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Contemporary issues in quantitative finance / Ahmet Can Inci.

By: Material type: TextTextSeries: Routledge advanced texts in economics and financePublication details: New York: Routledge, 2023.Description: x;291pISBN:
  • 9781032101156
  • 9781032101125
Subject(s): DDC classification:
  • 658.4033 INC.C 23
Contents:
Introduction: History, Present, Future of Financial Markets and Securities -- Global Finance -- Financial Crises: Reasons, Consequences, Lessons -- Trading Ecosystem: History, Speed, Orders, Intraday, ESG -- Asset Pricing Models -- Modern Portfolio Theory & Optimization -- Hedge Funds, Mutual Funds, ETFs -- Stochastic Calculus -- Monte Carlo Simulations -- Value-at-Risk [VaR] -- Fixed Income Securities, Term Structure of Interest Rates -- Options: Introduction -- Options: Binomial Tree Model -- Options: Black-Scholes-Merton Model -- Options: Greeks and Risk Management -- Forwards and Futures -- Alternative Investments -- Currency, Cryptocurrency, Blockchain, FinTech -- Artificial Intelligence in Finance -- Big Data Analytics.
Summary: "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"--
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Holdings
Item type Current library Home library Call number Copy number Status Date due Barcode
Book Book Dept. of Commerce Dept. of Commerce 658.4033 INC.C (Browse shelf(Opens below)) 1 Available COM9481

Includes bibliographical references and index.

Introduction: History, Present, Future of Financial Markets and Securities -- Global Finance -- Financial Crises: Reasons, Consequences, Lessons -- Trading Ecosystem: History, Speed, Orders, Intraday, ESG -- Asset Pricing Models -- Modern Portfolio Theory & Optimization -- Hedge Funds, Mutual Funds, ETFs -- Stochastic Calculus -- Monte Carlo Simulations -- Value-at-Risk [VaR] -- Fixed Income Securities, Term Structure of Interest Rates -- Options: Introduction -- Options: Binomial Tree Model -- Options: Black-Scholes-Merton Model -- Options: Greeks and Risk Management -- Forwards and Futures -- Alternative Investments -- Currency, Cryptocurrency, Blockchain, FinTech -- Artificial Intelligence in Finance -- Big Data Analytics.

"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"--

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