Reflecting the fast pace and ever-evolving nature of the financial
industry, the Handbook of High-Frequency Trading and Modeling in
Finance details how high-frequency analysis presents new systematic
approaches to implementing quantitative activities with
high-frequency financial data. Introducing new and established
mathematical foundations necessary to analyze realistic market
models and scenarios, the handbook begins with a presentation of
the dynamics and complexity of futures and derivatives markets as
well as a portfolio optimization problem using quantum computers.
Subsequently, the handbook addresses estimating complex model
parameters using high-frequency data. Finally, the handbook focuses
on the links between models used in financial markets and models
used in other research areas such as geophysics, fossil records,
and earthquake studies. The Handbook of High-Frequency Trading and
Modeling in Finance also features: Contributions by well-known
experts within the academic, industrial, and regulatory fields A
well-structured outline on the various data analysis methodologies
used to identify new trading opportunities Newly emerging
quantitative tools that address growing concerns relating to
high-frequency data such as stochastic volatility and volatility
tracking; stochastic jump processes for limit-order books and
broader market indicators; and options markets Practical
applications using real-world data to help readers better
understand the presented material The Handbook of High-Frequency
Trading and Modeling in Finance is an excellent reference for
professionals in the fields of business, applied statistics,
econometrics, and financial engineering. The handbook is also a
good supplement for graduate and MBA-level courses on quantitative
finance, volatility, and financial econometrics. Ionut Florescu,
PhD, is Research Associate Professor in Financial Engineering and
Director of the Hanlon Financial Systems Laboratory at Stevens
Institute of Technology. His research interests include stochastic
volatility, stochastic partial differential equations, Monte Carlo
Methods, and numerical methods for stochastic processes. Dr.
Florescu is the author of Probability and Stochastic Processes, the
coauthor of Handbook of Probability, and the coeditor of Handbook
of Modeling High-Frequency Data in Finance, all published by Wiley.
Maria C. Mariani, PhD, is Shigeko K. Chan Distinguished Professor
in Mathematical Sciences and Chair of the Department of
Mathematical Sciences at The University of Texas at El Paso. Her
research interests include mathematical finance, applied
mathematics, geophysics, nonlinear and stochastic partial
differential equations and numerical methods. Dr. Mariani is the
coeditor of Handbook of Modeling High-Frequency Data in Finance,
also published by Wiley. H. Eugene Stanley, PhD, is William
Fairfield Warren Distinguished Professor at Boston University.
Stanley is one of the key founders of the new interdisciplinary
field of econophysics, and has an ISI Hirsch index H=128 based on
more than 1200 papers. In 2004 he was elected to the National
Academy of Sciences. Frederi G. Viens, PhD, is Professor of
Statistics and Mathematics and Director of the Computational
Finance Program at Purdue University. He holds more than two dozen
local, regional, and national awards and he travels extensively on
a world-wide basis to deliver lectures on his research interests,
which range from quantitative finance to climate science and
agricultural economics. A Fellow of the Institute of Mathematics
Statistics, Dr. Viens is the coeditor of Handbook of Modeling
High-Frequency Data in Finance, also published by Wiley.
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