BDS ANFIS ANFIS ARMA

Transcription

1 * MGN G7 C5 C58 C53 JEL

2 3 7 TAR 6 ARCH Chaos Theory Deterministic 3 Exponential Smoothing Autoregressive Integrated Moving Average 5 Autoregressive Conditional Heteroskedasticity 6 Bilinear 7 Threshold Auto Regressive

3 Zhang and Hu Artificial Neural Network 3 Prtugal Unobserved Component Models 5 Church and Curram 6 Dimension Correlation

4 Generalized Auto Regresive Conditional Heteroskedasticity Adaptive Neuro Fuzzy Inference System 3 Tully and lucey Threshold 5 Exponetial 6 Dunis and Nattani 7 Quantitive 8 Nearest Neighbors 9 Correct Directional Change 0 Risk Adjusted Return Parisi and Diaz Rooling Neural Network

5 Fahimifard Yayar 3 Levenberg Marquardt Algorithm Takagi Sugeno

6 3 q d p p p, q p, q q 3 p, q = ~ 0, 008 q p p, d, q 3 98 ARCH ARCH Volatility Clustering Engel 3 Bollerslev

7 ARCH E ARCHM p, q ARCHp I 986 ARCHq = + + q 986 ARCH p q p, q 00 = ARCH in Mean Model Exponential 3 Integrated Johnston and Scott 5 Bouchad and Matacz 6 Soft Computing

8 TAR ARCH =,, i t f = w i b i0 b 0 w ij Exponential Smoothing Input Pattern

9 IID DBS, =,,, 6 m m,t W m,t W Scheinnkman, Dechert & Brock

10 =H 0 =H 0 =H 0 =H =H =H 39 Z %0 6 %5 Z 6

11 World Gold Council wwwgoldorg Training Set 3 Test Set Out of sample

12 Skewness Kurtosis

13 5 p, d, q 986 t MA AR 0 9 AR 0, 9 5 Granger and Newbold Augmented DickeyFuller test

14 AR MA 5

15 5, 6, 6 35

16 5 0 M= M=3 M= M=5 M=

17 Matlab Sugeno fuzzy inference

18 6 99 MAE 5 TIC RMSE MAPE = 7 = 00 8 = 9 = Hykin Root Mean Squared Error RMSE 3 Mean Absolute Error MAE Mean Absolute Percentage Error MAPE 5 Theil inequality coefficient TIC 6 Brooks 7 Gerlow, Irowin and Liu

19 = Z t+s = If y t+s *f t,s >0 Z t+s =0 Otherwise T T t s f t,s t Y t = Z t+s = If y t+s y t f t,s y t >0 Z t+s =0 Otherwise 3 MGN Leitch and Tanner Pesaran and Timmerman 3 Correct Sign Predictions Correct Direction Change Predictions

20 00 e,t e,t D t S t =, +, =,,, =, = 5 x p x p x m MGN = 6 MGN N D t S t sd 00 N t 5 CSP CDCP TIC MAPE MAE RMSE , Diebold and Mariano

21 MGN ARAM 7

22 CDCP CSP TIC MAPE MAE RMSE MGN

23 ANN Bollerslev, T 986 Generalized Autoregressive Conditional Heteroskedasticity Journal of Economics; Brock, W A, W Dechert, J Scheinkman 987 A Test for Independence Based on the Correlation Dimension Working paper, University of Winconsin at Madison, University of Houston, and University of Chicago 7 Brooks, C 008 Introductory Econometrics for Finance Second Edition, Cambridge University Press 8 Church, k b, Curram S P 996 Forecasting consumers' expenditure A comparison between econometric and neural network models International Journal of Forecasting,,, Diebold F, Mariano R 00 Comparing predictive accuracy Journal of Business and Economic Statistics 0, 3 0 Engle F R 98 Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation Econometrica, Fahimifard, S M, Salarpour, M, Sabouhi, M, Shirzady, S 009 Application of to Agricultural Economic Variables Forecasting Case Study Poultry Retail Price, Artificial Intelligence, 657

24 Gerlow, M, Irwin, S, Liu, T 993 Economic Evaluation of Commodity Price Forecasting Models International Journal of Forecasting, Granger, C W J, Newbold, P 986 Forecasting economic time series Orlando Academic Press Gujarati D 008 Basic Econometrics 5 th Edition McGrawHill 5 Haykin, S 99, Neural Networks a Comprehensive Foundation Macmillan, New York 6 httpwwwgoldorg 7 Johnston k, Scott, E 000 Models and The Stochastic Process Underlying Exchange Rate Price Change Journal of Financial and Strategic Decisions, Vol pp 3 8 Leitch, G and Tanner, JE 99 Economic Forecast Evaluation Profits versus the Conventional Error Measures The American Economic Review AER, 83, Parisi, A, Parisi, F, Díaz, D 008 Forecasting gold price changes Rolling and recursive neural network models, Journal of Multinational Financial Management, Elsevier, vol 85, pages 7787, December 0 Pesaran, M H, Timmerman, A 99 A Simple Nonparametric Test of Predictive Performance journal of Business & Economic Statistics 0,, 665 Prtugal, N S 995, Neural networks versus time series Methods A Forecasting Exercises, th International Symposium on Forecasting, Sweden Tully, E, Lucey, B M 007 A power examination of the gold market Research in international business and finance, Yayar, M, Hekim, M, Yelmaz, V, Bakirci, F 0 A comparison of and techniques in the forecasting of electric energy consumption of Tokat province in Turkey Zarranezhad, M, Raoofi, A, kiyani, p 0 Evaluation and comparison of performance of and in forecasting the daily gold prices, The First international conference on econometrics and methods applications 5 Zhang, G, Hu, MY 998 Neural Network Forecasting of the British PoundUS Dollar Exchange Rate, International Journal of Management Science, Zhang, G, Hu, MY 00 A Simulation Study of Artificial Neural Networks for Nonliner Time Series Forecasting Comput Oper Res 8, pp Zhang, G, Hu, MY 00 Forecasting with Artificial Neural Networks The state of the Art, Neurocomputing 56,pp 05 3