Quantitative Investment in Art Assets
Company was acquired
Event Year: 2016
Company was acquired
Event Year: 2016
Arthena provided a unique financial product, granting access to the alternative asset class of art, known for its high barriers to entry and historically strong returns. The company focused on the most liquid segment of the art market, characterized by low volatility and significant growth potential uncorrelated with traditional investments. Arthena's core innovation was an automated, data-driven investment strategy that structured art investment using traditional fund frameworks. This allowed high-net-worth individuals (HNWIs) to diversify their portfolios securely and confidently into alternative assets within the luxury market. Arthena developed a statistically rigorous model to estimate artwork value over time, leveraging data from auction records and repeat sales. The model incorporated features such as artist name, medium, creation date, origin, and artwork size. By identifying similar groups of artworks, Arthena calculated expected ROI and estimated volatility based on gain distributions. Historical auction results were used to simulate fund performance, with Monte Carlo analysis determining annualized returns and Sharpe ratios. This comprehensive analysis enabled Arthena to validate the financial viability of its product and establish statistically sound bounds for its estimates.
Arthena provided a unique financial product, granting access to the alternative asset class of art, known for its high barriers to entry and historically strong returns. The company focused on the most liquid segment of the art market, characterized by low volatility and significant growth potential uncorrelated with traditional investments. Arthena's core innovation was an automated, data-driven investment strategy that structured art investment using traditional fund frameworks. This allowed high-net-worth individuals (HNWIs) to diversify their portfolios securely and confidently into alternative assets within the luxury market. Arthena developed a statistically rigorous model to estimate artwork value over time, leveraging data from auction records and repeat sales. The model incorporated features such as artist name, medium, creation date, origin, and artwork size. By identifying similar groups of artworks, Arthena calculated expected ROI and estimated volatility based on gain distributions. Historical auction results were used to simulate fund performance, with Monte Carlo analysis determining annualized returns and Sharpe ratios. This comprehensive analysis enabled Arthena to validate the financial viability of its product and establish statistically sound bounds for its estimates.
Total Raised: Unknown (Y Combinator backed)
Last Round: Winter 2017
Total Raised: Unknown (Y Combinator backed)
Last Round: Winter 2017
Fintech
Fintech
Fintech -> Asset Management
Fintech -> Asset Management
Team size: 12
Hiring: No
Team size: 12
Hiring: No