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Can't travel? Don't want to travel? LFS LiveLFS Live brings the class to you!

  • Live interactive training from world renowned practitioners in the comfort of your own home
  • Real classroom experience without the inconvenience of travel
  • World class teaching from the comfort of your preferred location

Please contact us for more information at info@londonfs.com.

Course Calendar Course Calendar

Asset Allocation and Portfolio Construction

This program covers the latest trends in quantitative modelling for asset allocation and portfolio construction and highlights approaches which help improving real-world in investment decision processes by taking into account risk factors, capital market scenarios, estimation risk and generally real-world aspects in applied investing beyond mean-variance.

Innovations suggested over the last twenty years are contrasted with current industry practice and illustrated with examples with an eye for practical implementation. Perspectives are provided on latest industry trends like Smart Beta and Machine Learning / Artificial Intelligence.

Six practical exercises simulate real-life key decisions in asset allocation and portfolio construction. Mathematical concepts are discussed and illustrated using Excel spreadsheets that delegates can take away.

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  • Date:
  • Venue:
  • This course is only available via LFS LiveLFS Live
  • Fee:
  • £1440 per day
    £4320 total

This course is also available in New York Time Zone, Singapore Time Zone and Sydney

Who The Course is For
  • Quants / Financial engineers
  • Chief Investment Officers
  • Portfolio and investment managers
  • Fund and wealth managers
  • Treasury and liquidity managers
  • Risk managers
  • Traders
  • Strategists
Learning Objectives
  • Comprehensive discussion of different approaches to portfolio construction
  • Latest research trends and industry best practice and implications for practitioners
  • Practical suggestions on estimation risk, model risk and advanced topics
  • Workshops on all models and detailed teaching on quantitative concepts
Prior Knowledge
  • Basic knowledge of financial markets, asset classes and derivative instruments
  • Elementary mathematics and statistics (probability distributions mean, variance and correlation)
  • Microsoft Excel

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