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 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 world economy has been struck by Covid-19 the same way people are struck by a lightning, fast and without warning, leaving nations out to dry on little to no reserves on their crucial supply side. Consequently, over the past year, economies shrunk, production drastically diminished, and...

Coronavirus disease (COVID-19) is a severe ongoing novel pandemic that has emerged in Wuhan, China, in December 2019. As of October 13, the outbreak has spread rapidly across the world, affecting over 38 million people, and causing over 1 million deaths. In this article, I analysed several time...

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 attempts to forecast imports of India using Auto Regressive Moving Average (ARMA) and Auto Regressive Integrated Moving Average (ARIMA) models of forecasting. Using data for 1971-72 to 2014-15, imports of India are forecasted for imminent 5 years starting from 2015-16 to 2019-2020....

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 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...

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...

This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physical form. The trade of gold futures relates to seasons, festivity, and...

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...

Many investors in order to predict stock prices use various techniques like fundamental analysis and technical analysis and sometimes rely on the discussions provided by various stock market analysts. ARIMA is a part of time-series analysis under prediction algorithms, and this paper attempts to...

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...

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...

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...

Annual time series data is used to forecast GDP per capita using the Box-Jenkins Auto-regressive-Integrated Moving-Average (ARIMA) model for the Egyptian and Saudi Arabian economies. The fitted ARIMA model is tested for per capita GDP forecasting of Egypt and of Saudi Arabia for the next ten...

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...

The outbreak of COVID-19 has brought the world economy at standstill which brings huge challenges to major affected countries. The impact of this disease on economy is highly uncertain putting policymakers in difficult situation to formulate appropriate policy in a short time. India being 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 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...

This paper derives a new method for comparing the weak-form efficiency of markets. The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process. For...

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...