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.
Item Type: | MPRA Paper |
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Original Title: | Housing market forecasts via stock market indicators |
Language: | English |
Keywords: | housing market; trend study; stock market indicators; candlestick analysis; Heikin-Ashi candlestick analysis; RSI; MACD; Bearish Engulfing,; Bullish Engulfing; Hammer; Hanging Man; Dark Cloud Over |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General G - Financial Economics > G0 - General G - Financial Economics > G2 - Financial Institutions and Services > G20 - General |
Item ID: | 115009 |
Depositing User: | Varun Vaurn Mittal Mittal |
Date Deposited: | 17 Oct 2022 05:55 |
Last Modified: | 20 Oct 2022 11:50 |
References: | A. M. Kirby, Transactions of the Institute of British Geographers 1, 2 (1976), ISSN 00202754, 14755661, URL http://www.jstor.org/stable/621308 C. M. Gong, C. Lizieri, and H. X. Bao, Journal of Business Research 97, 51 (2019), ISSN 0148- 2963, URL https://www.sciencedirect.com/science/article/pii/S0148296318306465 D. T. Carruthers, Urban Studies 26, 214 (1989), https://doi.org/10.1080/00420988920080181, URL https://doi.org/10.1080/00420988920080181 A. Khalafallah, Tsinghua Science and Technology 13, 325 (2008). R. M. Kirwan and D. B. Martin, Environment and Planning A: Economy and Space 3, 243 (1971), https://doi.org/10.1068/a030243, URL https://doi.org/10.1068/a030243 S. Liu and Y. Su, Economics Letters 207, 110010 (2021), ISSN 0165-1765, URL https://www.sciencedirect.com/science/article/pii/S0165176521002871 M. Chauvet and S. Potter, Journal of Empirical Finance 7, 87 (2000), ISSN 0927-5398, URL https://www.sciencedirect.com/science/article/pii/S0927539899000158 D. Matsunaga, T. Suzumura, and T. Takahashi, Exploring graph neural networks for stock market predictions with rolling window analysis (2019), URL https://arxiv.org/abs/1909.10660 Competitiveness Review: An International Business Journal 23, 426 (2013), ISSN 1059-5422, URL https://doi.org/10.1108/CR-02-2013-0010 T. T.-L. Chong, W.-K. Ng, and V. K.-S. Liew, Journal of Risk and Financial Management 7, 1 (2014), ISSN 1911-8074, URL https://www.mdpi.com/1911-8074/7/1/1 Varun121322, Varun121322/housing-market-forecastsvia-stock-market-indicators: An analysis of housing market forecasts with popular stock market indicators, including macd, rsi, and candlestick indicators. (2022), URL https://github.com/Varun121322/Housing-Market-Forecasts-Via-Stock-Market-Indicators Y. Liang and J. Unwin, Covid-19 forecasts via stock market indicators (2021), URL https://arxiv.org/abs/2112.06393 Zillow data (2021), URL https://www.zillow.com/research/data/ Housing, URL https://fred.stlouisfed.org/categories/97 K.-H. Kim, C.-M. Lee, and Y.-M. Lee, Chapter 12: Rental housing system and housing market volatility: Monthly rent-based vs. asset-based systems (2014), URL https://www.elgaronline.com/view/edcoll/9781783472871/9781783472871.00020.xml R. Bhansali and L. P. Schaposnik, Proceedings of the Royal Society A 476, 20190826 (2020). K. S. Cheung, C. Y. Yiu, and C. Xiong, Journal of Risk and Financial Management 14 (2021), ISSN 1911-8074, URL https://www.mdpi.com/1911-8074/14/3/108 G. V. Engelhardt and C. J. Mayer, Journal of Urban Economics 44, 135 (1998), ISSN 0094-1190, URL https://www.sciencedirect.com/science/article/pii/S0094119097920647 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/115009 |