The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks

In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attenti...

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Autores principales: Constantinou, Anthony C., Fenton, Norman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487021/
https://www.ncbi.nlm.nih.gov/pubmed/28654698
http://dx.doi.org/10.1371/journal.pone.0179297
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author Constantinou, Anthony C.
Fenton, Norman
author_facet Constantinou, Anthony C.
Fenton, Norman
author_sort Constantinou, Anthony C.
collection PubMed
description In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attention since there has been widespread belief that the new measures were sufficiently skewed against landlords that they could signal the end of the Buy-To-Let (BTL) investment era in the UK. This paper assesses the prospective performance of BTL investments in London from the investor’s perspective, and examines the impact of incoming tax reforms using a novel Temporal Bayesian Network model. The model captures uncertainties of interest by simulating the impact of changing circumstances and the interventions available to an investor at various time-steps of a BTL investment portfolio. The simulation results suggest that the new tax reforms are likely to have a detrimental effect on net profits from rental income, and this hits risk-seeking investors who favour leverage much harder than risk-averse investors who do not seek to expand their property portfolio. The impact on net profits also poses substantial risks for lossmaking returns excluding capital gains, especially in the case of rising interest rates. While this makes it less desirable or even non-viable for some to continue being a landlord, based on the current status of all factors taken into consideration for simulation, investment prospects are still likely to remain good within a reasonable range of interest rate and capital growth rate variations. The results also suggest that the recent trend of property prices in London increasing faster than rents will not continue for much longer; either capital growth rates will have to decrease, rental growth rates will have to increase, or we shall observe a combination of the two events.
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spelling pubmed-54870212017-07-11 The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks Constantinou, Anthony C. Fenton, Norman PLoS One Research Article In 2015 the British government announced a number of major tax reforms for individual landlords. To give landlords time to adjust, some of these tax measures are being introduced gradually from April 2017, with full effect in tax year 2020/21. The changes in taxation have received much media attention since there has been widespread belief that the new measures were sufficiently skewed against landlords that they could signal the end of the Buy-To-Let (BTL) investment era in the UK. This paper assesses the prospective performance of BTL investments in London from the investor’s perspective, and examines the impact of incoming tax reforms using a novel Temporal Bayesian Network model. The model captures uncertainties of interest by simulating the impact of changing circumstances and the interventions available to an investor at various time-steps of a BTL investment portfolio. The simulation results suggest that the new tax reforms are likely to have a detrimental effect on net profits from rental income, and this hits risk-seeking investors who favour leverage much harder than risk-averse investors who do not seek to expand their property portfolio. The impact on net profits also poses substantial risks for lossmaking returns excluding capital gains, especially in the case of rising interest rates. While this makes it less desirable or even non-viable for some to continue being a landlord, based on the current status of all factors taken into consideration for simulation, investment prospects are still likely to remain good within a reasonable range of interest rate and capital growth rate variations. The results also suggest that the recent trend of property prices in London increasing faster than rents will not continue for much longer; either capital growth rates will have to decrease, rental growth rates will have to increase, or we shall observe a combination of the two events. Public Library of Science 2017-06-27 /pmc/articles/PMC5487021/ /pubmed/28654698 http://dx.doi.org/10.1371/journal.pone.0179297 Text en © 2017 Constantinou, Fenton http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Constantinou, Anthony C.
Fenton, Norman
The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title_full The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title_fullStr The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title_full_unstemmed The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title_short The future of the London Buy-To-Let property market: Simulation with temporal Bayesian Networks
title_sort future of the london buy-to-let property market: simulation with temporal bayesian networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487021/
https://www.ncbi.nlm.nih.gov/pubmed/28654698
http://dx.doi.org/10.1371/journal.pone.0179297
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