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 volatile to get an accurate picture of economic changes, so four-week moving averages are typically used for the initial claims metric.

Initial jobless claims measure the number of filings for state jobless benefits. This report provides a timely, but often misleading, indicator of the direction of the economy, with increases (decreases) in claims potential signaling slowing (accelerating) job growth. On a week-to-week basis, claims are quite volatile, and many analysts therefore track a four week moving average to get a better sense of the underlying trend. It typically takes a sustained move of at least 30K in claims to signal a meaningful change in job growth.

Goal: The goal of this project is to model seasonally adjusted initial claims and then predict the initial claims for the future because it is used by financial institutions, especially in currency trading, to get a better idea about the direction of the United States economy.

Note: The data is acquired from the Federal Reserve Economic Data website: http://research.stlouisfed.org/fred2/series/ICSA

II. Exploratory Data Analysis

The plot of the time series