This paper studies the self-weighted least squares estimator (SWLSE) of the ARMA model with GARCH noises. It is shown that the SWLSE is consistent and asymptotically normal when the GARCH noise does not have a finite fourth moment. Using the residuals from the estimated ARMA model, it is shown...

We study the out-of-sample predictability of the real price of crude oil using forecast combinations constructed from several individual predictors. We find that forecasts of themonthly average price of oil are more accurate than the no-change forecast at horizons ranging from 1 to 24 months...

The paper presents a Bayes analysis of an autoregressive-moving average model and its components based on exact likelihood and weak priors for the parameters where the priors are defined so that they incorporate stationarity and invertibility restrictions naturally. A Gibbs-Metropolis hybrid...

An approach to the modelling of volatile time series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the stationary distribution of the time series and quantiles of the distribution of a...

The paper presents a Bayes analysis of an autoregressive-moving average model and its components based on exact likelihood and weak priors for the parameters where the priors are defined so that they incorporate stationarity and invertibility restrictions naturally. A Gibbs-Metropolis hybrid...

The purpose of this paper is to compare the accuracy of the three types of models: Autoregressive Integrated Moving Average (ARIMA) models, Holt-Winters models and Neural Network Auto-Regressive (NNAR) models in forcasting the Harmonized Index of Consumer Prices (HICP) for the countries of...

The Standard Generalised Autoregressive Conditionally Heteroskedastic (sGARCH) model and the Functional Generalised Autoregressive Conditionally Heteroskedastic (fGARCH) model were applied to study the volatility of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model, which...

An approach to the modelling of volatile time series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the stationary distribution of the time series and quantiles of the distribution of a...

This paper used cross-sectional aggregation as the inspiration for a model with long-range dependence that arises in actual data. One of the advantages of our model is that it is less brittle than fractionally integrated processes. In particular, we showed that the antipersistent phenomenon is...

The purpose of this research paper is to understand the MCX Comdex index, the paper also attempts to forecast the index level, the level of index reflects the change in commodity prices. The index is based on commodity futures prices of an exchange. To study the same daily closing prices of...

The most important assumption about time series and econometrics data is stationarity. Therefore, this study focuses on behaviors of some parameters in stationarity of autoregressive (AR) and moving average (MA) models. Simulation studies were conducted using R statistical software to...

In Afghanistan, the novel coronavirus disease 2019 (COVID-19) is spreading rapidly. Currently, we are in third wave of pandemic, in Afghanistan. And recently government of Afghanistan recorded the highest confirmed cases since the start of pandemic. In order to prepare ourselves and make right...

This study examined econometric modelling and forecasting foreign direct investment inflows in Nigeria over the next decade using Box-Jenkins ARIMA model approach. The scope of the study is from 1970 to 2020. The correlogram show that the net foreign direct investment inflow in Nigeria is...

Smart home is an important application of Internet of Things (IoT) that utilizes the Internet to monitor and control appliances in a home automation system by providing security, energy efficiency, low operating costs, convenience etc. The installation of smart products allows the user to...

The first official data releases of quarterly real GDP for the euro area are published about eight weeks after the end of the reference quarters. Meanwhile, ongoing economic developments must be assessed from various, more readily available, monthly indicators. We examine in the context of...

This study investigates the effectiveness of six of the key international indices in estimating Saudi financial market (TADAWUL) index (TASI) movement. To investigate the relationship between TASI and other variables, six equations were built using two independent variables of time and...

A two-stage simulation-based framework is proposed to derive Identification Robust confidence sets by applying Indirect Inference, in the context of Autoregressive Moving Average (ARMA) processes for finite samples. Resulting objective functions are treated as test statistics, which are inverted...

We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, which can heavily impact health, economics and finance. The model is a Poisson autoregression of the daily new observed cases, and can reveal whether contagion has a trend, and where is...

We test whether the selected cryptocurrencies exhibit long memory behavior in returns and volatility. We use data on five most traded cryptocurrencies: Bitcoin, Litecoin, Ethereum, Bitcoin Cash, and XRP. Using recent tests of long memory developed against persistent and nonlinear alternatives,...

Many forms of the ARIMA (auto-regressive integrated moving average) modeling method are used across risk management and specifically within PPNR (Pre-Provision Net Revenue) for CCAR (Comprehensive Capital Analysis and Review) and DFAST (Dodd-Frank Act Stress Testing). The ARIMA method allows for...

This paper aims to obtain an appropriate ARIMA model for the Sudan GDP using the Box- Jenkins methodology during the period 1960-2018 the various ARIMA models with different order of autoregressive and moving-average terms were compared. The appropriate model for Sudan is an ARIMA (1,1,1), the...

In developing countries with an unstable economic system, permanent fluctuation in historical data is always a concern. Recognizing dependency and independency of variables are vague and proceeding a reliable forecast model is more complex than other countries. Although linearization of...

This paper proposes a hybrid modelling approach for forecasting returns and volatilities of the stock market. The model, called ARFIMA-WLLWNN model, integrates the advantages of the ARFIMA model, the wavelet decomposition technique (namely, the discrete MODWT with Daubechies least asymmetric...

For the large family of ARMA models with variable coefficients we provide an explicit and computationally tractable solution representation, which yields the fundamental properties of such processes, including the Wold-Cramer decomposition and the covariance structure. These results are founded...

We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19. The model is a Poisson autoregression, and can reveal whether contagion has a trend, and where is each country on that trend. Model results are presented from the observed series of China,...

Estimating the exchange rate is considered a key tool for economic planning and reaching economic stability. This study aims to reach the best model for predicting exchange rates of Iraqi Dinar against the U.S. dollar in the period (2008-2017). For this purpose the following methods have been...

We propose moving average threshold heterogeneous autoregressive (MAT-HAR) models as a novel combination of heterogeneous autoregression (HAR) and threshold autoregression (TAR). The MAT-HAR has multiple groups of lags of a target series, and a threshold term can appear in each group. The...

This paper offers a multifaceted perspective of the literature on long memory. Although the research on long memory has played an instrumental role in elevating the level of scholarly discourse on market efficiency, the authors believe that the issue of the prevalence of long memory or lack...