The purpose of this paper is to verify the long-range correlation between the stock markets of the largest economies in the world and the respective exchange rate with the USD. According to theory, a negative correlation is expected, meaning that an increase in the return of one of the assets...

Consider using the simple moving average (MA) rule of Gartley (1935) to determine when to buy stocks, and when to sell them and switch to the risk-free rate. In comparison, how might the performance be affected if the frequency is changed to the use of MA calculations? The empirical results show...

In this paper, we investigated the profitability of technical analysis as applied to the stock markets of the BRICS member nations. In addition, we searched for evidence that technical analysis and fundamental analysis can complement each other in these markets. To implement this research, we...

This paper focuses on the estimation and predictive performance of several estimators for the time-space dynamic panel data model with Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. A dynamic spatial Generalized Moments (GM) estimator is proposed which combines the...

In this research, a taxonomy of known electricity demand forecasting techniques is presented based on extensive empirical studies. In addition, a decision strategy for selecting an electricity demand forecasting method has been presented. The strategy has been formulated based on an eight-factor...

Parametric production frontier functions are frequently used in stochastic frontier models, but there do not seem to be any empirical test statistics for its plausibility. To bridge the gap in the literature, we develop two test statistics based on local smoothing and an empirical process,...

A method is proposed for forecasting composite time series such as the market shares for multiple brands. Its novel feature is that it relies on multi-series adaptations of exponential smoothing combined with the log-ratio transformation for the conversion of proportions onto the real line. It...

To achieve sustainable development, massive changes towards fostering a clean and pollution-reducing industrial sector are quintessential. The textile industry has been one of the main contributors to water pollution all over the world, causing more than 20% of the registered levels of water...

This paper features an analysis of major currency exchange rate movements in relation to the US dollar, as constituted in US dollar terms. Euro, British pound, Chinese yuan, and Japanese yen are modelled using a variety of non-linear models, including smooth transition regression models,...

In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally...

Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the...

We assess the out-of-sample forecasting performance of eight models on Indian real exports and imports. The results, in large part show only a slight increase or no clear increase in India's international trade. However, the results are very robust when comparing the predictions in terms of...

This article discusses Windle and Carvalho's (2014) state-space model for observations and latent variables in the space of positive symmetric matrices. The present discussion focuses on the model specification and on the contribution to the positive-value time series literature. I apply the...

Exponential smoothing models are an important prediction tool in macroeconomics, finance and business. This paper presents the analytical forecasting properties of the random coefficient exponential smoothing model in the multiple source of error framework. The random coefficient state-space...

Exponential smoothing is one of the most popular forecasting methods. We present a method for bootstrap aggregation (bagging) of exponential smoothing methods. The bagging uses a Box-Cox transformation followed by an STL decomposition to separate the time series into trend, seasonal part, and...

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary...