1 : Robots advisors to enhance investor satisfaction


“In-Boarding”, a quantitative model, calibrates “Investor Satisfaction Function”, using the answers of 4 questions.


“Investor” is required to provide, a self-declared schedule of investments and withdrawals, “Prospective Cash Flow”, representing his own investment goals, maturities and saving means


Monte Carlo method simulate the multi-period prospective accumulated wealth to optimize “Investor aim Probability”, at the maturity of Investor’s “Prospective Cash Flow”.
1 interacts with “Investor”, to settle his adequate balance, between, risk appetite, saving effort, and withdrawals, to optimize “Investor aim Probability”

3 : A.I. to manage systemic risks

From 02-2012 to 07-2014 interviews with top academics, diplomates, actual and former policymakers,
and investment strategists and officers, reduced the number of systemic risk driver and mapped them to:

  • States of the World, 3 Thematic Portfolios, Institutions, Governance, Levers, Decisions, People, Debated in Negotiations, justified by Key Performance Indicators and broadcasted by Media and Social Media.

The Ontology “Atacama” enriched daily from 07-2014 to 09-2015 using Natural Language Processing visualization tool, an average of 50,000 Articles, constituting Public Information, described in ”APP”.

Data science artefacts translated three models’ variables and specifics : Game Theory Model, Smart beta portfolio building model, calibrating twenty four 3 Thematic Portfolios, constituting 3 Investment Universe, and Quantitative models, deriving from 3 Thematic Portfolios past performances and volatilities, the implied probability of a State of the World occurrence, called “State of the World’ Objective Probability”.


  • Global Macro
  • Target Vol 10%
  • μ 15,85%
  • 𝜎 5,64%
  • Sharpe 2,81
  • Sortino 6,67
  • DD 2,57%
  • VaR 0,72%

« Nous n’avons pas identifié d’erreur arithmétique dans le calcul de la performance du portefeuille. »

Mazars France

The 3 models :

  • derive “Nash Equilibria”, game Strategies combinations, that maximize People Satisfaction Function, such that, any Strategy change, would decrease, at least, one People Satisfaction Function
  • map the Nash Equilibria to State of the World and 3 Thematic Portfolios
  • quantify the probability that State of the World occurs equal to the probability that KPIs converge to  goals, targeted by People, called “State of the World Subjective Probability”
  • finally, by setting State of the World Objective and Subjective Probabilities, as inputs to Asset Allocation, a quantitative model, 3 quantifies the risk budget allocation, to Investment Universe. The portfolio obtained is called “Optimal Risk Allocation, advised by 3”

Preuve du Concept

Du 30/12/2014 au 31/08/2015, le Portefeuille Modèle, géré en stratégie Global Macro, conseillé par 3, avec un objectif de volatilité de 10%.

1. Identification désamarrage du Franc Suisse sur l’Euro et rebond des marchés actions Européens.

2. Rebond des marchés actions Chinois.

3. Rebond des prix des hydrocarbures.

4. Baisse des marchés actions Européens et hausse des taux d’intérêts.

5. Rebond des marchés actions japonais.

6. Craintes sur l’avenir de la Zone Euro.

7. Baisse des taux d’intérêts.

8. Accord sur le nucléaire Iranien et maintien de la Grèce dans la Zone Euro.

9. Dévaluation du Yuan et baisse des matières premières.