BTO: Analyzing Housing Data with Google Finance

While Google Finance is primarily known for tracking stocks, bonds, and currencies, its functionalities can also be creatively leveraged to analyze seemingly unrelated datasets, such as Build-To-Order (BTO) housing prices in Singapore. Although Google Finance doesn’t directly provide BTO data, you can use its chart functionalities and comparison tools with some ingenuity to gain valuable insights.

Conceptualizing BTO Data as a Financial Instrument

The key is to treat BTO prices as you would treat stock prices. Imagine each BTO launch as a separate “asset.” You can track the median or average prices of different apartment types (e.g., 3-room, 4-room, 5-room) in various locations over time. To do this effectively requires gathering the historical BTO data from reliable sources like the Housing & Development Board (HDB) website or reputable real estate analysis platforms.

Leveraging Google Finance Tools

1. Creating Custom Spreadsheets: The core of your analysis lies in a well-structured Google Sheet. Populate columns with the launch date, location, flat type, and median/average price. Calculate key metrics such as price change percentage from launch, price per square foot (PSF), and comparing prices across different launches.
2. Linking to Google Finance: This is where Google Finance indirectly comes into play. While you won’t be importing raw BTO data *into* Google Finance, you can *export* calculated metrics *from* your Google Sheet to inform your Google Finance research. For example, if a particular location consistently shows high PSF growth, you might be interested in related Real Estate Investment Trusts (REITs) traded on the stock market that invest in that area.
3. Benchmarking and Comparisons: Use Google Finance’s “Compare” feature to benchmark the performance of real estate stocks or REITs against more traditional investments. Does investing in a REIT focusing on residential properties outperform the general market index? While not directly related to BTO performance, it provides a broader context.
4. Correlation Analysis (Indirect): By plotting BTO price trends alongside relevant market indicators (e.g., interest rates, inflation rates – easily accessible through Google Finance), you can look for potential correlations. Is there a visible lag between changes in interest rates and BTO price fluctuations? This requires external analysis, but the readily available economic data on Google Finance helps inform your assessment.

Limitations and Considerations

This method is indirect and relies heavily on manual data entry and spreadsheet manipulation. Google Finance is not designed for this specific purpose, so the results will be indicative rather than definitive. Furthermore, BTO pricing is influenced by many factors besides pure market forces, including government subsidies, location desirability, and ballot luck. These nuances need to be considered when interpreting the data.

Conclusion

While not a perfect solution, using Google Finance in conjunction with meticulously gathered BTO data and well-structured Google Sheets allows for a creative approach to analyzing housing market trends. By treating BTO launches as individual “assets” and leveraging Google Finance’s charting and comparison tools, you can glean insights into price movements, identify potential correlations, and make more informed decisions – although always with a critical understanding of the limitations.