AMEDEE MANESME Charles Olivier

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This study addresses the price heterogeneity of the five first growths of Bordeaux. We apply the quantile regression (QR) approach with market segmentation based on wine bottle price quantiles. We compute the hedonic price of wine attributes for various price segments in the market. This approach is applied to a major dataset comprising approximately 50,000 transactions over the 2003–2017 period. The findings indicate that the relative hedonic prices of several wine attributes differ significantly among deciles. The implications of our results are manifold. Vintage and Parker grades have a strong impact on the variation in wine prices, and there is a hierarchy among the five first growths of Bordeaux. There is also a premium commanded by the reputation and experience of an auction house. Since the financial crisis of 2012–2013, investors have considered that the five first growths are overrated, save for the most expensive wines. for those most expensive ones, investors prefer scarcity to liquidity. These results are of import to several actors in the fine wine market: investors, for example, could use the findings herein to better diversify their wine portfolio, while auction houses could better anticipate their future sales based on consumers’ expectation.

The Cornish–Fisher expansion is a simple way to determine quantiles of non-normal distributions. It is frequently used by practitioners and by academics in risk management, portfolio allocation, and asset liability management. It allows us to consider non-normality and, thus, moments higher than the second moment, using a formula in which terms in higher-order moments appear explicitly. This paper has two primary objectives. First, we resolve the classic confusion between the skewness and kurtosis coefficients of the formula and the actual skewness and kurtosis of the distribution when using the Cornish–Fisher expansion. Second, we use the response surface approach to estimate a function for these two values. This helps to overcome the difficulties associated with using the Cornish–Fisher expansion correctly to compute value at risk. In particular, it allows a direct computation of the quantiles. Our methodology has many practical applications in risk management and asset allocation.

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Purpose: The purpose of this paper is to address the heterogeneity of real estate assets with regard to investment risk measurement, with Paris’ apartment market as a case study. Design/methodology/approach: Quantile regression is used to handle the fact that willingness to pay for housing attributes may vary greatly over both space and asset value categories. The method is alternately applied on central and peripheral districts of Paris, or “arrondissements”, with hedonic indices built for nine deciles over a 17-year period (1990-2006). Portfolio allocation is subsequently analysed with deciles being the assets. Findings: The findings suggest that during the slump, peripheral districts show better resilience and define the efficient frontier while also exhibiting a lower volatility. In addition, higher returns are observed for lower-priced apartments, both central and peripheral. During the recovery and boom stages of the cycle, the highest returns are experienced for the cheapest apartments in central locations, whereas upper-priced, centrally located units yield the lowest returns. Originality/value: The originality of this research resides in the application of quantile regression in a real estate investment and risk management context. The methodology may raise individual investors’ and practitioners’ attention, especially index providers’.

In this paper, the heterogeneity of the Paris apartment market is addressed. For this purpose, quantile regression is applied – with market segmentation based on price deciles – and the hedonic price of housing attributes is computed for various price segments of the market. The approach is applied to a major data set managed by the Paris region notary office (Chambre des Notaires d’Île de France), which consists of approximately 156,000 transactions over the 2000–2006 period. Although spatial econometric methods could not be applied owing to the unavailability of geocodes, spatial dependence effects are shown to be adequately accounted for through an array of 80 location dummy variables. The findings suggest that the relative hedonic prices of several housing attributes differ significantly among deciles. In particular, the elasticity coefficient of the apartment size variable, which is 1.09 for the cheapest units, is down to 1.03 for the most expensive ones. The unit floor level, the number of indoor parking slots, as well as several neighbourhood attributes and location dummies all exhibit substantial implicit price fluctuations among deciles. Finally, the lower the apartment price, the higher the potential for price appreciation over time. While enhancing our understanding of the complex market dynamics that underlie residential choices in a major metropolis such as Paris, this research provides empirical evidence that the QR approach adequately captures heterogeneity among house price ranges, which simultaneously applies to housing stock, historical construct and social fabric.

This paper deals with real estate portfolio optimization when investors are risk averse. In this framework, we examine an important decision making problem, namely the determination of the optimal time to sell a diversified real estate portfolio. The optimization problem corresponds to the maximization of a concave utility function defined on both the free cash flows and the terminal value of the portfolio. We determine several types of optimal times to sell and analyze their properties. We extend previous results, established for the quasi linear utility case, where investors are risk neutral. We consider four cases. In the first one, the investor knows the probability distribution of the real estate index. In the second one, the investor is perfectly informed about the real estate market dynamics. In the third case, the investor uses an intertemporal optimization approach which looks like an American option problem. Finally, the buy-and-hold strategy is considered. For these four cases, we analyze in particular how the solutions depend on the market volatility and we compare them with those of the quasi linear case. We show that the introduction of risk aversion allows to better account for the real estate market volatility. We also introduce the notion of compensating variation to better measure the impacts of both the risk aversion and the volatility.

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Purpose The purpose of this paper is to exhibit the impacts of lease duration and lease break options on the optimal holding period for a real estate asset or portfolio Methodology / approach We use a Monte Carlo simulation framework to simulate a real estate assets cash-flows in which lease structures (rents indexation patterns overall lease duration and break options) are explicitly taken into account. We assume that a tenant exercises his/her option to break a lease if the rent paid as higher than the market rental value of similar properties. We also model vacancy duration stochastically using Poisson's law. Finally capital values and market rental values are simulated using specific stochastic processes. and are also assumed to be correlated. We derive the optimal holding period for the asset as the value that maximises its discounted value. which is the sum of the discounted free cash flows and the discounted terminal Findings We demonstrate that. consistent with existing capital markets literature and real estate business practice. break-options in leases can dramatically alter optimal holding periods for real estate assets and portfolios by extension. We show that. everything else being equal. shorter lease durations. higher market rental value volatility. increasing negative rental reversion. higher vacancy duration. more break options. all tend to decrease the optimal holding period of a real estate asset. The converse is also true. Practical implications Practitioners are insights as well as a practical methodology for determining the ex-ame optimal holding period for an asset or a portfolio based on a number of market and asset specific parameters including the lease structure. Originality / value The originality of the paper derives from taking an explicit modelling approach to lease duration and lease breaks as additional sources of asset specific risk alongside market risk. This is critical in real estate portfolio management because such specific risk is usually difficult to diversify.

The computation of Value at Risk (VaR) has long been a problematic issue in commercial real estate. Difficulties mainly arise from the lack of appropriate data, the lack of transactions, the non-normality of returns, and the inapplicability of many of the traditional methodologies. In addition, specific risks remain latent in investors’ portfolios and thus risk measurements based on market index do not represent the risks of a specific portfolio. Following a spate of new regulations such as Basel II, Basel III, NAIC and Solvency II, financial institutions have increasingly been required to estimate and control their exposure to market risk. Hence, financial institutions now commonly use “internal” VaR (or Expected Shortfall) models in order to assess their market risk exposure. This paper proposes the first model designed especially for static real estate VaR computation. The proposal accounts for specific real estate characteristics such that the lease structures or the vacancies. The paper contributes to the real estate risk management literature by proposing for the first time a model that incorporates characteristics of real estate investments. It allows more precise real estate risk measurements and is derived from a regulators’ approach.

Purpose The purpose of this paper is to exhibit the impacts of lease duration and lease break options on the optimal holding period for a real estate asset or portfolio Methodology / approach We use a Monte Carlo simulation framework to simulate a real estate assets cash-flows in which lease structures (rents indexation patterns overall lease duration and break options) are explicitly taken into account. We assume that a tenant exercises his/her option to break a lease if the rent paid as higher than the market rental value of similar properties. We also model vacancy duration stochastically using Poisson's law. Finally capital values and market rental values are simulated using specific stochastic processes. and are also assumed to be correlated. We derive the optimal holding period for the asset as the value that maximises its discounted value. which is the sum of the discounted free cash flows and the discounted terminal Findings We demonstrate that. consistent with existing capital markets literature and real estate business practice. break-options in leases can dramatically alter optimal holding periods for real estate assets and portfolios by extension. We show that. everything else being equal. shorter lease durations. higher market rental value volatility. increasing negative rental reversion. higher vacancy duration. more break options. all tend to decrease the optimal holding period of a real estate asset. The converse is also true. Practical implications Practitioners are insights as well as a practical methodology for determining the ex-ame optimal holding period for an asset or a portfolio based on a number of market and asset specific parameters including the lease structure. Originality / value The originality of the paper derives from taking an explicit modelling approach to lease duration and lease breaks as additional sources of asset specific risk alongside market risk. This is critical in real estate portfolio management because such specific risk is usually difficult to diversify.

The computation of Value at Risk has traditionally been a troublesome issue in commercial real estate. Difficulties mainly arise from the lack of appropriate data, the non-normality of returns, and the inapplicability of many of the traditional methodologies. As a result, calculation of this risk measure has rarely been done in the real estate field. However, following a spate of new regulations such as Basel II, Basel III, NAIC and Solvency II, financial institutions have increasingly been required to estimate and control their exposure to market risk. As a result, financial institutions now commonly use “internal” Value at Risk (VaR) models in order to assess their market risk exposure. The purpose of this paper is to estimate distribution functions of real estate VaR while taking into account non-normality in the distribution of returns. This is accomplished by the combination of the Cornish-Fisher expansion with a certain rearrangement procedure. We demonstrate that this combination allows superior estimation, and thus a better VaR estimate, than has previously been obtainable. We also show how the use of a rearrangement procedure solves well-known issues arising from the monotonicity assumption required for the Cornish-Fisher expansion to be applicable, a difficulty which has previously limited the useful of this expansion technique. Thus, practitioners can find a methodology here to quickly assess Value at Risk without suffering loss of relevancy due to any non-normality in their actual return distribution. The originality of this paper lies in our particular combination of Cornish-Fisher expansions and the rearrangement procedure.

No summary available.

This thesis contributes to academic research in real estate by providing a risk assessment for commercial real estate investment management. Real estate investment has many specificities such as location, liquidity, investment size or obsolescence and requires active management. These specificities make traditional risk measurement approaches difficult to apply. This research work is presented in the form of four academic papers dealing with portfolio management and risk in real estate. This work is built on the existing academic literature and is based on previous publications. First, it analyzes tenant exit options contained in commercial leases in continental Europe and studies their impacts on portfolio value, management and risk. In the first paper, we consider tenant exit options included in commercial leases in continental Europe to better assess the value and risk of a real estate portfolio. This is achieved through the simultaneous use of Monte-Carlo simulations and option theory. The second article deals with the optimal holding period of a real estate portfolio when options contained in the leases are taken into account. The third article focuses on Value at Risk and proposes a model that takes into account the non-normality of real estate returns. This is obtained by combining the use of the Cornish-Fisher development and rearrangement procedures. Finally, in a last article, we present a model specially developed for the calculation of Value at Risk in real estate. This model has the particularity of taking into account the specificities of real estate and the parameters that have a greater influence on the value of assets.

This thesis contributes to academic research in real estate by providing a risk assessment for commercial real estate investment management. Real estate investment has many specificities such as location, liquidity, investment size or obsolescence and requires active management. These specificities make traditional risk measurement approaches difficult to apply. This research work is presented in the form of four academic papers dealing with portfolio management and risk in real estate. This work is built on the existing academic literature and is based on previous publications. First, it analyzes tenant exit options contained in commercial leases in continental Europe and studies their impacts on portfolio value, management and risk. In the first paper, we consider tenant exit options included in commercial leases in continental Europe to better assess the value and risk of a real estate portfolio. This is achieved through the simultaneous use of Monte-Carlo simulations and option theory. The second article deals with the optimal holding period of a real estate portfolio when options contained in the leases are taken into account. The third article focuses on Value at Risk and proposes a model that takes into account the non-normality of real estate returns. This is obtained by combining the use of the Cornish-Fisher development and rearrangement procedures. Finally, in a last article, we present a model specially developed for the calculation of Value at Risk in real estate. This model has the particularity of taking into account the specificities of real estate and the parameters that have a greater influence on the value of assets.