The object of this thesis is the evaluation of a real estate asset considered as an investment opportunity. The hypotheses underlying the following paper are two; the first is that the traditional method of valuing real estate assets of the income approach applied by means of a discounted cash flows analysis (hereinafter DCFA or DCF) is not a tool capable of providing reliable indications to a real estate investor since it does not allow to quantify the riskiness of the asset being evaluated. This lack leads to incorrect price evaluations, since one of the key principles of the financial economy is that riskier assets have low prices and relatively high returns compared to less risky assets, which have high prices and relatively low returns. The second hypothesis is that representing the objective functions of the DCFA - whether they are the price, the net present value, the internal rate of return, or others - as a random variable (or stochastic) allows to quantify the riskiness of an asset and therefore provide more precise indications both for the purpose of estimating the price (a topic that will not be dealt with) and as regards the evaluation of the convenience of investing in a real estate asset. To achieve this, the traditional DCF method was used in combination with the Monte Carlo simulation, thanks to which it was possible to aggregate the risks deriving from the individual variables contained in the DCF and obtain a quantitative description of the global risk of the asset. The DCF variables must necessarily be made stochastic in order to apply the Monte Carlo method, therefore the parameters and the type of distribution that best represents them must be chosen. The peculiarity of the applicative part of the thesis is represented by the presence of a break-option in the lease contract, which is incorporated into the DCF following the model developed by C. Amédée-Manesme et all (2013) and so be able to verify the effects on profitability and on the riskiness of the asset. The results achieved by applying the method just briefly described above are that the presence of the break-option creates two completely disjointed scenarios, which lead the NPV and IRR random variables to be represented by a bimodal probability distribution. This id due to the coexistence in the same domain of values deriving from a scenario in which the break-option is exercised and one in which it is not. Using the Monte Carlo method it was possible to firstly separate two scenario, then estimate their probability of occurrence and to quantify both the expected values of performances and the levels of risk. The hypotheses were verified through the application of the tools and methodology just described by means of a case study in which is analysed a property owned by COIMA RES known as Vodafone Village; that is an office building with a commercial area of approximately 46 thousand square meters located in the south-west suburbs of Milan.
L’oggetto di questa tesi è la valutazione di un asset immobiliare considerato come opportunità d’investimento. Le ipotesi che stanno alla base del seguente elaborato sono due; la prima è che il metodo tradizionale di valutazione degli asset immobiliari dell’income approach applicato per mezzo di una discounted cash flows analisi (in seguito DCFA o DCF) non è uno strumento capace di fornire indicazioni affidabili ad un investitore immobiliare, in quanto non permette di quantificare la rischiosità dell’asset che sta valutando. Questa mancanza porta a valutazioni del prezzo incorrette, dal momento che uno dei principi cardine dell’economia finanziaria è che asset più rischiosi hanno prezzi bassi e rendimenti relativamente elevati rispetto ad asset meno rischiosi, che hanno prezzi alti e rendimenti relativamente bassi. La seconda ipotesi è che rappresentare le funzioni obiettivo della DCFA – sia che essi siano il prezzo, il valore attuale netto, il tasso interno di ritorno, o altre – come una variabile aleatoria (o stocastica) permette di quantificare la rischiosità di un asset e quindi fornire indicazioni più precise sia al fine della stima del prezzo (argomento che non verrà trattato) che per quanto riguarda la valutazione della convenienza dell’investimento in un asset immobiliare. Per riuscire in questo intento è stato utilizzato il tradizionale metodo del DCF in combinazione con la simulazione Monte Carlo, grazie alla quale è stato possibile aggregare i rischi derivanti dalle singole variabili contenute nel DCF ed ottenere una descrizione quantitativa del rischio globale dell’asset. Le variabili del DCF devono necessariamente essere rese stocastiche per poter applicare il metodo Monte Carlo, dunque devono essere scelti i parametri e il tipo di distribuzione che meglio le rappresenta. La peculiarità della parte applicativa della tesi è rappresentata dalla presenza di una break-option nel contratto di locazione, la quale viene incorporata nel DCF seguendo il modello sviluppato da C. Amédée‐Manesme et all (2013), per poterne verificare gli effetti sulla redditività e sulla rischiosità dell’asset. I risultati raggiunti applicando il metodo brevemente appena descritto sono che la presenza della break-option crea due scenari completamente disgiunti, i quali portano a far assumere una forma bimodale alla distribuzione di probabilità delle variabili aleatorie dell’NPV e dell’IRR, dovuta proprio alla compresenza nel suo dominio di valori derivanti da uno scenario in cui la break-option viene esercitata e uno in cui non lo è. Grazie all’uso del Monte Carlo è stato possibile stimare la probabilità di avvenimento dei due scenari e quantificarne sia i valori attesi di performances che i livelli di rischio. Le ipotesi sono state verificate tramite l’applicazione degli strumenti e della metodologia appena descritta per mezzo di un caso studio in cui viene analizzato un immobile di proprietà di COIMA RES conosciuto come Vodafone Village; un edificio per uffici con una superficie commerciale di circa 46 mila metri quadri localizzato nella periferia sud-ovest di Milano.
Applying Monte Carlo simulation in real estate capital budgeting for investment evaluation
ISELLA, MARCO
2018/2019
Abstract
The object of this thesis is the evaluation of a real estate asset considered as an investment opportunity. The hypotheses underlying the following paper are two; the first is that the traditional method of valuing real estate assets of the income approach applied by means of a discounted cash flows analysis (hereinafter DCFA or DCF) is not a tool capable of providing reliable indications to a real estate investor since it does not allow to quantify the riskiness of the asset being evaluated. This lack leads to incorrect price evaluations, since one of the key principles of the financial economy is that riskier assets have low prices and relatively high returns compared to less risky assets, which have high prices and relatively low returns. The second hypothesis is that representing the objective functions of the DCFA - whether they are the price, the net present value, the internal rate of return, or others - as a random variable (or stochastic) allows to quantify the riskiness of an asset and therefore provide more precise indications both for the purpose of estimating the price (a topic that will not be dealt with) and as regards the evaluation of the convenience of investing in a real estate asset. To achieve this, the traditional DCF method was used in combination with the Monte Carlo simulation, thanks to which it was possible to aggregate the risks deriving from the individual variables contained in the DCF and obtain a quantitative description of the global risk of the asset. The DCF variables must necessarily be made stochastic in order to apply the Monte Carlo method, therefore the parameters and the type of distribution that best represents them must be chosen. The peculiarity of the applicative part of the thesis is represented by the presence of a break-option in the lease contract, which is incorporated into the DCF following the model developed by C. Amédée-Manesme et all (2013) and so be able to verify the effects on profitability and on the riskiness of the asset. The results achieved by applying the method just briefly described above are that the presence of the break-option creates two completely disjointed scenarios, which lead the NPV and IRR random variables to be represented by a bimodal probability distribution. This id due to the coexistence in the same domain of values deriving from a scenario in which the break-option is exercised and one in which it is not. Using the Monte Carlo method it was possible to firstly separate two scenario, then estimate their probability of occurrence and to quantify both the expected values of performances and the levels of risk. The hypotheses were verified through the application of the tools and methodology just described by means of a case study in which is analysed a property owned by COIMA RES known as Vodafone Village; that is an office building with a commercial area of approximately 46 thousand square meters located in the south-west suburbs of Milan.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/149793