Contemporary Issues in Quantitative Finance

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A01=Ahmet Can Inci
advanced quantitative finance techniques
artificial intelligence finance
Asset Classes
Author_Ahmet Can Inci
Basel Iii
Binomial Tree
Binomial Tree Model
Black Scholes Merton Formula
Black Scholes Merton Model
blockchain applications
Call Option
Call Option Price
Category=KC
Category=KFF
Category=KFFM
Category=PBW
Contemporary Issues
Convertible Bond
cryptocurrencies
derivatives
Efficient Frontier
eq_bestseller
eq_business-finance-law
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
European Call Option
Exercise Price
Federal Reserve
financial engineering
financial risk modelling
Geometric Brownian Motion
Lognormal Process
mathematical tools
Monte Carlo methods
Option Greeks
Option Price
Option Price Formula
portfolio optimisation
Put Option Price
Quantitative Finance
Risk Free Portfolio
Risk Free Rate
Risk Neutral World
Sharpe Ratio
statistical methodologies
statistical techniques
stochastic processes
ultra-high-frequency trading
Underlying Security
Underlying Stock Price

Product details

  • ISBN 9781032101125
  • Weight: 760g
  • Dimensions: 174 x 246mm
  • Publication Date: 10 Apr 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Contemporary quantitative finance connects the abstract theory and the practical use of financial innovations, such as ultra-high-frequency trading and cryptocurrencies. It teaches students how to use cutting-edge computational techniques, mathematical tools, and statistical methodologies, with a focus on real-life applications.

The textbook opens with chapters on financial markets, global finance, and financial crises, setting the subject in its historical and international context. It then examines key topics in modern quantitative finance, including asset pricing, exchange-traded funds, Monte Carlo simulations, options, alternative investments, artificial intelligence, and big data analytics in finance. Complex theory is condensed to intuition, with appendices presenting advanced mathematical or statistical techniques. Each chapter offers Excel-based implementations, conceptual questions, quantitative problems, and a research project, giving students ample opportunity to develop their skills. Clear chapter objectives, summaries, and key terms also support student learning.

Digital supplements, including code and PowerPoint slides, are available for instructors. Assuming some prior financial education, this textbook is suited to upper-level undergraduate and postgraduate courses in quantitative finance, financial engineering, and derivatives.

Ahmet Can Inci is Professor of Finance at Bryant University in Rhode Island, U.S.A. He received his Ph.D. from the University of Michigan, Ann Arbor, in 2001. He holds an M.B.A. from Ohio State University, an M.Sc. in control systems from Imperial College – University of London, and a B.Sc. in electrical and electronics engineering from Bogazici University in Istanbul. Professor Inci’s research interests include exchange rate dynamics, corporate governance, emerging markets, oil and energy, futures, contagion and flight to quality, the gender gap at the workplace, insider trading, intraday volatility, and market efficiency. He teaches innovations in finance, international finance and business, investments, corporate finance, foundations of financial theory, financial analytics, and financial engineering. He is a C.A.I.A. member, A.A.S.C.B. program consultant/reviewer, and editorial board member of numerous academic journals.

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