After a careful research and synthesis of the theoretical framework regarding residential real estate performance measurement and Real estate forecasting, this dissertation deepens in the proposition of real estate investments in an asset class that represents the biggest share of Italian Real Estate but yet is avoided by the big portfolios; the analysis is based on the development of correlation indices to evaluate two different behaviors, the first one evaluates through a GIS based HPM the relation between the rent/price performance with the different external and intrinsic variables (structural, neighborhood, socioeconomic and accessibility characteristics) of a residential property, and the second one evaluates the rent/price autocorrelation through time, in order to quantify how much price levels anticipate subsequent price changes within Milan’s Metropolitan Area. Using recent real transactions data, and analyzing the rent and price trends of residential real estate obtained from a robust database, this work develops an econometric model of the city of Milan with the objective of using it as a tool for raising various investment scenarios that are based on future public urban transformation plans and on private real estate projects; in this sense this dissertation analyzes previously-identified areas of interest with the objective of evaluating the feasibility of different real estate investments.
Dopo un'attenta ricerca e sintesi del quadro teorico relativo alla misurazione delle prestazioni degli immobili residenziali e soprattutto alle metodologie usate per la previsione di futuri scenari immobiliari, questa tesi approfondisce in questo senso e propone investimenti in un asset class che rappresenta la quota maggiore delle transazioni immobiliari in Italia, ma che viene comunque evitato dai grandi investitori; l'analisi si basa sullo sviluppo di indici di correlazione per valutare due diversi comportamenti, il primo valuta attraverso un modello edonico basato su GIS la relazione tra rendimento/prezzo con le diverse variabili esterne ed intrinseche (caratteristiche strutturali, di quartiere, socioeconomiche e di accessibilità) di una proprietà residenziale, e la seconda valuta l'autocorrelazione affitto/prezzo nel tempo, al fine di quantificare quanto le fasce di prezzo anticipino le successive variazioni di prezzo nell'area metropolitana di Milano. Utilizzando dati recenti di transazioni reali e analizzando le tendenze di affitto e prezzi degli immobili residenziali ottenute da un solido database, questo lavoro sviluppa un modello econometrico per la città di Milano con l'obiettivo di utilizzarlo come strumento per proporre ed esaminare vari scenari di investimento che sono basati su futuri piani di trasformazione urbana pubblica proposti dal Comune di Milano; questa tesi analizza le aree di interesse precedentemente identificate con l'obiettivo di valutare la fattibilità di diversi investimenti immobiliari.
The trend of property prices in the residential market of the metropolitan city of Milan. Analysis of historical thresholds in order to define real estate forecasts and investments
RODRIGUEZ ROJAS, JUAN SEBASTIAN
2018/2019
Abstract
After a careful research and synthesis of the theoretical framework regarding residential real estate performance measurement and Real estate forecasting, this dissertation deepens in the proposition of real estate investments in an asset class that represents the biggest share of Italian Real Estate but yet is avoided by the big portfolios; the analysis is based on the development of correlation indices to evaluate two different behaviors, the first one evaluates through a GIS based HPM the relation between the rent/price performance with the different external and intrinsic variables (structural, neighborhood, socioeconomic and accessibility characteristics) of a residential property, and the second one evaluates the rent/price autocorrelation through time, in order to quantify how much price levels anticipate subsequent price changes within Milan’s Metropolitan Area. Using recent real transactions data, and analyzing the rent and price trends of residential real estate obtained from a robust database, this work develops an econometric model of the city of Milan with the objective of using it as a tool for raising various investment scenarios that are based on future public urban transformation plans and on private real estate projects; in this sense this dissertation analyzes previously-identified areas of interest with the objective of evaluating the feasibility of different real estate investments.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/152352