Walnut Algorithms combines machine learning and data science for asset management

Country: Francewalnut algorithms

Year: 2015

Concept

  • Paris-based start-up, Walnut Algorithms, aims to guarantee higher investment returns on portfolios through its investment strategies combining machine learning and data science
  • The artificial-intelligence hedge fund uses algorithms to confidently spot trading patterns, including intraday ones in financial markets for more efficient trading
  • The resulting data is aggregated and forms the basis of Walnut Algorithms’ trading strategies
  • After analysing and learning from ten years of market data, Walnut looks at between 2000 and 3000 data points per second, creating a snapshot of the market and predicts probable outcomes
  • Walnut Algorithms plans to start trading liquid equity-index futures through Interactive Brokers on the Chicago Mercantile Exchange (CME), typically holding positions on an average of between two and four hours

Consumer Benefits

  • Higher returns for end consumers: With an average performance of 15% and average volatility of 8-10% compared to traditional performance of around 4-5%
  • Reduce human error: through machine learning and deep learning quantitative finance

How To Use

Currently unavailable, Walnut Algorithms will start managing third party assets from the beginning of 2017.

Illustration

Startupbootcamp takes a look at Walnut Algorithms