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Outline:

  • Using machine learning in the new financial markets big data landscape
  • Big Data in Finance Landscape
  • Infrastructure and technologyData sources
  • Modern data analysis - Structured and Unstructured Data & New Models
  • Classical and advanced models
  • Machine Learning models in practice
  • Machine learning robust modeling
  • The future of machine learning in finance

Big Data in Finance Landscape

  • Big data in finance landscape: Financial modeling, data governance, integration, NoSQL, batch and real-time computing and storage

  • Infrastructure and technology

  • New data sources

  • Modern data analysis: Structured / Unstructured data and new models 


Machine Learning Models

  • Supervised learning

  • Unsupervised learning

  • Reinforcement learning

  • Deep learning

  • Advanced machine learning models


Machine learning in finance - Practice

  • Momentum and Mean Reversion

  • Sentiment Analysis

  • Asymmetric Trading Strategies

  • Non Linear Multi-Factor Models

  • High Frequency Trading

  • Advanced Machine Learning


Machine learning in finance - Opportunities and challenges

  • Algo-Grading 101

  • Interpretation

  • Data mining biases: overfitting, survivorship and data-snooping

  • Robust trading strategies

  • The future of machine learning in finance


Course Tutor:

Miquel Noguer Alonso: Adjunct Assistant Professor, COLUMBIA UNIVERSITY

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 – 10:45
Lunch: 12:30 – 13:30
Break: 15:15 – 15:30