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This book gathers the proceedings of the 13th International Conference on Management Science and Engineering Management (ICMSEM 2019), which was held at Brock University, Ontario, Canada on August 5–8, 2019. Exploring the latest ideas and pioneering research achievements in management science and engineering management, the respective contributions highlight both theoretical and practical studies on management science and computing methodologies, and present advanced management concepts and computing technologies for decision-making problems involving large, uncertain and unstructured data. Accordingly, the proceedings offer researchers and practitioners in related fields an essential update, as well as a source of new research directions.
The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.
Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors’ Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance and showcases the formulation of emerging potential applications of new research over the book’s 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market.
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized in areas of social science research as well. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics. As such we only cover the necessary theoretical aspects in each chapter while focusing on real life applications using contemporary data mainly from OECD group of countries. The underlying assumption here is that the researchers in financial economics would be familiar with such application although empirical techniques would be more traditional econometrics. Keeping the application level in a more familiar level, we focus on the methodology based on hidden Markov processes. This will, we believe, help the reader to develop more in-depth understanding of the modeling issues thereby benefiting their future research.
The Finance Division of the Faculty of Commerce and Business Administration at the University of British Columbia in Vancouver, British Columbia, Canada, presents the full text of a working paper entitled "Markov-Swtiching and Stochastic Volatility Diffusion Models of Short-Term Interest Rates," by Daniel R. Smith. The paper compares the Markov-switching and stochastic volatility diffusion models of short-term interest rates.
Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This work brings together some of the main papers that have influenced this field, andshows that the development of this subject has been highly multidisciplinary.
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
The present study has been accepted as a doctoral thesis by the Depart ment of Economics of the Johann Wolfgang Goethe-University in Frankfurt am Main. It grew out from my five year long participation in two research projects, "Econometric analysis of transaction intensity and volatility on fi nancial markets", and "Microstructure on financial markets", that were both conducted by the chair of Statistics and Econometrics (Empirical Economic Research) at the Department of Economics and Business Administration, Jo hann Wolfgang Goethe-University in Frankfurt am Main and financed by the state of Hessen. During this time I have benefitted from many people. First and foremost I would like to thank my thesis supervisor, Prof. Dr. Reinhard Hujer, for initiating and supporting my studies with great encouragement. I am also very grateful to Prof. Dr. Christian Schlag for acting as the second thesis supervisor. Furthermore, I wish to thank Prof. Dr. Joachim Grammig who introduced me to the topics covered in this study in the first place and helped me to sharpen my views on econometrics and financial market microstructure theory through many discussions and also through his willingness to work with me on several related studies.