Title

Identifying Significant Predictors of Real Estate Price Increases: A Case Study in the California Central Valley

Poster Number

Withdrawn

Lead Author Affiliation

M.S. Business Analytics

Lead Author Status

Masters Student

Purpose

As prices of real estate have surged during the pandemic yet fallen in housing bubbles in the long history of real estate, analysts have struggled to predict whether or not an investment will create positive returns in the long-run. With the introduction of big data and machine learning, recent studies have introduced using statistical techniques to predict housing prices or investment returns given certain parameters. Most studies are focused on predicting price or potential investment risks, whereas this paper educates the intended audience on what predictors (out of the information provided by Zillow) are the most significant for a house selling for above original listing price. The data of the study was collected from Zillow’s recent housing sales in the Central Valley and was used to identify which predictors (number of rooms, square footage, etc.) had the most impact on list prices as well as price adjustments. The research describes which predictors dictate a house selling for above listing price in the current housing climate to give sellers as well as buyers an understanding on their financial gains/investment. The article concludes that either the original list price of the house (the intercept) or the square footage was the most significant predictor for a house selling above list price and thus, returning positive yield on the original investment.

Method

Data will be collected using a website scraper built in Python to obtain information from housing listings in the Central Valley. The listings will consist of houses that recently sold and will include original list price as well as final sale price.

Location

William Knox Holt Memorial Library and Learning Center, University of the Pacific, 3601 Pacific Ave., Stockton, CA 95211

Format

Poster Presentation

Poster Session

Afternoon

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Apr 30th, 1:00 PM Apr 30th, 3:00 PM

Identifying Significant Predictors of Real Estate Price Increases: A Case Study in the California Central Valley

William Knox Holt Memorial Library and Learning Center, University of the Pacific, 3601 Pacific Ave., Stockton, CA 95211