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Köp båda 2 för 2114 krIntroduction (T. B. Fomby, D. Terrell). Remarks (R. Engle, C. Granger). Realized beta: persistence and predictability (T. G. and ersen, T.Bollerslev, F. X. Diebold, J. Wu). Asymmetric predictive abilities of nonlinearmodels for stock returns: evidence from density forecast comparison (Y. Bao, T.-H. Lee). Flexible seasonal time seriesmodels (Z. Cai, R. Chen). Estimation of long-memory time seriesmodels : a survey of different likelihood-based methods (N. Hang Chan, W. Palma). Boosting-based frameworks infinancial modeling : application to symbolic volatility forecasting (V. V. Gavrishchaka). Overlaying time scales infinancial volatility data (E. Hillebrand). Evaluating the fed model of stock price valuation: an out-of-sample forecasting perspective (D. W. Jansen, Z. Wang). Structural change as an alternative to long memory in financial time series (T. Leung Lai, H. Xing). Time series mean level and stochastic volatility modeling by smooth transition autoregressions: a bayesian approach (H. Freitas Lopes, E. Salazar). Estimating Taylor-type rules: an unbalanced regression? (P. L. Siklos, Mark E. Wohar). Bayesian inference on mixture-of-experts for estimation of stochastic volatility (A. Villagran, G. Huerta). A modern time series assessment of A statistical model for sunspot activity by C.W.J. Granger (1957) (G.Yoon). Comment on Yoon Paper ( C.W.J. Granger, KB). A new class of tail-dependent time seriesmodels and its applications in financial time series (Z. Zhang).