Residential Rent in Wuhan Based on Geometric Brownian Motion Model Fluctuation Fitting and Prediction

被引：0
|
作者：
Zhu Lifang [1 ]
Mei Likeya [2 ]
Liu Yang [2 ]
Dorgizaba [2 ]
机构：
[1] Wuhan Donghu Univ, Econ Sch, Wuhan 430072, Hubei, Peoples R China
[2] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Hubei, Peoples R China
来源：
2023 IEEE 8TH INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS, ICBDA | 2023年
关键词：
residential rental; geometric Brownian motion; monte carlo simulation; predictive analysis; Wuhan City;
D O I：
10.1109/ICBDA57405.2023.10104631
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper makes an analysis of the fitting and prediction of residential rent fluctuation in Wuhan by using the advantages of big data. Frequent fluctuations in rental residential prices and market trends urgently need to strengthen the analysis of residential rental market price monitoring data. This paper attempts to fit and analyze the trend of random fluctuation behavior of residential rent based on scientific methods. Based on the geometric Brownian motion, the geometric Brownian motion model is established for the 24-month residential rental price fluctuation behavior of 7 districts in Wuhan, and the Monte Carlo method is used to simulate the residential rental price. By comparing the correlation coefficient between the fitted value and the actual price, the residual sum of squares and the residual analysis diagram test the goodness of fit of the simulation results to explore the differences in the fitting application of different districts to the model, and use the selected optimal fitting results to analyze the future price trend and establish the price monitoring and early warning model mechanism. Through empirical research, it provides a new method for the government to accurately grasp the dynamic fluctuation law of residential rental price.
引用
收藏
页码：87 / 93
页数：7
相关论文
共 50 条
  • [1] Multi-purpose binomial model: Fitting all moments to the underlying geometric Brownian motion
    Kim, Y. S.
    Stoyanov, S.
    Rachev, S.
    Fabozzi, F.
    [J]. ECONOMICS LETTERS, 2016, 145 : 225 - 229
  • [2] Stock price prediction using geometric Brownian motion
    Agustini, Farida W.
    Affianti, Ika Restu
    Putri, Endah R. M.
    [J]. INTERNATIONAL CONFERENCE ON MATHEMATICS: PURE, APPLIED AND COMPUTATION, 2018, 974
  • [3] A New Approach in Geometric Brownian Motion Model
    Azizi, Seyed Mohammad Esmaeil Pour Mohammad
    Neisy, Abdolsadeh
    [J]. FUZZY INFORMATION AND ENGINEERING AND DECISION, 2018, 646 : 336 - 342
  • [4] Geometric Brownian motion as a model for river flows
    Lefebvre, M
    [J]. HYDROLOGICAL PROCESSES, 2002, 16 (07) : 1373 - 1381
  • [5] A Model Based on Fractional Brownian Motion for Temperature Fluctuation in the Campi Flegrei Caldera
    Di Crescenzo, Antonio
    Martinucci, Barbara
    Mustaro, Verdiana
    [J]. FRACTAL AND FRACTIONAL, 2022, 6 (08)
  • [6] A geometric Brownian motion model for field degradation data
    Elsayed, EA
    Liao, HT
    [J]. EIGHTH ISSAT INTERNATIONAL CONFERENCE ON RELIABILITY AND QUALITY IN DESIGN, PROCEEDINGS, 2003, : 55 - 59
  • [7] Intermittency in an interacting generalization of the geometric Brownian motion model
    Kuehn, Reimer
    Neu, Peter
    [J]. JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2008, 41 (32)
  • [8] Applications of an extended geometric Brownian motion degradation model
    Hsu, Yu-Sheng
    Chen, Pei-Chun
    Lee, Ming-Yung
    Wu, Cheng-Hsun
    [J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2022, 51 (07) : 2139 - 2153
  • [9] Explaining Freeway Breakdown with Geometric Brownian Motion Model
    Ossenbruggen, Paul J.
    Laflamme, Eric M.
    [J]. JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2019, 145 (09)
  • [10] A geometric Brownian motion model for field degradation data
    Elsayed, EA
    Liao, HT
    [J]. INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY, 2004, 20 (1-3): : 51 - 72
12345