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Wilms, Ines; Gelper, Sarah; Croux, Christophe - In: European journal of operational research : EJOR 254 (2016) 1, pp. 138-147

Persistent link: https://www.econbiz.de/10011503231

Model selection and post selection to improve the estimation of the ARCH model

Al-Momani, Marwan; Dawod, Abdaljbbar B. A. - In: Journal of risk and financial management : JRFM 15 (2022) 4, pp. 1-17

The Autoregressive Conditionally Heteroscedastic (ARCH) model is useful for handling volatilities in economical time series phenomena that ARIMA models are unable to handle. The ARCH model has been adopted in many applications that contain time series data such as financial market prices,...

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Exploring the sources of uncertainty : why does bagging for time series forecasting work?

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Statistical testing of optimality conditions in multiresponse simulation-based optimization

Bettonvil, Bert; Del Castillo, Enrique; Kleijnen, Jack P. C. - In: European journal of operational research : EJOR 199 (2009) 2, pp. 448-458

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Optimal operation of hydrothermal systems with hydrological scenario generation through Bootstrap and Periodic Autoregressive Models

Souza, Reinaldo Castro; Marcato, André Luís Marques; … - In: European journal of operational research : EJOR 222 (2012) 3, pp. 606-615

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Measuring the efficiency of highway maintenance contracting strategies : a bootstrapped non-parametric meta-frontier approach

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Rankings and university performance: A conditional multidimensional approach

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A Tabu Search heuristic procedure in Markov chain bootstrapping

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Theoretical and empirical estimates of mean-variance portfolop sensitivity

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Directional distances and their robust versions : computational and testing issues

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