Applied Quantitative Finance 2nd edition by Wolfgang Karl Härdle, Nikolaus Hautsch, Ludger Overbeck ISBN 3540691774 978-3540691778

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Product details:

ISBN 10: 3540691774
ISBN 13: 978-3540691778
Author: Wolfgang Karl Härdle, Nikolaus Hautsch, Ludger Overbeck 

Recent years have witnessed a growing importance of quantitative methods in both financial research and industry. This development requires the use of advanced techniques on a theoretical and applied level, especially when it comes to the quantification of risk and the valuation of modern financial products. Applied Quantitative Finance (2nd edition) provides a comprehensive and state-of-the-art treatment of cutting-edge topics and methods. It provides solutions to and presents theoretical developments in many practical problems such as risk management, pricing of credit derivatives, quantification of volatility and copula modelling. The synthesis of theory and practice supported by computational tools is reflected in the selection of topics as well as in a finely tuned balance of scientific contributions on practical implementation and theoretical concepts. This linkage between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners comfortable access to new techniques in quantitative finance. Themes that are dominant in current research and which are presented in this book include among others the valuation of Collaterized Debt Obligations (CDOs), the high-frequency analysis of market liquidity, the pricing of Bermuda options and realized volatility. All Quantlets for the calculation of the given examples are downloadable from the Springer web pages.

Applied Quantitative Finance 2nd Table of contents:

• Introduction to Quantitative Finance

  • Overview of Quantitative Finance
  • The Role of Mathematics in Finance
  • Financial Markets and Instruments

• Financial Derivatives and Markets

  • Options, Futures, and Swaps
  • Pricing and Hedging Derivatives
  • The Black-Scholes Model
  • Market Microstructure and Trading Strategies

• Probability Theory in Finance

  • Stochastic Processes
  • Brownian Motion and Random Walks
  • Probability Distributions and Their Applications

• Risk Management and Quantification

  • Value-at-Risk (VaR) Models
  • Portfolio Optimization
  • Risk Metrics and Stress Testing

• Stochastic Calculus and Financial Models

  • Ito’s Lemma
  • Stochastic Differential Equations (SDEs)
  • The Black-Scholes Equation and its Applications

• Numerical Methods for Financial Modelling

  • Monte Carlo Simulation
  • Finite Difference Methods
  • Binomial Trees and Lattice Methods

• Asset Pricing and Models

  • The Capital Asset Pricing Model (CAPM)
  • Arbitrage Pricing Theory (APT)
  • Multi-Factor Models

• Time Series Analysis in Finance

  • Forecasting Financial Time Series
  • Autoregressive Models (AR, ARMA, GARCH)
  • Volatility Modeling and Forecasting

• Algorithmic and High-Frequency Trading

  • Algorithms for Trading and Market Making
  • Quantitative Trading Strategies
  • Risk Management in Algorithmic Trading

• Advanced Topics in Quantitative Finance

  • Credit Risk Models
  • Exotic Options and Complex Derivatives
  • Multi-Asset Models and Portfolio Theory

• Applications and Case Studies

  • Real-World Applications of Quantitative Models
  • Case Studies in Risk Management, Derivatives Trading, and Investment Strategies

• Conclusion and Future Directions

  • Emerging Trends in Quantitative Finance
  • The Future of Algorithmic Trading and AI in Finance
  • Career Paths in Quantitative Finance

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