Winner of"Arab geniuses" For the Economics category: The award commemorates the scientific and artistic legacy of the Arab world

DUBAI, 6 JANUARY / WAM / Algerian Professor Yacine Ait Sahalia, Professor of Finance and Economics at Princeton University and winner of the “Arab Geniuses” Award 2024 in the Economics category, confirmed that this award provides role models for young people in the region, and that such awards remind the world of the scientific legacy. The great artist of the Arab world, expressing his hope that it will contribute to enhancing its renaissance.
He considered it a distinguished initiative because it showcases success stories in the sciences and arts, noting that winning the award and recognizing his academic achievements represents a great honor for him on both the personal and professional levels.
Professor Yassin Ait Sahalia said in a statement to the Emirates News Agency, WAM, that the UAE’s economy has succeeded in diversifying its sources away from oil, with significant contributions from tourism, real estate, logistics, trade, financial services, and technology.
He added that the focus on knowledge-based industries, and investments in research and development to support artificial intelligence, renewable energy and biotechnology are very smart strategic steps on the part of the UAE to continue its development.
He stressed the power and impact of education in raising the level of a person and his society, noting that he did not expect to be part of a group of distinguished scholars and artists in various disciplines who were honored this year with the “Geniuses of the Arabs” award.
In recognition of his contributions to developing theories and methodologies of financial market analysis and economic planning, the award-winning professor touched on his research on high-frequency financial data, explaining its nature and impact on financial markets.
High-frequency data refers to financial information recorded over very short periods of time, such as every second or millisecond, which captures trades and price changes in real time, he said.
He added that he focused his work on trying to understand this flood of data using mathematical models, with the aim of understanding price movements, market risks and small fluctuations that occur in a fraction of a thousandth of a second but can have a significant impact on the markets, and this can help market participants and regulators. In detecting unusual market behavior or risks faster and more accurately.
He pointed out that many financial companies adopt high-frequency trading strategies, which have become an essential source of liquidity in the markets.
He explained that the financial industry has invested heavily in computing infrastructure to process and analyze high-frequency data, while regulators use these models to monitor and stabilize markets, protect small investors and ensure transparency.
Regarding the most prominent challenges facing financial markets, he pointed to market fluctuations and uncertainty resulting from geopolitical tensions and economic instability, in addition to the emergence of decentralized finance and cryptocurrencies as a new source of risks to traditional financial systems, in addition to the technological challenges and cyber risks resulting from digital trading systems and algorithms.
He stated that some of his recent research aims to address these risks by analyzing the strategies of high-frequency trading companies and making informed predictions about their likely behavior in different market situations.
Regarding the horizon and development of financial economic measurement, he explained that this field is increasingly adopting machine learning and data science tools, pointing out that these methods allow analyzing big data in two dimensions, including the frequency of observations and the number of variables that are analyzed simultaneously.
Professor Sahaliya advised young researchers in the field of finance and economics in the Arab world to start with the basics of economics, finance, and mathematical methods, and learn about machine learning methods, whose role is growing in finance and economics, in addition to attending international conferences, webinars, and workshops to communicate with other researchers.

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