How does HousingAlerts Data Predict Future Markets?

Question:

Retrospective data is useful for seeing what happened, but I am most interested in the prospective or predicted data of where some of the markets are headed. How does HousingAlerts data predict future markets?

Answer:

HousingAlerts, is, in essence, a type of artificial adaptive intelligence software system able to detect complex patterns in data. It is, in mathematical terms, a universal function approximator.  In other words, given the right data correctly configured, it can capture and model input- output relationships and generate actionable decision triggers. Past data is a prerequisite.

There’s an old saying applicable to life and real estate markets, “You have to know where you are before you know where you’re going.” If you don’t know where a market is in its cycle, you’re in no position to make a truly informed decision about whether or not you should buy or sell, or what investing strategy you should be using.
The data is used **in conjunction with** Technical Analysis (TA) – it’s the combination of the two, in a visual format, that helps generate local market decision triggers.
Technical Analysis tools are used by virtually every Investment Bank and global trading firm on the planet for analyzing market cycles and as a predictive methodology for timing more than $11 Trillion in daily stock, commodity and currency investments.
Technical Analysis has withstood the test of time, even in these complex and fast-moving markets.
Using these same TA tools is helpful in identifying and predicting Real Estate cycles so well **because** real estate is so very cyclical.  Real Estate cycles are like a slow moving train compared to the financial markets (which can change direction minute-by-minute).
Local real estate cycles can be spotted a mile away if you have the right data, and the right tools. Most importantly, TA incorporates ‘Market Psychology’ into the analysis – one of, if not the most dominant driver affecting future local real estate values.

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