Forecasting Models, Computational and Bayesian Models
Buch, Englisch, 195 Seiten, Format (B × H): 144 mm x 224 mm, Gewicht: 401 g
ISBN: 978-0-230-28365-7
Verlag: Springer Nature B.V.
This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
PART I: FORECASTING MODELS The Yield of Constant Maturity 10-Year U.S. Treasury Notes: Stumbling Towards an Accurate Forecast; R.Weißbach, W.Poniatowski & G.Zimmermann Estimating the APT Factor Sensitivities Using Quantile Regression; Z.Adams, R.Füss, P.Grüber, U.Hommel & H.Wohlenberg Financial Risk Forecasting with Non-Stationarity; H.K.K.Tung & M.C.S.Wong International Portfolio Choice: A Spanning Approach; B.Tims & R.Mahieu Quantification of Risk and Return for Portfolio Optimization: A Comparison of Forecasting Models; N.S.Thomaidis, E.Roumpis & V.Karavas Hedging Effectiveness in The Index Futures Market; L.Copeland& Y.Zhu PART II: COMPUTATIONAL AND BAYESIAN METHODS A Bayesian Framework for Explaining the Rate Spread on Corporate Bonds; O.Chakroun & R.Ben-Abdallah GARCH, Outliers and Forecasting Volatility; P.H.Franses & D.van Dijk Is There a Relation between Discrete Time GARCH and Continuous Time Diffusion Models?; T.Bali The Recursive Fitting of Multivariate Complex Subset ARMA Models in Financial Econometrics; J.Penm & R.D.Terrell




