Pariwisata dianggap sebagai suatu aset yang strategis untuk mendorong pembangunan pada wilayah-wilayah tertentu mempunyai potensi objek wisata. Faktor-faktor mempengaruhi wisatawan mancanegara berkunjung ke wilayah negara, diantaranya nilai tukar mata uang, inflasi disuatu kunjungan wisatawan, dan letak geografis negara. Peningkatan tidak terduga jumlah ini dapat berdampak kesulitan bagi para p...

This paper proposes a hybrid modelling approach for forecasting returns and volatilities of the stock market. The model, called ARFIMA-WLLWNN integrates advantages ARFIMA wavelet decomposition technique (namely, discrete MODWT with Daubechies least asymmetric filter) artificial neural network LLWNN network). model develops through two-phase approach. In phase one, improves accuracy network, res...

In this article we derive conditions which ensure the non-negativity of the conditional variance in the Hyperbolic GARCH(p, d, q) (HYGARCH) model of Davidson (2004). The conditions are necessary and sufficient for p ≤ 2 and sufficient for p > 2 and emerge as natural extensions of the inequality constraints derived in Nelson and Cao (1992) for the GARCH model and in Conrad and Haag (2006) for th...

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty into account when making inferences on quantities of interest. Our methods are then used to investigat...

GARCH-type models have been highly developed since Engle [1982] presented ARCH process 30 years ago. Different kinds of GARCH-type models are applicable to different kinds of research purposes. As documented by many literatures that short-memory processes with level shifts will exhibit properties that make standard tools conclude long-memory is present. Therefore, in this paper, we want to fore...

Strong coupling between values at different times that exhibit properties of long range dependence, non-stationary, spiky signals cannot be processed by the conventional time series analysis. The autoregressive fractional integral moving average (ARFIMA) model, a fractional order signal processing technique, is the generalization of the conventional integer order models—autoregressive integral ...

ARFIMA models generated an enormous amount of interest in the literature about three decades ago. However, this interest vaned after Granger (1999) showed that an ARFIMA process might have stochastic properties that do not mimic the properties of the data at all. The empirical results of our research in which we used exchange rate data for the analysis, show that a variant of an ARFIMA process ...

2 1 1 =0 | | d t t t p p q q d d k k t () () ()(1) () = () (0) () () (1) (1) = () ())(+ 1) () () 0 5 1. Fractionally integrated timeseries and ARFIMA modelling 1 This presentation of ARFIMA modelling draws heavily from Baum and Wiggins (2000). The model of an autoregressive fractionally integrated moving average process of a timeseries of order , denoted by ARFIMA , with mean , may be written u...