Abstract
Two key features of airline departure delays are that they cascade and that there can be exceptional peaks. We model these features using an intensity-based Hawkes process. Our application to all KLM departure delays at Amsterdam Schiphol airport in January 2015 shows that volatility in departure delays is endogenous. We correlate the key parameters of the estimated Hawkes process with daily weather conditions and find that these conditions amplify the self-exciting feature of departure delays.
Original language | English |
---|---|
Pages (from-to) | 863-874 |
Number of pages | 12 |
Journal | Applied Stochastic Models in Business and Industry |
Volume | 40 |
Issue number | 4 |
DOIs | |
Publication status | E-pub ahead of print - 13 Feb 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons Ltd.