Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01c821gn75f
Title: | Deconstructing Airbnb: Pricing, Seasonality, and Optionality in the Sharing Economy |
Authors: | Tang, Timothy |
Advisors: | Mulvey, John |
Department: | Operations Research and Financial Engineering |
Certificate Program: | Center for Statistics and Machine Learning Finance Program Center for Statistics and Machine Learning Center for Statistics and Machine Learning |
Class Year: | 2020 |
Abstract: | The rapid growth of Airbnb, a virtual platform that allows users to quickly and efficiently rent and lease property, has caused significant disruption in the hospitality and real estate markets. Blurring the lines between hotel, rental, and residential properties, its short-term nature, accessibility, and versatility make it a promising resource for information-gathering and potential investment. We examine the relationship between Airbnb and broader economic factors by creating a regime-based market model through conventional economic metrics. We then use Monte Carlo simulation to evaluate pricing and listing strategies for a potential Airbnb property. |
URI: | http://arks.princeton.edu/ark:/88435/dsp01c821gn75f |
Type of Material: | Princeton University Senior Theses |
Language: | en |
Appears in Collections: | Operations Research and Financial Engineering, 2000-2019 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
TANG-TIMOTHY-THESIS.pdf | 1.5 MB | Adobe PDF | Request a copy |
Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.