# Essay on Time Series Arima Project

2779 Words Nov 10th, 2014 12 Pages
Predicting Initial Claims Using ARIMA models

I. Introduction

Initial claims is a measure of the number of jobless claims filed by individuals seeking to receive state jobless benefits. This number is watched closely by financial analysts because it provides insight into the direction of the economy. Higher initial claims correlate with a weakening economy.

According to Investopedia.com, the strength of a nation's economy will have an impact on the appreciation or depreciation of its currency against other major currencies. Therefore, forex traders typically look at the initial claims figure as part of their analyses when assessing a currency's prospects for the immediate future. Generally speaking, week-by-week numbers are too
Because no clear order can be seen from these plots, I decided to take the first difference of the data.

Now, looking at the first difference of the weekly initial unemployment claims, the data seems to be a little smoother but still contains some outliers. Now, there seems to be a more discernible order in the data, and once again, it does not follow a white noise process as seen by the ACF and PACF plots.

I put these plots again just so that the plots can be a little bit more visible to see the reason behind why I chose the models below. III. Model Estimation

From the ACF and PACF plots, I surmise that the data can fit a number of ARMA models: * ARMA(0,1) MA(1) * ARMA(0,3) MA(3) * ARMA(10,0) AR(10) * ARMA(12,0) AR(12) * ARMA(14,0) AR(14) * ARMA(19,0) AR(19) * ARMA(10,1) * ARMA(10,3) * ARMA(12,1) * ARMA(12,3) * ARMA(14,1) * ARMA(14,3) * ARMA(19,1) * ARMA(19,3)

Now, I used R to perform some preliminary estimation of the parameters of the above models to the differenced data. After doing this estimation, some of the models I retained and some I rejected based on the ratio test of significance of the coefficients. The reasons are: * ARMA(0,1) MA(1) – retained * ARMA(0,3) MA(3) – retained * ARMA(10,0) AR(10) – retained * ARMA(12,0) AR(12) – retained * ARMA(14,0)

## Related Documents

• ###### Mama Essay

organisational excellence for building a knowledge-based society through training, systems development and best practices; * Nurturing innovative and creative culture through QE 5S. 1.2.5 ORGANIZATION’S LOGO Figure 1: JGSO DHRM Logo CHAPTER 2 PROJECT DEFINITION 2.1 PROBLEM STATEMENT Each month, Johor Government Secretary Office, Department of Human Resource Management (JGSO DHRM) spends a huge amount of money for courses, induction, training, development programmes, team building, seminars…

Words: 7686 - Pages: 31
• ###### Wind Speed Analysis of Cox's Bazar Using Ann Essay

beforehand. Wind speed is a random variable depending on meteorological variables like atmospheric pressure,temperature,relative humidity & such. Methods that are currently being applied to predict wind speed are Statistical, Intelligent systems, Time series, Fuzzy logic, neural networks.Our focus will be on using Artificial Neural Network to predict the wind speed in daily basis in this report. Chapter 1 1.1 Introduction Bangladesh has a 724 lm long coastal area where south-westerly…

Words: 4021 - Pages: 17
• ###### Essay on Mutual Funds

buying pressure. The longer the white candlestick, the further the close is above the open. This indicates that prices increased considerably from open to close and buyers were aggressive. In other words, the bulls are kicking the bears’ butts big time! Long black (filled) candlesticks show strong selling pressure. The longer the black candlestick, the further the close is below the open. This indicates that prices fell a great deal from the open and sellers were aggressive. In other words, the…

Words: 13219 - Pages: 53