World Business StrategiesServing the Global Financial Community since 2000

Workshop Day

From Quantitative Finance to Artificial Finance Workshop 

In this new workshop we will help the delegates to successfully transition from traditional quantitative finance to artificial finance. We will explore the mathematics, the rationale and code of the new machine learning and artificial intelligence models in finance.

Miquel Noguer Alonso:

Co-Founder at Artificial Intelligence Finance Institute – AIFI

Miquel Noguer Alonso: Co-Founder at Artificial Intelligence Finance Institute – AIFI

Miquel Noguer i Alonso is a financial markets practitioner with more than 20 years of experience in asset management, he is currently working for UBS AG (Switzerland). He worked as a CFO and CIO for a European bank from 2000 to 2006. He started his career at KPMG.

He is Adjunct Assistant Professor at Columbia University teaching Asset Allocation, Big Data in Finance, Fintech and Hedge Fund Professor at ESADE. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain). He also holds the Certified European Financial Analyst diploma ( 2000 ).

His research interests range from asset allocation, big data to algorithmic trading and fintech. His academic collaborations include a visiting scholarship in Columbia University in 2013 in the Finance and Economics Department, in Fribourg University in 2010 in the mathematics department, and presentations in Indiana University, ESADE, London Business School, CAIA Association, AFI and several industry seminars.

Workshop Schedule: 09:00 – 17:30

Break: 10:30 – 11:00
Lunch: 12:30 – 13:30
Break: 15:15 – 15:30

  • Discount Structure
  • Super early bird discount
    25% until February 8th 2019

  • Early bird discount
    10% until March 1st 2019

  • Special Offer
    When two colleagues attend the 3rd goes free!

  • Conference + Workshop
    £150 Discount

  • 70% Academic Discount
    (FULL-TIME Students Only)

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