about

Last Updated: 05/05/23

Background & Credentials

The Watches.io team brings together experts across finance, accounting, and engineering from industry leading firms and companies. We are experienced watch traders with over 40 years of combined experience, and have leveraged our extensive network of connections in the luxury watch industry to gain access to very closely held sources of data and ensure we are always at the forefront of any market moving events.

Appraisal Capabilities

Appraisals for all our watches are given on the proven basis that each watch is in perfect working condition without any signs of material damage, and included is the original manufacturer box and authentic serial numbered card or documentation.

To be eligible for our market appraisal, all watches must undergo an inspection by verified watchmakers and high-precision tooling/microscopes and be verified against databases of stolen watches.

Our appraisals consist of the following information:

1. The current fair market value of each timepiece.
2. Proprietary grading for liquidity of the market around that specific watch model.
3. Time weighted volatility estimates for that model.
4. Interval bounded price performance for that model, such as 3-month highs and lows.

Appraisals do not include any forward-looking estimates on price fluctuation.

Technology

We have a highly scalable and reliable system set up to constantly intake and process market data in order to generate as close to real time market models as possible.

Methodology

We consider three main sources of data for our modeling and estimation capabilities:

1. Public Sources including marketplaces, direct to consumer online storefronts, and market aggregators.
2. Private Sources including exclusive trading groups and OTC dealer channels.
3. Industry Constituents including our network of traders, jewelers, and other active buyers of luxury watches.

Our appraisals are based on an analysis of multiple indicators:

1. Internal ranking of each data source based on deviation from mean price values, objective accuracy of information, reliability, and relationship.
2. Pricing nuances of each piece across each data source, considering regional differences in price, production year and condition, marketplace fees, and estimated target profit margins. 
3. Estimations of liquidity for a given model based on the number and frequency of listings, offers, and completed sales as well as the price spread across each data source.
4. Market volatility for each unique model, model line, and manufacturer across different time intervals.