is no uniquely accepted definition of such a "merger wave" in a time series context. Count-data time series models are often employed to measure M&A activity and merger waves are then defined as clusters of periods with an unusually high number of M&A deals retrospectively. However, the distribution of deals is usually not normal (Gaussian). More recently, different approaches that take into account the time-varying nature of M&A activity have been proposed, but still require the a-priori selection of parameters. We propose adapating the combination of the Local Parametric Approach and Multiplier Bootstrap to a count data setup in order to identify locally homogeneous intervals in the time series of M&A activity. This eliminates the need for manual parameter selection and allows for the generation of accurate forecasts without any manual input. Chapter 4 is an empirical study on jumps in high frequency digital asset markets. While attention is a predictor for digital asset prices, and jumps in Bitcoin prices are well-known, we know little about its alternatives. Studying high frequency crypto ticks gives us the unique possibility to confirm that cross market digital asset returns are driven by high frequency jumps clustered around black swan events, resembling volatility and trading volume seasonalities. Regressions show that intra-day jumps significantly influence end of day returns in size and direction. This provides fundamental research for crypto option pricing models and opens up possibilities to evolve econometric theory to better address the specific market microstructure of cryptos. Chapter 5 discusses the increasing adoption of Digital Assets (DAs), such as Bitcoin (BTC), which raises the need for accurate option pricing models. Yet, existing methodologies fail to cope with the volatile nature of the emerging DAs. Many models have been proposed to address the unorthodox market dynamics and frequent disruptions in the microstructure caused by the non-stationarity, and peculiar statistics, in DA markets. However, they are either prone to the curse of dimensionality, as additional complexity is required to employ traditional theories, or they overfit historical patterns that may never repeat. Instead, we leverage recent advances in market regime (MR) clustering with the Implied Stochastic Volatility Model (ISVM) on a very recent dataset covering BTC options on the popular trading platform Deribit. Time-regime clustering is a temporal clustering method, that clusters the historic evolution of a market into different volatility periods accounting for non-stationarity. ISVM can incorporate investor expectations in each of the sentiment-driven periods by using implied volatility (IV) data. In this paper, we apply this integrated time-regime clustering and ISVM method (termed MR-ISVM) to high-frequency data on BTC options. We demonstrate that MR-ISVM contributes to overcome the burden of complex adaption to jumps in higher order characteristics of option pricing models. This allows us to price the market based on the expectations of its participants in an adaptive fashion and put the procedure to action on a new dataset covering previously unexplored DA dynamics.

文化常被認為是跨國併購失敗的重要原因，許多文化因素在研究與調查中仍屬薄弱。在本論文中，國家文化是衡量跨境併購文化差異的重點，我們使用了Hofstede 六維度來分析兩種家公司併購情況，即使聯想案例文化維度距離高於TCL案例，但聯想理解在最短時間內和解文化差異，聯想最終解決了問題並變成了利潤。研究表明，溝通是必要的，大大提高了併購的成功性，管理層在合併前，文化評估是必要決策收購的成敗的重要因素。 / The failure rate of cross-border M&As is still high and culture is often blamed for hampering performance. If substantial research has been devoted to investigating M&As performance, cultural factors remain largely unexplained. In this research, national culture is the focus to measure cultural differences in cross border M&As. we used Hofstede 5 dimensions to analyzes two cases, even though Lenovo case cultural dimension distance is higher than TCL case, but Lenovo understand reconciling cultural differences in the shortest time, Lenovo eventually solved the problems and turn into profit. The studies reveal that communication is a necessity, drastically improving the success of a merger, and a cultural assessment of both fit and potential are important factors for providing direction and guidance for necessary decision making and planning initiatives required by management throughout all stages of a merger or acquisition. The purpose of this conceptual paper is to highlight the tensions generated by national culture in cross-border M&As and Chinese enterprises want to increase the success rate of Cross-border M&As, they have to pay close attention on the cultural problems, make a good cultural assessment and manager the cultural integrating work in the cultural integrating process.