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Contemporary Issues in Quantitative Finance




  • Available for pre-order on March 20, 2023. Item will ship after April 10, 2023
ISBN 9781032101125
April 10, 2023 Forthcoming by Routledge
342 Pages 89 B/W Illustrations

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Book Description

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.

Table of Contents

About the Author, Chapter 1. Introduction: History, Present, Future of Financial Markets and Securities, Chapter 2. Global Finance, Chapter 3. Financial Crises: Reasons, Consequences, Lessons, Chapter 4. Trading Ecosystem: History, Speed, Orders, Intraday, ESG, Chapter 5. Asset Pricing Models, Chapter 6. Modern Portfolio Theory & Optimization, Chapter 7. Hedge Funds, Mutual Funds, ETFs, Chapter 8. Stochastic Calculus, Chapter 9. Monte Carlo Simulations, Chapter 10. Value-at-Risk [VaR], Chapter 11. Fixed Income Securities, Term Structure of Interest Rates, Chapter 12. Options: Introduction, Chapter 13. Options: Binomial Tree Model, Chapter 14. Options: Black-Scholes-Merton Model, Chapter 15. Options: Greeks and Risk Management, Chapter 16. Forwards and Futures, Chapter 17. Alternative Investments, Chapter 18. Currency, Cryptocurrency, Blockchain, FinTech, Chapter 19. Artificial Intelligence in Finance, Chapter 20. Big Data Analytics, 21. Bibliography, Index

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Author(s)

Biography

Ahmet Can Inci is a Professor of Finance at Bryant University in Rhode Island, USA. He received his Ph.D. from University of Michigan, Ann Arbor in 2001. He holds an MBA from Ohio State University, MSc in Control Systems from Imperial College – University of London, and BSc in Electrical and Electronics Engineering from Bogazici University in Istanbul. Prof. Inci’s research interests include exchange rate dynamics, corporate governance, emerging markets, oil and energy, futures, contagion and flight to quality, 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 CAIA member, AASCB program consultant / reviewer, and editorial board member of numerous academic journals.