Application Research of Q-Type Clustering Model in Financial Data Analysis of Beijing Housing Price

DOI

10.2991/978-94-6463-098-5_187How to use a DOI?

Keywords

Q-type Clustering Method; Financial Development; House Prices in Beijing; Threshold Effect

Abstract

Under the influence of the socio-economic system, financial development and rising house prices are no longer two separate issues. For a specific regional environment, financial development will, to a certain extent, suppress the rising trend of house prices and contribute to the stable development of the regional economy. Based on the connotation of the role of Q-type clustering method, the trend of financial mechanism is determined, and then based on this, the temporal and spatial characteristics of the rising house prices in Beijing are studied. The Q-type clustering algorithm is combined with a threshold effect analysis model, and the practical value of the defined model is verified based on the results of the analysis of known data.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ao Dong
PY  - 2022
DA  - 2022/12/27
TI  - Application Research of Q-Type Clustering Model in Financial Data Analysis of Beijing Housing Price
BT  - Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)
PB  - Atlantis Press
SP  - 1656
EP  - 1667
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-098-5_187
DO  - 10.2991/978-94-6463-098-5_187
ID  - Dong2022
ER  -