Aplikasi Metode Ekonometri (ARCH, GARCH, EGARCH, TARCH, EMA, CARR) di Eviews dalam Peramalan Volatilitas Harga Saham

Penelitian tentang peramalan volatilitas harga saham di pasar saham telah banyak dilakukan di berbagai negara dengan berbagai metode ekonometrika (ARCH, GARCH, EGARCH, TARCH, EMA, CARR) yang ada di program Eviews. Penelitian-penelitian di Evews, dapat juga dilakukan dengan metode moving average (EMA), random walk (RW), historical average, moving average (MA), auto regression (AR), ARMA, ARIMA, simple regression, exponential smoothing, exponentially weighted moving average (EMA). Namun penelitian-penelitian tersebut harus dicari dahulu metode ekonometrika yang cocok sehingga ditemukan metode yang paling baik untuk meramal volatilitas.

Penelitian-penelitian yang telah dilakukan sebelumnya mengenai peramalan volatilitas dikutip dari Yu (2002), diantaranya: Baca lebih lanjut

Daftar Referensi Buku Statistik dan Buku Aplikasi Software Statistik ( SPSS LISREL AMOS PLS SAS STATA SPLUS R )

Berikut adalan sebagian Daftar Buku-Buku Aplikasi Software Statistik ( SPSS LISREL AMOS PLS SAS STATA SPLUS R )

  • Advances in Clinical Trial Biostatistics by Nancy L. Geller
  • Analysis of Incomplete Multivariate Data by Joe Schafer
  • Analysis of Messy Data, Volume III: Analysis of Covariance by George A. Milliken Dallas E. Johnson
  • Analysis of Pretest-Posttest Designs by Peter L. Bonate
  • Applied Nonparametric Statistical Methods, Third Edition by Peter Sprent Nigel Charles Smeeton
  • Applied Statistical Designs for the Researcher by Daryl S Paulson
  • Bayes and Empirical Bayes Methods for Data Analysis, Second Edition by Bradley P Carlin Thomas A Louis
  • Clinical Trials in Oncology, Second Edition by Stephanie Green Jacqueline Benedetti John Crowley
  • Contemporary Statistical Models for the Plant and Soil Sciences by Oliver Schabenberger Francis J Pierce
  • Contingency Table Approach to Nonparametric Testing by A J.C.W. Rayner D.J. Best
  • CRC Standard Probability and Statistics Tables and Formulae by Daniel Zwillinger Stephen Kokoska
  • Data Mining Using SAS Applications by George Fernandez
  • Design and Analysis of Cross-Over Trials, Second Edition by Byron Jones M.G. Kenward
  • EM Algorithm and Related Statistical Models, by The Michiko Watanabe Kazunori Yamaguchi
  • Environmental Statistics with S-PLUS by Steven P. Millard Nagaraj K. Neerchal
  • Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models by Anders Skrondal Sophia Rabe-Hesketh (2 copies)
  • Group Sequential Methods with Applications to Clinical Trials by Christopher Jennison Bruce W. Turnbull
  • Handbook of Parametric and Nonparametric Statistical Procedures, Second Edition by David J Sheskin
  • Handbook of Statistical Analyses Using SAS, Second Edition by Geoff Der Brian S. Everitt
  • Handbook of Statistical Analyses Using SPSS, A Sabine Landau Brian S Everitt
  • Handbook of Statistical Analyses using S-Plus, Second Edition by Brian S. Everitt
  • Handbook of Statistical Analyses Using Stata, Second Edition by Sophia Rabe-Hesketh Brian S. Everitt
  • Hierarchical Modeling and Analysis for Spatial Data by Sudipto Banerjee Bradley P Carlin Alan E Gelfand
  • Introduction to Generalized Linear Models, Second Edition by Annette J. Dobson
  • Measures of Interobserver Agreement by Mohamed M. Shoukri
  • Multidimensional Scaling, Second Edition Trevor F. Cox M.A.A. Cox
  • Sample Size Calculations in Clinical Research by Shein-Chung Chow Jun Shao Hansheng Wang
  • Sampling Methodologies with Applications by Poduri S.R.S. Rao
  • Statistical and Econometric Methods for Transportation Data Analysis by Simon P Washington Matthew G Karlaftis Fred L Mannering
  • Statistics in Drug Research: Methodologies and Recent Developments by SHEIN-CHUNG CHOW JUN SHAO
  • Statistical Methods for Health Sciences, Second Edition by Mohamed M. Shoukri Cheryl A. Pause
  • Statistics in the 21st Century by Adrian E. Raftery Martin A. Tanner Martin T. Wells
  • Theory of the Design of Experiments, The by Sir David R. Cox Nancy Reid
  • Time-Series Forecasting by Chris Chatfield
  • Topics in Modeling of Clustered Data by Marc Aerts Geert Molenberghs Helena Geys Louise Ryan

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