Data-Driven Real Estate Investment
Veres, Krisztina (2024)
Veres, Krisztina
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024052917880
https://urn.fi/URN:NBN:fi:amk-2024052917880
Tiivistelmä
The objective of the thesis is to develop a strategic investment proposal for the case company for residential real estate in Budapest, Hungary. The study explored the relationship between economic conditions and the real estate market, using data analytics for data-driven decision-making together with qualitative analysis to identify optimal timing, location, and property types. Eventually, innovative investment strategies are offered to exploit emerging opportunities.
The research approach used is Applied action research. This study included four stages. First, a conceptual framework (CF) was established based on key factors influencing residential real estate investment, derived from the literature review. Second, a current state analysis (CSA) assessed relevant economic and real estate market indicators using data analytics and visualisations. Third, insights derived from the CF and CSA were combined by qualitative research methods into building the proposal. Interviews and workshops with experts and stakeholders informed the formation of the investment proposal. Fourth, the proposal was validated by experts.
The CSA revealed that the Hungarian economy is contracting, leading to remarkably low consumer confidence, curtailed housing demand and stagnating prices. Despite some localised signs of recovery, the economy remains vulnerable and housing subsidy programs were significantly modified. The study also underlines a growing rental demand for high-quality, modern apartments in liveable neighbourhoods in Budapest. Experts emphasise the significance of targeting new rust zone developments. These projects strategically transform large areas, incorporating green spaces and reducing traffic. The new Maxi Dubai project in Rákosrendező emerges as having the most potential to create a completely new, liveable district in the heart of Budapest. This development is specifically identified as a potential strategic investment area.
The proposed strategy offers potential for long-term capital gains, steady cash flow, and a favourable risk-reward profile due to rental demand for such properties as well as tax incentives. The proposal is carefully validated by expert feedback.
The research approach used is Applied action research. This study included four stages. First, a conceptual framework (CF) was established based on key factors influencing residential real estate investment, derived from the literature review. Second, a current state analysis (CSA) assessed relevant economic and real estate market indicators using data analytics and visualisations. Third, insights derived from the CF and CSA were combined by qualitative research methods into building the proposal. Interviews and workshops with experts and stakeholders informed the formation of the investment proposal. Fourth, the proposal was validated by experts.
The CSA revealed that the Hungarian economy is contracting, leading to remarkably low consumer confidence, curtailed housing demand and stagnating prices. Despite some localised signs of recovery, the economy remains vulnerable and housing subsidy programs were significantly modified. The study also underlines a growing rental demand for high-quality, modern apartments in liveable neighbourhoods in Budapest. Experts emphasise the significance of targeting new rust zone developments. These projects strategically transform large areas, incorporating green spaces and reducing traffic. The new Maxi Dubai project in Rákosrendező emerges as having the most potential to create a completely new, liveable district in the heart of Budapest. This development is specifically identified as a potential strategic investment area.
The proposed strategy offers potential for long-term capital gains, steady cash flow, and a favourable risk-reward profile due to rental demand for such properties as well as tax incentives. The proposal is carefully validated by expert feedback.