Primer for Financial Engineering : Financial Signal Processing and Electronic Trading

This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets.
The book builds from the fundamentals, with the help of simple examples, clearly explaining the concepts to the level needed by an engineer, while showing their practical significance. Topics covered include an in depth examination of market microstructure and trading, a detailed explanation of High Frequency Trading and the 2010 Flash Crash, risk analysis and management, popular trading strategies and their characteristics, and High Performance DSP and  Financial Computing. The book has many examples to explain financial concepts, and the presentation is enhanced with the visual representation of relevant market data. It provides relevant MATLAB codes for readers to further their study. Please visit the companion website on http://booksite.elsevier.com/9780128015612/

Ali N. Akansu received the BS degree from the Technical University of Istanbul, Turkey, in 1980, the MS and Ph.D degrees from the Polytechnic University, Brooklyn, New York in 1983 and 1987, respectively, all in Electrical Engineering. He has been with the Electrical & Computer Engineering Department of the New Jersey Institute of Technology since 1987. He was an academic visitor at David Sarnoff Research Center, at IBM T.J. Watson Research Center, and at GEC-Marconi Electronic Systems Corp. He was a Visiting Professor at Courant Institute of Mathematical Sciences of the New York University performed research on Quantitative Finance. He serves as a consultant to the industry. His current research and professional interests include theory of signals and transforms, financial engineering & electronic trading, and high performance DSP (FPGA & GPU computing).

Mustafa U. Torun received his BS and MS degrees from the Dokuz Eylul University, Turkey, in 2005 and 2007 respectively, both in electrical and electronics engineering. He received his Ph.D degree from the New Jersey Institute of Technology, Newark, NJ, in 2013, in electrical engineering. He published several papers and served as a peer reviewer in many journals and conferences in a wide range of topics including multi-resolution signal processing, statistical signal processing, pattern classification, neural networks, genetic algorithms; their applications in quantitative finance, electronic trading, high frequency trading, digital communications, digital imaging, biomedical engineering; and their implementations on general purpose graphics processing units (GP-GPU) and field programmable gate arrays (FPGA). His current interests include distributed systems, distributed algorithms, cloud computing, and massively parallel computing.