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.

In this paper, the heterogeneity of the Paris apartment market is addressed through assessing the differences in the hedonic price of housing attributes over the 2000-2006 period for various price, hence income, segments of the housing market. For that purpose, quantile regression is applied to the 20 Paris "arrondissements" as well as to the 80 neighborhoods, called "quartiers" -or quarters -(each "arrondissement" is composed of four quarters), with market segmentation being based on price deciles (deciles 1 to 9). The database includes some 159,000 sales spread over a seven year period (2000 -2006). Housing descriptors include, among other things, a price index, building age, apartment size, number of rooms and bathrooms, unit floor level, the presence of a lift and of a garage, the type of street and access to building (boulevard, square, alley, etc.) as well as a series of location dummy variables standing for both the "arrondissements" and the quarters.Findings clearly suggest that hedonic "relative" prices of several housing attributes significantly differ among deciles, although discrepancies tend to vary greatly in magnitude depending on the attribute. Among other findings, the elasticity coefficient of the size variable, which stands at 1.07 for the first price decile (cheapest units), is down to 1.03 for units belonging to the ninth one (dearest units). The number of rooms, of service rooms, of bathrooms, the housing type, the apartment floor level as well as the number of parking slots all exhibit strong implicit price fluctuations among deciles while it is less so for the building period that affect prices in a more uniform way. Finally, the lower the apartment price, the higher the potential for price appreciation over time.

This paper aims to show that the accuracy of real estate portfolio valuations can be improved through the simultaneous use of Monte Carlo simulations and options theory. Our method considers the options embedded in Continental European lease contracts drawn up with tenants who may move before the end of the contract. We combine Monte Carlo simulations for both market prices and rental values with an optional model that takes into account a rational tenant's behavior. We analyze to what extent the options exercised by the tenant significantly affect the owner's income. Our main findings are that simulated cash flows which take account of such options are more reliable that those usually computed by the traditional method of discounted cash flow. Moreover, this approach provides interesting metrics, such as the distribution of cash flows. The originality of this research lies in the possibility of taking the structure of the lease into account. In practice this model could be used by professionals to improve the relevance of their valuations: the output as a distribution of outcomes should be of interest to investors. However, some limitations are inherent to our model: these include the assumption of the rationality of tenant's decisions, and the difficulty of calibrating the model, given the lack of data. After a brief literature review of simulation methods used for real estate valuation, the paper describes the suggested simulation model, its main assumptions, and the incorporation of tenant's decisions regarding break options influencing the cash flows. Finally, using an empirical example, we analyze the sensitivity of the model to various parameters, test its robustness and note some limitations.

No abstract