Real Estate valuation and forecasting in non-homogeneous markets: A case study in Greece during the financial crisis

Alexandridis, Antonis; Karlis, Dimitrios; Papastamos, Dimitrios; Andritsos, Dimitrios

doi:10.1080/01605682.2018.1468864

Cited by 14 publications

(11 citation statements)

References 56 publications

(45 reference statements)

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“…A number of recent studies have examined the performance of housing markets in a crosscountry context. These include but are not restricted to Yip (2019), Sau-Leung ( 2019), Alexandridis et al (2019) and Yousaf and Ali (2020). To investigate the specific relationship between mortgage activity and house prices, a standard house price model, popular in the international literature, is used.…”

Section: Methodsmentioning

confidence: 99%

The potential impact of Covid-19 on the Irish housing sector

Allen-Coghlan

McQuinn

2020

IJHMA

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Purpose This paper aims to examine the implications for the Irish housing market of the economic slowdown due to the Covid-19 virus. Design/methodology/approach In this paper, an inverted demand function for housing is augmented to include a residential market activity variable and estimate the impact on house prices of the decline in economic activity due to the virus-related measures. The likely future path of house prices based on two different recovery scenarios is also examined. Under both scenarios house prices are forecast to decline in the near term. Findings The scenario analysis presented here indicates that Irish house prices are set to fall over the next 18 months as a result of the Covid-19 downturn. This contraction in prices is due to the decline in household disposable income and the sharp fall-off in mortgage market activity, which will inevitably result from the administrative closedown implemented by the Irish authorities. Originality/value As such the approach builds on several studies which have examined both house price movements in general and the relationship between house prices and mortgage credit availability. The paper also draws on the latest analysis of the implications for the Irish economy of Covid-19 and the related administrative closure methods introduced by the public authorities.

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Section: Methodsmentioning

confidence: 99%

The potential impact of Covid-19 on the Irish housing sector

Allen-Coghlan

McQuinn

2020

IJHMA

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“…Among researchers that adopted AI techniques in real estate valuation includes those that applied only ANN in prediction (Abidoye & Chan, 2017b;Rahman et al, 2019). Others compared the prediction ability of ANN with other techniques (Alexandridis et al, 2019;Cechin et al, 2000;Zurada et al, 2011). Others adopted fuzzy logic-FL (Gonzalez & Formoso, 2006;Król et al, 2016;Pagourtzi et al, 2006) among others.…”

Section: Related Researchesmentioning

confidence: 99%

An Integrated Approach Based on Artificial Intelligence Using Anfis and Ann for Multiple Criteria Real Estate Price Prediction

Yakub

Ali

Achu

et al. 2021

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A relatively high level of precision is required in real estate valuation for investment purposes. Such estimates of value which is carried out by real estate professionals are relied upon by the end-users of such financial information having paid a certain fee for consultation hence leaving little room for errors. However, valuation reports are often criticised for their inability to be replicated by two or more valuers. Hence, stirring to a keen interest within the academic cycle leading to the need for exploring avenues to improve the price prediction ability of the professional valuer. This study, therefore, focuses on overcoming these challenges by introducing an integrated approach that combines ANFIS with ANN termed ANFIS-AN, thereby having a reiteration in terms of ANN application to fortify price predictability. Using 255 property data alongside 12 variables, the ANFIS-AN model was adopted and its outcome was compared with that of ANN. Finally, the results were subjected to 3 different error testing models using the same training and learning benchmarks. The proposed model’s RMSE gave 1.413169, while that of ANN showed 9.942206. Similarly, using MAPE, ANN recorded 0.256438 while ANFIS-AN had 0.208324. Hence, ANFIS-AN’s performance is laudable, thus a better tool over ANN.

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“…This means that multivariate models are preferred in estate appraisal. Regression analysis, time series [29] and quantitative comparative approach [30] are some of the available tools used in this aspect. A combination of regression analysis and ANN performed better than the individual models [31].…”

Section: Evaluation Modelsmentioning

confidence: 99%

Review on the Application of Artificial Neural Networks in Real Estate Valuation

Nkolika¹

2020

IJATCSE

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Real estate appraisal is needed in assessment of the value of properties and contribute the regional economy of any country. Real estate valuation is thus an important subject, which has to be studied carefully as there are many individual subjective criteria, which often results in variations, which makes the traditional valuation methods to be inadequate. This work aimed at coping with the complexity of real estate valuation, by putting forth the advantages of artificial neural network, one of the novel model of real estate appraisal. The review of literature has helped to establish that the neural network model is better than the traditional model previously. This work opens up a new and better understanding to the principle of real estate evaluation.

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Real Estate valuation and forecasting in non-homogeneous markets: A case study in Greece during the financial crisis

Cited by 14 publications

References 56 publications

The potential impact of Covid-19 on the Irish housing sector

The potential impact of Covid-19 on the Irish housing sector

An Integrated Approach Based on Artificial Intelligence Using Anfis and Ann for Multiple Criteria Real Estate Price Prediction

Review on the Application of Artificial Neural Networks in Real Estate Valuation

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