Predicting Housing Price in Beijing Using ARIMA Models Open Access

Gao, Yue (Spring 2022)

Permanent URL: https://etd.library.emory.edu/concern/etds/7p88ch78f?locale=en
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Abstract

With the rapid increase in housing demand, more and more homebuyers in Beijing tend to purchase housing properties without collecting enough information. To provide a solution for information asymmetry and high information acquiring cost in the housing market, this study focusses on the housing price forecasting. Reliable forecasts could provide valuable information for homebuyers and sellers and help them better understand the local housing market. This paper seeks to predict the housing price in Beijing using ARIMA models due to the model’s demonstrated outperformance in predicting time series data accuracy. In addition, district-by-district housing price prediction is also performed.

 

Table of Contents

1. Introduction................................................................................................................................. 1

2. Research Methodology ............................................................................................................... 3

2.1. Background: ARIMA Model Approach.............................................................................................3

2.2. Workflow Chart..................................................................................................................................5

2.3. Evaluation Criteria of ARIMA models ..............................................................................................6

3. Data and Data Pre-Processing..................................................................................................... 7

3.1. Data ....................................................................................................................................................7

3.2. Data Pre-Processing ...........................................................................................................................8

4. Result ........................................................................................................................................ 14

4.1. RQ1: What is the performance of ARIMA in predicting housing price in Beijing?........................14

4.2. RQ2: Will the forecasting performance differ from district to district?...........................................18

5. Discussion ................................................................................................................................. 20

5.1. Limitations of Study .........................................................................................................................20

5.2. ARIMA Model Performance............................................................................................................21

6. Conclusion ................................................................................................................................ 24

References..................................................................................................................................... 25 Appendix....................................................................................................................................... 27 

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