omershahar/housing-market-resilience-audit

Forensic Housing Market Resilience Analysis (REmatch)

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Overview

This project presents a forensic Exploratory Data Analysis (EDA) and predictive framework for the U.S. residential real estate market (2012–2023). Using the REmatch model, we analyze supply-side volatility to distinguish between "False Oversupply Warnings" (entry opportunities) and "Real Market Deterioration".

Objectives

• —Identify structural supply shocks vs. seasonal noise.
• —Quantify market resilience using the Three Pillars: Behavior, Infrastructure, and Socioeconomics.
• —Validate the "Luxury Veil" theory and its impact on price perception.
• —Predict 10-month forward price appreciation outcomes.

Dataset Description

The analysis utilizes the HouseTS dataset, covering U.S. ZIP codes with key features such as:

• —inventory_sa: STL-adjusted inventory levels.
• —median_sale_price: Median transaction price (Robust to outliers).
• —DRS (Dynamic Resilience Score): Physical infrastructure strength.
• —SCS (Seller Capitulation Score): Behavioral indicator of seller bargaining power.
• —RTI (Rent-to-Income): Socioeconomic affordability metric.

Data Cleaning & Pre-processing

• —Missing Value Audit: Mapped data gaps to ensure "Investment Grade" reliability.
• —STL Decomposition: Removed seasonal "Spring Fever" noise from inventory growth.
• —Outlier Management: Implemented Winsorized Medians to negate the "Luxury Veil" distortion caused by extreme high-end sales.

Exploratory Data Analysis (EDA) Insights

• —The Luxury Veil: We proved that arithmetic means overstate returns by over 115%. By switching to Robust Medians, we identified the true core market appreciation of ~16%.
• —Signal vs. Noise: Using STL decomposition, we revealed that many "oversupply alarms" are seasonal artifacts. True alarms only trigger when the structural trend deviates significantly from the 12-month average.
• —Behavioral Pricing Power: We identified a correlation where rising Seller Capitulation Scores (SCS) lead to a collapse in bidding wars, signaling a loss of seller negotiating power.

Key Forensic Findings

• —Market Fortresses: ZIP codes with high infrastructure (DRS) clear excess inventory faster, validating the "Moat" theory.
• —False Warnings: The model identified entry opportunities where prices rose 10 months later despite initial supply alarms.
• —Critical Vulnerability: The forensic audit highlighted potential Survivorship Bias in the historical data.