Implementing Models in Quantitative Finance: Methods and Cases [electronic resource] /
Fusai, Gianluca.author.
Roncoroni, Andrea.author.
This book puts numerical methods into action for the purpose of solving concrete problems arising in quantitative finance. Part one develops a comprehensive toolkit including Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. The content originates from class notes written for courses on numerical methods for finance and exotic derivative pricing held by the authors at Bocconi University since the year 2000. Part two proposes eighteen self-contained cases covering model simulation, derivative valuation, dynamic hedging, portfolio selection, risk management, statistical estimation and model calibration. It encompasses a wide variety of problems arising in markets for equity, interest rates, credit risk, energy and exotic derivatives. Each case introduces a problem, develops a detailed solution and illustrates empirical results. Proposed algorithms are implemented using either Matlab® or Visual Basic for Applications® in collaboration with contributors.
Description based upon print version of record.
Includes bibliographical references (p. [573]-597) and index.
Methods -- Static Monte Carlo -- Dynamic Monte Carlo -- Dynamic Programming for Stochastic Optimization -- Finite Difference Methods -- Numerical Solution of Linear Systems -- Quadrature Methods -- The Laplace Transform -- Structuring Dependence using Copula Functions -- Problems -- Portfolio Selection: “Optimizing” an Error -- Alpha, Beta and Beyond -- Automatic Trading: Winning or Losing in a kBit -- Estimating the Risk-Neutral Density -- An “American” Monte Carlo -- Fixing Volatile Volatility -- An Average Problem -- Quasi-Monte Carlo: An Asian Bet -- Lookback Options: A Discrete Problem -- Electrifying the Price of Power -- A Sparkling Option -- Swinging on a Tree -- Floating Mortgages -- Basket Default Swaps -- Scenario Simulation Using Principal Components -- Parametric Estimation of Jump-Diffusions -- Nonparametric Estimation of Jump-Diffusions -- A Smiling GARCH.
This book puts numerical methods into action for the purpose of solving concrete problems arising in quantitative finance. Part one develops a comprehensive toolkit including Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. The content originates from class notes written for courses on numerical methods for finance and exotic derivative pricing held by the authors at Bocconi University since the year 2000. Part two proposes eighteen self-contained cases covering model simulation, derivative valuation, dynamic hedging, portfolio selection, risk management, statistical estimation and model calibration. It encompasses a wide variety of problems arising in markets for equity, interest rates, credit risk, energy and exotic derivatives. Each case introduces a problem, develops a detailed solution and illustrates empirical results. Proposed algorithms are implemented using either Matlab® or Visual Basic for Applications® in collaboration with contributors.
Public finance.
Economics, Mathematical .
Computer mathematics.
Partial differential equations.
Numerical analysis.
Public Economics.
Quantitative Finance.
Computational Mathematics and Numerical Analysis.
Partial Differential Equations.
Numerical Analysis.
Springer finance