Statistics for finance. (2018)

• Record Type: Book
• Further Information: Note: Erik Lindstrom, Henrik Madsen, Jan Nygaard Nielsen.
• Authors: Lindström, Erik; Madsen, Henrik, 1955-; Nielsen, Jan Nygaard
• Contents: Introduction; Introduction to financial derivatives; Financial derivatives—what’s the big deal?; Stylized facts; Overview Fundamentals; Interest rates; Cash flows; Continuously compounded interest rates; Interest rate options: caps and floors Discrete-Time Finance ; The binomial one period model; The one period model; The multi period model Linear Time Series Models ; Introduction; Linear systems in the time domain; Linear stochastic processes; Linear processes with a rational transfer function; Autocovariance functions; Prediction in linear processes Non-Linear Time Series Models ; Introduction; The aim of model building; Qualitative properties of the models; Parameter estimation; Parametric models; Model identification; Prediction in non-linear models; Applications of non-linear models Kernel Estimators in Time Series Analysis ; Non-parametric estimation; Kernel estimators for time series; Kernel estimation for regression; Applications of kernel estimators Stochastic Calculus ; Dynamical systems; The Wiener process; Stochastic Integrals; Itō stochastic calculus; Extensions to jump processes Stochastic Differential Equations; Stochastic differential equations; Analytical solution methods; Feynman–Kac representation; Girsanov measure transformation Continuous-Time Security Markets ; From discrete to continuous time; Classical arbitrage theory; Modern approach using martingale measures; Pricing; Model extensions; Computational methods Stochastic Interest Rate Models ; Gaussian one-factor models; A general class of one-factor models; Time-dependent models; Multifactor and stochastic volatility models The Term Structure of Interest Rates ; Basic concepts; The classical approach; The term structure for specific models; Heath–Jarrow–Morton framework; Credit models; Estimation of the term structure—curve-fitting Discrete-Time Approximations ; Stochastic Taylor expansion; Convergence; Discretization schemes; Multilevel Monte Carlo; Simulation of SDEs Parameter Estimation in Discretely Observed SDEs ; Introduction; High frequency methods; Approximate methods for linear and non-linear models; State dependent diffusion term; MLE for non-linear diffusions; Generalized method of moments (GMM); Model validation for discretely observed SDEs Inference in Partially Observed Processes ; Introduction; The model; Exact filtering; Conditional moment estimators; Kalman filter; Approximate filters; State filtering and prediction; The unscented Kalman filter; A maximum likelihood method; Sequential Monte Carlo filters; Application of non-linear filters Appendix A: Projections in Hilbert Spaces; Appendix B: Probability Theory Bibliography Problems appear at the end of each chapter.
• Publisher Details: Place of publication not identified : Chapman and Hall/CRC
• Publication Date: 2018
• Extent: 1 online resource (384 pages), (63 illustrations)
• Subjects: 332.015195; Finance -- Statistical methods
• Languages: English
• ISBNs: 9781315360218; 1315360217
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.