The change of the geopolitical realities, the emergence of new regional dynamics and the perception of security in Central Asia have also changed current perspectives in the region. Fully revised and updated to cover the latest informations and developments, the book will provide comprehensive, accessible and successful introduction for those who are interested in the Central Asia region. As the editors, we have filled a long-neglected gap by producing a volume that authoritatively covers the states of the region. The book will become a definitive text for the teaching as it presents in-depth explorations of systemic and sophisticated way of understanding the actors and processes and offers case study encompassing many subjects about Central Asia. It conbines old and new perspectives with discerning care.

This book –The Changing Perspectives of Central Asia in the 21^st Century- has provided readers with prominent knowledge of independence period, actors, minority issues, nation-state building process, energy, security, water, boundary, regional integration and foreign policies of Kazakhstan, Kyrgyzstan, Uzbekistan, Turkmenistan and Tajikistan with each other and with Russia, China, America, the EU and Turkey. The book claims that geopolitical realities, regional dynamics and the perception of security in Central Asia have changed. Thus, the book focuses on environmental degradation, cyber insecurity and social unrest triggered by sovereign debt traps. These discussions highlight the necessity to reconsider the traditional perception of security as the analysis has to go beyond the state to address a wide range of security threats.

Dr. Murat YORULMAZ is an Assistant Professor in the Department of Management and Organization at Trakya University, Edirne.

Dr. Serdar YILMAZ is an Assistant Professor in the Department of Political Science and International Relations at Muğla Sıtkı Koçman University, Muğla.

Financial time series including high frequency structures like jumps, spikes and stochastic volatility are usually modeled in an ad-hoc manner by stochastic differential equations together with Levy processes. Estimating the parameters and determining the jump size distributions do not have a precise and universally accepted method. Under these circumstances, complexities and confusions usually arise. This book, approaches to this issue from a very different angle through introducing an autocorrelation one process together with finite number of Fourier series terms. Introduction of Fourier series to estimate the dynamics of the process is not done in an ad-hoc manner or as done before in dealing with seasonality. Here the moving average is transformed to a “moving and fluctuating” average by the help of Fourier series. Instead of adding jump structures to the model which makes the parameter estimation quite cumbersome, our model in discrete time can easily be transformed to a well-known mean reverting continuous time process. Moreover, our alternative model turned out to be a quite powerful and accurate forecasting technique.