Public bikeshare systems have gained popularity in the United States over the past decade. This study examines the effect of bikeshare systems on property prices and the so-called metro station house price gradient, i.e., the curve that depicts the relationship between property prices and distance to the closest metro station. A priori, bikeshare can have ambiguous effects on residential property prices and the (metro station house) price gradient. It can provide amenities, e.g., by solving the last-mile problem for residents living within a certain radius of metro stations. On the other hand, it can have disamenity effects as more non-residents gain easier access to a neighborhood. Amenity and disamenity effects will affect property prices in opposing ways. The heterogeneous amenity and disamenity effects at different distances to metro stations, and the extent to which bikeshare and metro rail are complements or substitutes, can affect the price gradient. This study employs a hedonic regression model with difference-in-differences to analyze how residential property prices and the price gradient respond to the introduction of docked bikeshare in eight counties and cities of the Washington, DC metropolitan area. The study uses detailed property level transaction data from Zillow along with data on the locations and opening dates of Capital Bikeshare stations and metro stations. This study is the first to examine the effects of bikeshare systems on the price gradient in the North American context. Results show that introducing bikeshare stations near residential properties has no net effect on property prices or the price gradient. A conceptual model is developed to provide possible explanations for the results.