Yaron Golgher at AI Panel Discussion for FWO Trading Israel Derivatives Conference

January 28, 2020
derivatives

FOW Derivatives Israel Conference

The fourth annual FOW Derivatives Israel conference will be held at the Sheraton Hotel in Tel Aviv on February 26. Global Investor Group comes to Israel in February 2020 – it will host a third time the largest derivatives conference in the region. This FWO conference will cover many topics and present panel discussions on a few key matters – International Trading, The Future of Liquidity, Technology Innovation, The Opportunities for Israel and Artificial Intelligence / Big Data / ABCD innovation.

Yaron Golgher will be representing I Know First at AI panel discussion to be held at 3pm. Among the panelist will also be Daniel Giamouridis, Global Head of Scientific Implementation Data and innovation Group, BAML, Chris Jenkins (Co-Head, ZISHI, part of OSTC Group), Didier Essemini (Finotec Trading) and Rahav Shalom (Israel’s Fintech Cyber Innovation Lab, Ministry of Finance). The major topics to be discussed are:

  • How is the application of artificial intelligence based on Big Data changing the derivatives markets?
  • How do firms differentiate themselves in a market where Artificial Intelligence is prevalent?
  • What are the risks associated with the widespread adoption of artificial intelligence technologies?

Many leading experts from the best asset managers, hedge funds, prop trading firms, market-makers, brokers, banks and exchanges in Israel, Europe and further afield will discuss the main issues, opportunities and challenges facing the industry today. As of now, more than 250 delegates are expected to attend the event to showcase a cross-section of the rich and booming Israeli financial technology and services ecosystem.

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I Know First, Ltd. is a financial technology company that provides daily investment forecasts based on an advanced, self-learning algorithm. Thus, the company’s algorithm predicts over 10,500 securities (and growing). Thus, it has capabilities to discover patterns in large sets of historical stock market data.

The underlying technology of the algorithm based itself on Artificial Intelligence. It also based itself on machine learning and incorporating elements of artificial neural networks and genetic algorithms. Moreover, the algorithm generates daily market predictions for stocks, commodities, ETF’s, interest rates, currencies, and world indices for the short, medium and long-term time horizons.

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