Cross Listing of a Finnish Company on an Exchange in the United States of America

Finnish companies cross listing in the United States is an exceptional phenomenon. This study examines the cross listing decision, cross listing choice and cross listing process with associated challenges and critical factors. The aim is to create an in-depth understanding of the cross listing process and the required financial information. Based on that, the aim is to establish the process phases with the challenges and the critical factors that ought to be considered be- fore establishing the process plus re-evaluated and further considered at points in time during the process. The empirical part of this study is conducted as a qualitative study. The research data was collected through the adoption of two approaches, which are the interview approach and the textual data approach. The interviews were conducted with Finnish practitioners in the field of accounting and finance. The textual data was from publicly available publications of this phenomenon by the two BIG5 accounting companies worldwide. The results of this study demonstrate the benefits of cross listing in the U.S. are the better growth opportunities, the reduction of cost of capital and the production of higher quality financial information. In the decision making process companies should assess whether the benefits exceed the increased costs, the pressure for performance, the uncertainty of market recognition and the requirements of management. The exchange listing is seen as the most favourable cross listing choice for Finnish companies. The establishment of the processes for producing reliable, transparent and timely financial information was seen as both highly critical and very challenging. The critical success factors relating to the cross listing phases are the assessment and planning as well as the right mix of experiences and expertise. The timing plays important role in the process. The results mainly corroborate the literature concerning cross listing decision and choice. This study contributes to the literature on the cross listing process offering a useful model for the phases of the cross listing process.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Managing the change of organizational culture in cross-border mergers and acquisitions: The role of post-acquisition integration in organizational culture change

Over the years, cross-border mergers and acquisitions have become a popular strategic option for variety of firms. Companies often seek rapid growth through acquiring potentially valuable enterprises or attempting to enhance their organization’s profitability by merging with other firms. However, managing the change of organizational culture is a major managerial challenge as companies often confront difficulties when merging two previously autonomous organizational cultures into one, joint organizational culture. Therefore, the purpose of this study is to increase understanding related to the challenges and possibilities concerning the management of organizational culture change in cross-border mergers and acquisitions. The research question “How to manage the change of organizational culture in cross-border mergers and acquisitions?” is analysed in relation to the theories presented in this thesis regarding organizational culture, organizational change and acculturation as well as in relation with the collected empirical data. The research question is divided into three sub-questions according to the following: (1) “What is the role of organizational culture in organizations?”, (2) “How to manage organizational change in mergers and acquisitions?” and (3) “How to manage organizational culture change through acculturation?”. The thesis is conducted as a qualitative case study research including three personal interviews and one group interview. The interviews were conducted as a combination of semi-structured and unstructured interviews. Theories related to organizational culture, the management of change as well as acculturation are studied and further analysed in relation to empirical material collected by the researcher. Research findings indicate that that several factors can influence the success of managing the organizational culture change in cross-border mergers and acquisitions. Factors such as defining the preferred acculturation model prior the merger; managing the resistance of change; open communication; acknowledgement of local culture and cultural differences; involvement of personnel in change processes; as well as the formulation and implementation of comprehensive change plans proved to be important factors with relation to successful management of organizational culture change

[Joseph] Guillemot gagnant du National anglais [épreuve de cross à Windsor, le 13 mars 1920] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58527

21-3-20, [27e] championnat de France de cross-country, le départ [à Bry-sur-Marne] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58558

21-3-20, Bry-sur-Marne, [27e] championnat de France de cross-country, un passage de [Joseph] Guillemot et Vignaud : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58560

21/3/20, Bry-sur-Marne, [27e] championnat de France de cross-country, l'arrivée, [Joseph] Guillemot et Vignaud : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58561

21-3-20, Bry-sur-Marne [27e] championnat de France de cross-country, Vignaud et [Joseph] Guillemot après leur arrivée : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58562