Decision making and planning under low levels of predictability
By Spyros Makridakis, Nassim Nicholas Taleb. 2009
97 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Konstantinos Nikolopoulos
- Fotios Petropoulos
- Evangelos Spiliotis
- Rob J Hyndman
- Vassilios Assimakopoulos
- Spyros Makridakis
- Rafal Weron
- Nikolaos Kourentzes
In Management Science and Operations Research
- Fotios Petropoulos
- Konstantinos Nikolopoulos
- Evangelos Spiliotis
- Vassilios Assimakopoulos
- Rob J Hyndman
- Spyros Makridakis
- Christoph Bergmeir
- Nikolaos Kourentzes
Citations in the corpus
- Forecasting in social settings: The state of the art (2020, background): “Now it is accepted that Gaussian distributions, although extremely useful, are of limited value to approximate some areas of applications (Cooke, Nieboer, Misiewicz, 2014; Makridakis and Taleb, 2009), in particular in those referring to forecast error distributions, describing the uncertainty in for”
- Predictive Analytics in Information Systems Research (2011, unknown): “Knowledge of predictability (or unpredictability) is a fundamental component of scientific knowledge (see Mak-ridakis et al. 2009; Makridakis and Taleb 2009; Taleb 2007).”
- Tales from tails: On the empirical distributions of forecasting errors and their implication to risk (2019, background): “Undoubtedly, the risk of large errors cannot be reliably assessed (Makridakis & Taleb, 2009).”