Modelling and Forecasting High Frequency Financial Data

ISBN-13: 9781137396488 / Angielski / Twarda / 2015 / 278 str.

Stavros Degiannakis

Opis

This book is an accessible practitioners guide to the most cutting-edge models used in high-frequency finance modelling, providing advanced techniques and tools for understanding market microstructure and more generally for analyzing financial markets using recent HF data.

Spis treści

Chapter 1: Introduction to High Frequency Financial Modelling.- Chapter 2: Intra-day Realized Volatility Measures.- Chapter 3: Methods of Volatility Estimation and Forecasting.- Chapter 4: Multiple Model Comparison and Hypothesis Framework Construction.- Chapter 5: Realized Volatility Forecasting - Applications.- Chapter 6: Recent Methods: A Review.- Chapter 7: Intraday Hedge Ratios & Option Pricing.

O autorze

Dr. Christos Floros (Crete, Greece) is Professor of Finance at the Technological Educational Institute of Crete and Hellenic Open University (Greece). 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). 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). 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). 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).

Dr. Stavros Degiannakis is Assistant Professor in the Department of Economic and Regional Development of Panteion University of Social and Political Sciences. 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. He has also served as econometrician for companies in the private and public sector (the Bank of Greece, the University of Portsmouth, the Economic Chamber of Greece, Inventive, the Hellenic Parliament, and Profile). He has served as a referee in more than 30 international journals, such as the Journal of Applied Econometrics, the Journal of Banking and Finance, and the Journal of Applied Statistics. His research interests are in the areas of applied and theoretical financial econometrics (ultra-high frequency data analysis, macro-finance modelling, option pricing, risk modelling) and statistics (marketing metrics, multivariate distributions, forecasting ability, time series analysis). Dr. Stavros Degiannakis received his PhD in Statistics from Athens University of Economics and Business. He graduated from the Athens University of Economics and Business, where he completed his studies in Statistics, and holds a M.Sc. degree in Econometrics from the University of Essex.

Blurb

The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets.

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. 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.

Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.