Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/126942
Título: Modelling prices and volatilities in the sharing economy
Autores/as: Pérez Rodríguez, Jorge Vicente 
Hernández Guerra, Juan María 
Andrada Félix, Julián 
Clasificación UNESCO: 5302 Econometría
Palabras clave: Arfima-Hygarch Models
Average Daily Prices
Fractional Modelling
Long Short-Term Memory
Machine Learning Forecasts, et al.
Fecha de publicación: 2023
Publicación seriada: Tourism Economics 
Resumen: This paper examines whether short-term rental listings in the sharing accommodation market take account of market risk in their pricing. To do so, we estimate time-varying market risks, and forecast price changes using daily supply-price time series. The empirical analysis was conducted using daily data for the Canary Islands sharing accommodation market for the period January 2016 to September 2021. The following main results were obtained. First, individual listings face systematic risks that are lower than the average market listing return, but multi-unit hosts are more sensitive to market index variations than single-unit hosts. Second, there is a time-varying but long-range dependence on market risk, indicating a slow reversion to the mean level of volatility. Price changes also reflect negative long-range dependence or anti-persistence. Third, volatility does not affect price adjustments in the market (no evidence of risk-return trade-off) for types of hosts and lodgings. Fourth, models can be used to perform risk management using value-at-risk approaches, and market risks are greater for houses and single-unit hosts in the GBP market. Finally, prices can be predicted in different horizons using long-range dependence models.
URI: http://hdl.handle.net/10553/126942
ISSN: 1354-8166
DOI: 10.1177/13548166231200932
Fuente: Tourism Economics[ISSN 1354-8166], (Enero 2023)
Colección:Artículos
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