In recent years, graphics processing units have made parallel processing affordable with the price of personal desktop computers. This report investigates the computational aspects of calculating simple moving average and exponential moving average operations, two of the most popular financial indicators. In this report, we also investigate the usage of GPU to run artificial neural network as a...

We are interested in recurrent disaster forecasts; these are events such as annual cyclones in the Caribbean, earthquakes along the Ring of Fire and so on. These crises, even smallor medium-sized, are, in fact, critical for the emergency response of humanitarian organizations inasmuch as the sum of casualties and losses attained are as deadly as those that are considered exceptional. The aim of...

We study the autocorrelation structure and the spectral density function of aggregates from a discrete-time process. The underlying discrete-time process is assumed to be a stationary AutoRegressive Fractionally Integrated Moving-Average (ARFIMA) process, after suitable number of differencing if necessary. We derive closed-form expressions for the limiting autocorrelation function and the norma...

Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of dollars to economy. The main reasons of major percentage of traffic congestion are the incidents. Road accidents continue to increase in digital age. There are many reasons for road ...

With the increasing competition in the telecommunications industry, the operators try their best to increase telecom income via various measures, one of which is to set an amount of income as a goal to make the encouragement. Since accurate forecast of income plays an important role in income target setting, this paper builds a time series Autoregressive Integrated Moving Average Model (ARIMA) ...

We examine recursive out-of-sample forecasting of monthly postwar U.S. core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading indicators associated with macroeconomic activity and monetary conditions for forecasting horizons up to two years....

This paper develops a general asymptotic theory for the estimation of strictly stationary and ergodic time series models. Under simple conditions that are straightforward to check, we establish the strong consistency, the rate of strong convergence and the asymptotic normality of a general class of estimators that includes LSE, MLE, and some M-type estimators. As an application, we verify the a...

and Applied Analysis 3 is the order of regular differences and φ(B) and θ(B) are, respectively, defined as follows φ (B) = 1 − φ 1 B − φ 2 B 2 − ⋅ ⋅ ⋅ − φ p B p θ (B) = 1 − θ 1 B − θ 2 B 2 − ⋅ ⋅ ⋅ − θ q B q . (5) Random errors, ε t , are assumed to be independently and identically distributed with a mean of zero and a constant variance of σ, and the roots of φ(x) = 0 and θ(x) = 0 all lie outsid...