Author: June Nguyen, Mirrien Liang, Alex Li
Last Updated on: December 9, 2023
The real estate market in the Greater Vancouver area has experienced various fluctuations over the past decade. Understanding these changes is crucial for market stakeholders, including investors, realtors, and policy makers.
There is a need for a comprehensive analysis of the Sales to Active Listings Rate (SALR) to understand its trends, seasonal patterns, and the probability and impact of extreme market events.
We propose a practical approach by conducting a time series analysis of the SALR from 2011 to 2023. This will include trend analysis, seasonality study, forecasting future values, and particularly focusing on the identification and analysis of extreme events in the market.
The SALR values are collected and provided by The Real Estate Board of Greater Vancouver (REBGV) for public usages. The REBGV is a member-based professional association of 15,000 REALTORS® and their companies who live and work in communities from Whistler to Maple Ridge to Tsawwassen and everywhere in between.
There are five variables in the dataset:
Year_month: the year and month the observations were recorded forReported_SAL: the SAL rates used in the monthly reports generated by the boardSales: the total number of properties sold during a monthListings: the total number of properties actively listed during a monthCalculated_SAL: the SAL rates calculated based on the values ofSalesandListings.
Modeling efforts led to the selection of SARIMA(2,0,1)x(1,0,0)[12] as the preferred choice due to its ability to cappture short-term dynamics and seasonal patterns. This model, despite a relatively higher AIC compared to SARIMA(2,0,1)x(1,0,0)[12], showcased a more reasonable fit by appropriately handling presumably non-recurring shocks in 2016 and 2021 without overfitting.
While proficient in short-term forecasting, the chosen model displayed reduced accuracy in longer forecasts, possibly indicative of overfitting. Predictions suggested a gradual decrease in market volatility, assuming no major shocks.
In conclusion, the SARIMA(2,0,1)x(1,0,0)[12] model was favored for its alignment with observed anomalies and practicality. Continuous refinement is crucial for enhancing the model's reliability in predicting the dynamic trends of the Greater Vancouver real estate market.