A Study on the Asymmetric Effect to Housing Market Price Volatility

Chasoon Choi

doi:doi:10.11648/j.ijber.20190806.21

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A Study on the Asymmetric Effect to Housing Market Price Volatility

Chasoon Choi

Published in International Journal of Business and Economics Research (Volume 8, Issue 6)

Received: 18 October 2019 Accepted: 20 November 2019 Published: 25 November 2019

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Abstract

The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.

Published in	International Journal of Business and Economics Research (Volume 8, Issue 6)
DOI	10.11648/j.ijber.20190806.21
Page(s)	406-413
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Housing Price, Volatility, Asymmetric Effect, Information, GJR-GARCH Model

References

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APA Style

Chasoon Choi. (2019). A Study on the Asymmetric Effect to Housing Market Price Volatility. International Journal of Business and Economics Research, 8(6), 406-413. https://doi.org/10.11648/j.ijber.20190806.21

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ACS Style

Chasoon Choi. A Study on the Asymmetric Effect to Housing Market Price Volatility. Int. J. Bus. Econ. Res. 2019, 8(6), 406-413. doi: 10.11648/j.ijber.20190806.21

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AMA Style

Chasoon Choi. A Study on the Asymmetric Effect to Housing Market Price Volatility. Int J Bus Econ Res. 2019;8(6):406-413. doi: 10.11648/j.ijber.20190806.21

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@article{10.11648/j.ijber.20190806.21,
  author = {Chasoon Choi},
  title = {A Study on the Asymmetric Effect to Housing Market Price Volatility},
  journal = {International Journal of Business and Economics Research},
  volume = {8},
  number = {6},
  pages = {406-413},
  doi = {10.11648/j.ijber.20190806.21},
  url = {https://doi.org/10.11648/j.ijber.20190806.21},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20190806.21},
  abstract = {The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.},
 year = {2019}
}

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TY  - JOUR
T1  - A Study on the Asymmetric Effect to Housing Market Price Volatility
AU  - Chasoon Choi
Y1  - 2019/11/25
PY  - 2019
N1  - https://doi.org/10.11648/j.ijber.20190806.21
DO  - 10.11648/j.ijber.20190806.21
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 406
EP  - 413
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20190806.21
AB  - The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.
VL  - 8
IS  - 6
ER  -

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Author Information

Chasoon Choi

Department of Real Estate Studies, Namseoul University, Cheonan-Si, Chungnam, Korea

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Plain Text BibTeX RIS

APA Style

Chasoon Choi. (2019). A Study on the Asymmetric Effect to Housing Market Price Volatility. International Journal of Business and Economics Research, 8(6), 406-413. https://doi.org/10.11648/j.ijber.20190806.21

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ACS Style

Chasoon Choi. A Study on the Asymmetric Effect to Housing Market Price Volatility. Int. J. Bus. Econ. Res. 2019, 8(6), 406-413. doi: 10.11648/j.ijber.20190806.21

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AMA Style

Chasoon Choi. A Study on the Asymmetric Effect to Housing Market Price Volatility. Int J Bus Econ Res. 2019;8(6):406-413. doi: 10.11648/j.ijber.20190806.21

Copy | Download

@article{10.11648/j.ijber.20190806.21,
  author = {Chasoon Choi},
  title = {A Study on the Asymmetric Effect to Housing Market Price Volatility},
  journal = {International Journal of Business and Economics Research},
  volume = {8},
  number = {6},
  pages = {406-413},
  doi = {10.11648/j.ijber.20190806.21},
  url = {https://doi.org/10.11648/j.ijber.20190806.21},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20190806.21},
  abstract = {The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - A Study on the Asymmetric Effect to Housing Market Price Volatility
AU  - Chasoon Choi
Y1  - 2019/11/25
PY  - 2019
N1  - https://doi.org/10.11648/j.ijber.20190806.21
DO  - 10.11648/j.ijber.20190806.21
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 406
EP  - 413
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20190806.21
AB  - The objective of this paper empirically analyzes the relations between information and housing market volatility using the housing price index of Seoul, San Francisco and Los Angeles for the time period from January 1995 to July 2019. For the empirical test of the asymmetric effect of information on housing market volatility, this paper employs GJR-GARCH model which enable good information and bad information to have impact on volatility. The analysis results are as follows. First, it was found that the GJR-GARCH (1,1) model is suitable for analyzing the asymmetric reaction of housing price volatility for information types. Second, it was found that for information types, Seoul, San Francisco, and Los Angeles all displayed asymmetric housing price volatility. It was found that Seoul reacted greater to volatility for unexpected positive earnings rate information than unexpected negative earnings rate information, while on the contrary, San Francisco and Los Angeles showed that they reacted greater to unexpected negative earnings rate information than to unexpected positive earnings rate information. These findings support the hypothesis. Third, for sensitivity to volatility, Seoul was found to be about five times higher than San Francisco and Los Angeles. It is necessary to differentiate the housing price volatility prediction model and portfolio composition according to the information type.
VL  - 8
IS  - 6
ER  -

Copy | Download