This exciting volume presents cutting-edge developments in high frequency financial econometrics, spanning a diverse range of topics: stochastic modeling, statistical analysis of high-frequency data, models in econophysics, applications to the analysis of high-frequency data, systems and complex adaptive systems in finance, among a host of others. Written, in part, on the outgrowth of several recent conferences in the subject matter and in concert with over two-dozen experts in the field, the main purpose of the handbook is to mathematically illustrate the fundamental implementation of high-frequency models in the banking and financial industries, both at home and abroad, through use of real-world, time-sensitive applications. By using examples derived from consulting projects, current research and course instruction, each chapter in the book offers a systematic understanding of the recent advances in high-frequency modeling related to real-world situations. Every effort is made to present a balanced treatment between theory and practice, as well as to showcase how accuracy and efficiency in implementing various methods can be used as indispensable tools. To by-pass tedious computation, software illustrations are presented in an assortment of packages, ranging from R, C++, EXCEL-VBA, Minitab, to JMP/SAS. Shedding light on some of the most relevant open questions in the analysis of high-frequency data, this volume will be of interest to graduate students, researchers and industry professionals.
Preface xi Contributors xiii Part One Analysis of Empirical Data 1 1 Estimation of NIG and VG Models for High Frequency Financial Data 3 Jose E. Figueroa-Lopez, Steven R. Lancette, Kiseop Lee, and Yanhui Mi 1.1 Introduction, 3 1.2 The Statistical Models, 6 1.3 Parametric Estimation Methods, 9 1.4 Finite-Sample Performance via Simulations, 14 1.5 Empirical Results, 18 1.6 Conclusion, 22 References, 24 2 A Study of Persistence of Price Movement using High Frequency Financial Data 27 Dragos Bozdog, IonutC Florescu, Khaldoun Khashanah, and Jim Wang 2.1 Introduction, 27 2.2 Methodology, 29 2.3 Results, 35 2.4 Rare Events Distribution, 41 2.5 Conclusions, 44 References, 45 3 Using Boosting for Financial Analysis and Trading 47 German Creamer 3.1 Introduction, 47 3.2 Methods, 48 3.3 Performance Evaluation, 53 3.4 Earnings Prediction and Algorithmic Trading, 60 3.5 Final Comments and Conclusions, 66 References, 69 4 Impact of Correlation Fluctuations on Securitized structures 75 Eric Hillebrand, Ambar N. Sengupta, and Junyue Xu 4.1 Introduction, 75 4.2 Description of the Products and Models, 77 4.3 Impact of Dynamics of Default Correlation on Low-Frequency Tranches, 79 4.4 Impact of Dynamics of Default Correlation on High-Frequency Tranches, 87 4.5 Conclusion, 92 References, 94 5 Construction of Volatility Indices Using A Multinomial Tree Approximation Method 97 Dragos Bozdog, IonutC Florescu, Khaldoun Khashanah, and Hongwei Qiu 5.1 Introduction, 97 5.2 New Methodology, 99 5.3 Results and Discussions, 101 5.4 Summary and Conclusion, 110 References, 115 Part Two Long Range Dependence Models 117 6 Long Correlations Applied to the Study of Memory Effects in High Frequency (TICK) Data, the Dow Jones Index, and International Indices 119 Ernest Barany and Maria Pia Beccar Varela 6.1 Introduction, 119 6.2 Methods Used for Data Analysis, 122 6.3 Data, 128 6.4 Results and Discussions, 132 6.5 Conclusion, 150 References, 160 7 Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales 163 Alec N. Kercheval and Yang Liu 7.1 Introduction, 163 7.2 The Skewed t Distributions, 165 7.3 Risk Forecasts on a Fixed Timescale, 176 7.4 Multiple Timescale Forecasts, 185 7.5 Backtesting, 188 7.6 Further Analysis: Long-Term GARCH and Comparisons using Simulated Data, 203 7.7 Conclusion, 216 References, 217 8 Parameter Estimation and Calibration for Long-Memory Stochastic Volatility Models 219 Alexandra Chronopoulou 8.1 Introduction, 219 8.2 Statistical Inference Under the LMSV Model, 222 8.3 Simulation Results, 227 8.4 Application to the S&P Index, 228 8.5 Conclusion, 229 References, 230 Part Three Analytical Results 233 9 A Market Microstructure Model of Ultra High Frequency Trading 235 Carlos A. Ulibarri and Peter C. Anselmo 9.1 Introduction, 235 9.2 Microstructural Model, 237 9.3 Static Comparisons, 239 9.4 Questions for Future Research, 241 References, 242 10 Multivariate Volatility Estimation with High Frequency Data Using Fourier Method 243 Maria Elvira Mancino and Simona Sanfelici 10.1 Introduction, 243 10.2 Fourier Estimator of Multivariate Spot Volatility, 246 10.3 Fourier Estimator of Integrated Volatility in the Presence of Microstructure Noise, 252 10.4 Fourier Estimator of Integrated Covariance in the Presence of Microstructure Noise, 263 10.5 Forecasting Properties of Fourier Estimator, 272 10.6 Application: Asset Allocation, 286 References, 290 11 The "Retirement" Problem 295 Cristian Pasarica 11.1 Introduction, 295 11.2 The Market Model, 296 11.3 Portfolio and Wealth Processes, 297 11.4 Utility Function, 299 11.5 The Optimization Problem in the Case p(t ,T] = 0, 299 11.6 Duality Approach, 300 11.7 Infinite Horizon Case, 305 References, 324 12 Stochastic Differential Equations and Levy Models with Applications to High Frequency Data 327 Ernest Barany and Maria Pia Beccar Varela 12.1 Solutions to Stochastic Differential Equations, 327 12.2 Stable Distributions, 334 12.3 The Levy Flight Models, 336 12.4 Numerical Simulations
