1. Probabilistic demand forecasting Prepared & presented by Daniel SALLIER Traffic Data & Forecasting Director Aéroports de Paris [email_address] 01 70 03 45 68

4. Foreground

8. How to cope with the intrinsic technical uncertainty

15. The data aggregation / break-up issue

19. Part of the prospective uncertainty: the residual issue

21. Taking into account part of the prospective risk (continued) There is ground here for the development of specific financial / management / industrial tools and policies to cover part of this latent risk 0% 5% 10% 15% 20% 25% -25% -20% -15% -10% -5% 0% 5% 10% 15% Residuals (% of total pax) Probability Probability distribution of the residuals 0 2 4 6 8 10 12 14 16 18 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand (M pax) Actual traffic data 50% probability for the demand to be greater or equal No residuals 98% probability range No residuals 0 2 4 6 8 10 12 14 16 18 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand (M pax) Actual traffic data 50% probability for the demand to be greater or equal Residuals included 98% probability range Residuals included 0 2 4 6 8 10 12 14 16 18 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand (M pax) Actual traffic data 50% probability for the demand to be greater or equal No residuals 98% probability range No residuals 0 2 4 6 8 10 12 14 16 18 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand (M pax) Actual traffic data 50% probability for the demand to be greater or equal Residuals included 98% probability range Residuals included 0 2 4 6 8 10 12 14 16 18 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand (M pax) Actual traffic data 50% probability for the demand to be greater or equal No residuals 98% probability range No residuals 50% probability for the demand to be greater or equal Residuals included 98% probability range Residuals included

22. Further developments and applications

24. Horizontal cuts for most of the mid & long term utilisation 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 Traffic/demand Actual capacity etc. To be mostly used for optimal dimensioning and planning of mid and long term capacity growth: heavy investments Planned capacity Annual 50% probability - actual capacity 50% probability - planned capacity 98% centred probability - actual capacity 98% centred probability - planned capacity Year 0 Operating profit

25. Conclusions