Oliver Linton, Faculty of Economics, University of Cambridge, Keynote at Foremost London HFT Summit

Golden Networking hosts the World's Most Influential High-Frequency Trading Conference Series, High Frequency Trading Leaders Forum 2013 London "Strategic and Tactical Insights for Investors, Speed Traders, Brokers and Exchanges", December 5 (www.HFTLeadersForum).

New York City, NY, USA (November 10, 2013) -- Professor Oliver Linton, Chair of Political Economy at Cambridge University and Foresight Project Member of the Lead Expert Group on Algorithmic and High-Frequency Trading, will speak at High-Frequency Trading Leaders Forum 2013,"Strategic and Tactical Insights for Investors, Speed Traders, Brokers and Exchanges" (http://www.HFT-Leaders-Forum.com), organized by Golden Networking, forum that will bring the latest on speed trading to one of the world's financial capitals, London, on December 5.

Professor Linton is a member of the Government Office for Science Foresight Lead Expert Group on The Future of Computer Trading in Financial Markets. Their final report, published in 2012, sheds new light on technological advances which have transformed market structures in recent years. This independent and international study has involved 150 leading experts from more 20 countries to provide the best possible analysis on computer trading to date. Sponsored by Her Majesty's Treasury, the project was led by the Government Office for Science under the direction of the Government's Chief Scientific Adviser, Professor Sir John Beddington. It has involved leading experts in the field and explored how computer generated trading in financial markets will evolve over the next 10 years. It assembled and analyzed evidence on the effect of HFT on financial markets looking out to 2022.

Professor Linton holds the Chair of Political Economy at Cambridge University, having previously held the post of Professor of Econometrics at the London School of Economics. He is a Fellow of the Econometric Society, of the Institute of Mathematical Statistics and of the British Academy. A former Professor of Economics at Yale University, he is the author of over one hundred articles in the areas of econometric theory and financial econometrics. Within financial econometrics he is interested in high frequency data and in low frequency panel data issues.

His research interests are nonparametric and semiparametric methods, particularly as applied to bandwidth choice and to efficiency comparisons between first order equivalent procedures, leading to examination of practical problems such as how to choose bandwidth, the curse of dimensionality, and how to obtain good approximations to the actual sampling variability of the estimators. He is also interested in financial econometrics. Professor Linton has also acted in a consulting or advisory capacity for (among others) Hargreaves Lansdown, Rio Tinto, the Financial Services Authority (FSA), Royal and Sun Alliance and Concordia Asset Management.

High-Frequency Trading Leaders Forum 2013 (http://www.High-Frequency-Trading-Conference.com) "Strategic and Tactical Insights for Investors, Speed Traders, Brokers and Exchanges" will bring insights for investors and speed traders, who need to protect and refine their competitive advantage in a world dominated by algorithmic and high-frequency trading. Recognized practitioners, regulators, experts, and strategists will return to High-Frequency Trading Leaders Forum 2013 London to provide hundreds of attendees with the information they are looking for in an open and unbiased environment, highly conducive to the most efficient and effective networking.

High Frequency Trading Leaders Forum 2013 is produced by Golden Networking (http://www.goldennetworking.com), the premier networking community for business executives, entrepreneurs and investors. Panelists, speakers and sponsors are invited to contact Golden Networking by calling +1-414-FORUMS0 or sending an email to information@goldennetworking.com.

Media Contact:
Julia Petrova
Media Relations Coordinator
Golden Networking

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