Financial Forecasting - Time Series Models Essay examples

2287 Words Feb 5th, 2013 10 Pages
Time Series Models for Forecasting New One-Family Houses Sold in the United States
Introduction
The economic recession felt in the United States since the collapse of the housing market in 2007 can be seen by various trends in the housing market. This collapse claimed some of the largest financial institutions in the U.S. such as Bear Sterns and Lehman Brothers, as they held over-leveraged positions in the mortgage backed securities market. Credit became widely available to unqualified borrowers during the nineties and the early part of the next decade which caused bankers to act predatorily in their lending practices, as they could easily sell and package subprime mortgage loans on leverage. This act caused a bubble that would later
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Figure 2
12-period plot of autocorrelation functions (ACF) for NHS

Now that we have verified the presense of a trend in the data we will look to verify the seasonality we saw earlier represented by regularly reoccurring fluctuations in the levels of data in accordance with the calendar seasons. To do this we will use an autocorrelation function for the first differenced new home sales data. We will use a larger sample, in this case 24 months, so that we can see the regularly reoccurring fluctuations from one year to the next. When we look at the graph in Figure 3 we notice great increases with lag 12 and lag 24. The jumps seen in lags 12 and 24 confirms the presense of seasonality as they are above the upper limit representing statistical significance.
Figure 3
24-period plot of autocorrelation functions (ACF) for first differenced NHS

Time Series and Regression Models for New One-Family Houses Sold
Since the NHS data has been shown to have trend and seasonality we will evaluate the data using four different time series models and compare the results of each to see which model is the most accurate. The models we are going to use are the Modified Naïve model, Winters Exponential Smoothing model, Time Series Decomposition, and Autoregressive Integrated Moving Average (ARIMA).
We will also test a multiple regression model to attempt to forecast future NHS, while taking
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