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Aeroporti de roma fco

It is three page analysis for FCO airport - Aeroporti de Roma i.e 2018-2019-2020

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Aeroporti de roma fco

  1. 1. Airport Forecasting - 2020 (Issue No. 39) Aeroporti di Roma (FCO) Annual Passengers Forecast: The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. First – General Trend Model using the concept of Straight Line equation – defining general trend. Second – Most Recent Data Trend Model Using a Polynomial Model – Second-degree equation. This reflects the impact of most recent data on the path of generaltrend. The mid-point is the most convenient forecast annual result at Dec 2020. So as long as the gap between two models is small, the more accurate approaching value for setting annual target otherwise we have to select the half way distance between two extreme targets of these two models provided that Dec 2020 > Dec 2019. Scenario 1: Preset Annual Target = Passengers = 45,062,311 Pax. At 4.20 % Annual Growth (recommend) Scenario 2: Optimum Solution. = Passengers = 45,210,976 Pax. The objective is to minimize the risk of not achieving the desired goals. Both scenarios are fairs, and the results are good. The first scenario is fair enough to select, as it has lower growth, we recommend the 1st scenario, to avoid the high-risk passenger growth that mislead the final results. By: Mohammed Salem Awad Aviation Consultant Data Source: http://www.adr.it/web/aeroporti- di-roma-en-/bsn-traffic-data
  2. 2. Airport Forecasting - 2019 Issue No. ( 12 / 2019) Airport Traffic Passengers Forecast - 2019 (FCO) All Roads Lead To Rome In spite of the high discrepancy of annual trend models, the seasonality analysis shows a fair result. While the general role is, the model will be fair when R-square is greater than 80% and S.T is less than ± 4. Usually, we have two approaches: 1- Scenario 1 : Preset AnnualTarget = ForecastPax = 42,767,887 2- Scenario 2 : Optimum Solution. Forecast Pax = 42,443,868 (recommended) The objective is to minimize the risk of not achieving the desired goals. (Select one who has lower growth). The Second scenario is fair enough to select, as it has lower Growth, higher R-square,and lower range of Single Tracking; therefore,we recommend the second one, to avoid the high-risk passenger growth. By: Mohammed Salem Awad Aviation Consultant Data Source: http://www.adr.it/web/aeroporti-di- roma-en-/bsn-traffic-data
  3. 3. Airport Forecasting - 2018 (Issue No. 77) Aeroporti di Roma (FCO) Annually Forecast: The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. Here we implement two trend models by using Add a trend line in XLS sheet: First – General Trend Model using the concept of Straight Line equation – defining general trend. Second – Most Recent Data Trend Model Using a Polynomial Model – Second-degree equation. This reflects the impact of most recent data on the path of general trend. The mid-point is the most convenient forecast annual result at Dec 2018. So as long as the gap between two models is small, the more accurate approaching value for setting annual target otherwise we have to select the half way distance between two extreme targets of these two models provided that Dec 2018 > Dec 2017. Monthly Forecast – we define the monthly targets that fulfill the condition of the first point (annual traffic setting forecast 2018 = 41,851,234 Pax) with minimum errors. Which shows a fair result in the second graph, at R-squared = 98.48 %, AnnualGrowth = 0.88 % and a clear picture about the seasonality pattern of the airport is defined as shown in table and graph. By: Mohammed Salem Awad Aviation Consultant Data Source:www.anna.aero

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