He has taught at various Universities including the Athens University of Economics and Business and the Hellenic Open University, Greece, in subjects such as statistics, econometrics, time series, data analysis and quantitative techniques. Stavros Degiannakis is Assistant Professor in the Department of Economic and Regional Development of Panteion University of Social and Political Sciences. Christos has presented several papers at international academic conferences in the UK, Greece, Portugal, Italy, France, Ireland, and Spain, and is a Fellow of the Higher Education Academy (UK).ĭr. He has been involved in a number of research funded projects including a Marie Curie project on 'Volatility forecasting evaluation based on loss function with well-defined multivariate distributional form and ultra-high frequency datasets (as co-ordinator). He has published extensively in academic journals and is the Editor-in-Chief of the International Journal of Financial Markets and Derivatives (IJFMD) and Editor of the International Journal of Computational Economics and Econometrics (IJCEE). His main research interests include behavioural finance, financial derivatives (futures and options markets), financial econometrics (forecasting realized volatility, VaR modelling) and empirical banking (efficiency, competition and profitability). Christos Floros (Crete, Greece) is Professor of Finance at the Technological Educational Institute of Crete and Hellenic Open University (Greece). It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.ĭr. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets. The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate.
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