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Housing market forecasts via stock market indicators

Mittal, Varun and Schaposnik, Laura (2022): Housing market forecasts via stock market indicators.

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Abstract

Reliable forecasting of the housing market can provide salient insights into housing investments. Through the reinterpretation of housing data as candlesticks, we are able to utilize some of the most prominent technical indicators from the stock market to estimate future changes in the housing market. By providing an analysis of MACD, RSI, and Candlestick indicators (Bullish Engulfing, Bearish Engulfing, Hanging Man, and Hammer), we exhibit their statistical significance in making predictions for USA data sets (using Zillow Housing data), as well as for a stable housing market, a volatile housing market, and a saturated market by considering the data-sets of Germany, Japan, and Canada. Moreover, we show that bearish indicators have a much higher statistical significance then bullish indicators, and we further illustrate how in less stable or more populated countries, bearish trends are only slightly more statistically present compared to bullish trends. Finally, we show how the insights gained from our trend study can help consumers save significant amounts of money.

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