EPAT project presentations on “Portfolio Asset Allocation with Machine Learning: A Practical and Scalable Framework for Machine Learning Development” by two of our esteemed EPAT alumni by Raimondo Marino from Milan, Italy and “Portfolio Optimization for Dividend Stocks” by Kurt Selleslagh from Singapore.

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Chapters:
00:00 Introduction
05:04 Agenda Project 1: Portfolio Assets Allocation
06:22 Ingredient
08:42 The lowmedium FT framework
09:54 What you need
13:34 The machine learning pipeline (1/3)
19:49 The machine learning pipeline (2/3)
21:44 Results of parameter optimization
24:29 The machine learning pipeline (3/3)
26:29 Money management: Montecarlo simulation
28:16 What I learned from EPAT
31:39 Q&A 1
41:06 Agenda Project 2: Portfolio Optimization for Dividend Stocks
43:39 Approach (Step 1 of 6)
46:19 Approach (Step 2 of 6)
48:29 Approach (Step 3 of 6)
53:11 Approach (Step 4 of 6)
55:20 Approach (Step 5 of 6)
56:01 Approach (Step 6 of 6)
59:00 Challenges
01:00:37 Next Steps
01:02:22 Q&A 1

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