Ebook: Handbook of Quantitative Finance and Risk Management
- Genre: Business // Management
- Tags: Finance/Investment/Banking, Quantitative Finance, Econometrics
- Year: 2010
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This three-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
Selected entries include:
- Michael J. Brennan and Yihong Xia on "Persistence, Predictability and Portfolio Planning"
- Kenton K. Yee on "Combining Fundamental Measures for Stock Selection"
- Itzhak Venezia on "Asian Options"
- Ren-Raw Chen, Ben Logan, Oded Palmon, and Larry Shepp on "Dividends vs. Reinvestments in Continuous Time"
- Fathali Firoozi and Donald Lien on "Capital Structure and Entre Deterrence"
- Lan-Chih Ho, John Cadle, and Michael Theobald on "Portfolio Insurance Strategies – Review of Theory and Empirical Studies"
- Gurdip Bakshi, Charles Cao, and Zhiwu Chen on "Option Pricing and Hedging Performance under Stochastic Volatility and Stochastic Interest Rates"
- C.H. Ted Hong on "Dynamic Econometric Loss Model: A Default Study of US Subprime Market"
- N.K. Chidambaran on "Genetic Programming for Option Pricing"
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.