Identification and parametrization of polycyclicity in the primary housing market

Mach, Łukasz; Zmarzły, D.; Dąbrowski, Ireneusz; Frącz, Paweł

doi:10.1007/s10901-020-09817-6

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…Research that identifies the influence of endogenous variables [39,40], credit constraints [41], purchase expectations [42], and financial intermediation [43] on cyclicality in the housing market allows for a more accurate understanding of the relationships occurring in the market. Additional useful studies introducing decision support in possibly determined real estate market forecasts are those in the field of identifying cyclicality and seasonality in the market [44][45][46][47][48][49].…”

Section: Origins Of Seasonal and Cyclical Fluctuations In The Residen...mentioning

confidence: 99%

Identification of Differences in the Seasonality of the Developer and Individual Housing Market as a Basis for Its Sustainable Development

et al. 2023

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This article identifies seasonality profiles for three stages of housing construction. The profiles were determined as average monthly values obtained for permits issued for the construction of new apartments, for apartments whose construction has begun, and for apartments put into operation. The research process showed that there are differences in seasonality profiles between investments carried out by individual investors and those who build apartments for sale or rent. The research clearly showed that the development of reports and analyses for the housing market should include a breakdown of the market for the activities of individual developers as well as those operating as investments. Unfortunately, at present, reports on the real estate market are developed in total terms, which significantly reduces their utilitarian application. Taking into account the recommendations of the research will allow for sustainable development of the housing market in such a way that the market will strengthen its resilience to the occurrence of cyclical fluctuations, among other things.

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Section: Origins Of Seasonal and Cyclical Fluctuations In The Residen...mentioning

confidence: 99%

Identification of Differences in the Seasonality of the Developer and Individual Housing Market as a Basis for Its Sustainable Development

et al. 2023

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“…It should be noted, however, that the real estate market situation in Poland is changing dynamically and can vary from region to region. The housing construction market is characterized by high seasonality, determined, among other things, by the seasons of the year and related weather conditions (Frącz et al 2023;Mach et al 2021). At the same time, there is a great need to predict the actual situation in this market and to make predictions over different time horizons for its key components.…”

Section: Introductionmentioning

confidence: 99%

Time Series Prediction For The Housing Construction Market With The Use Of NARNet

Wotzka¹,

Suchacka²,

Mach³

et al. 2023

ECMS 2023 Proceedings Edited by Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni

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The paper discusses the study to develop and tune parameters of a nonlinear autoregressive neural network (NARNet or NARNN) model for predicting the number of housing units. Predictions were made for the housing construction market in Poland, which is a dynamically growing European market. Three stages of the housing construction process have been taken into considerationThe paper discusses the study to develop and tune parameters of a nonlinear autoregressive neural network (NARNet or NARNN) model for predicting the number of housing units. Predictions were made for the housing construction market in Poland, which is a dynamically growing European market. Three stages of the housing construction process have been taken into consideration: permits issued for house construction, houses under construction, and completed new houses. Experimental results have shown that a NARNet model can be a very effective tool in the considered scenario. A network model using the Levenberg-Marquardt backpropagation training function achieved the best model fit, as well as the most accurate one-month predictions.

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“…This provided an opportunity to learn about qualities that are crucial for their development. The real estate market is one of the most important elements of the economy, which is characterised by certain cycles, the details of which can be found in the following studies: (Alqaralleh and Canepa, 2020;Huang, Liow, and Zhou, 2020;Łaszek and Olszewski 2018;Mach, Zmarzły, Dąbrowski, and Frącz, 2021). This may involve events described as self-perpetuating mechanisms that cause price increases that are not justified by economic and financial factors.…”

Section: Introductionmentioning

confidence: 99%

Identification of homogeneous groups of real estate markets and the pandemic resilience of the construction sector

Dąbrowski¹,

Mach²,

Mikołajczyk³

et al. 2021

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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Identification and parametrization of polycyclicity in the primary housing market

Cited by 5 publications

References 20 publications

Identification of Differences in the Seasonality of the Developer and Individual Housing Market as a Basis for Its Sustainable Development

Identification of Differences in the Seasonality of the Developer and Individual Housing Market as a Basis for Its Sustainable Development

Time Series Prediction For The Housing Construction Market With The Use Of NARNet

Identification of homogeneous groups of real estate markets and the pandemic resilience of the construction sector

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