4 citations · 5 across the 5 of their papers we have counts for
6 papers
High-Frequency Pricing at Scale for E-Commerce
Stefan Birr, Tobias Huelden, Mones Raslan +7
This paper presents the design, development, and implementation of a specialized forecast-then-optimize algorithmic pricing tool for sales campaigns in fashion e-commerce. Sales ev…
Hierarchical Time Series Forecasting Via Latent Mean Encoding
Alessandro Salatiello, Stefan Birr, Manuel Kunz
Coherently forecasting the behaviour of a target variable across both coarse and fine temporal scales is crucial for profit-optimized decision-making in several business applicatio…
Deep Learning based Forecasting: a case study from the online fashion industry
Manuel Kunz, Stefan Birr, Mones Raslan +13
Demand forecasting in the online fashion industry is particularly amendable to global, data-driven forecasting models because of the industry's set of particular challenges. These…
Model assessment for time series dynamics using copula spectral densities: a graphical tool
Stefan Birr, Tobias Kley, Stanislav Volgushev
Finding parametric models that accurately describe the dependence structure of observed data is a central task in the analysis of time series. Classical frequency domain methods pr…
On Wigner-Ville Spectra and the Unicity of Time-Varying Quantile-Based Spectral Densities
Stefan Birr, Holger Dette, Marc Hallin +2
The unicity of the time-varying quantile-based spectrum proposed in Birr et al. (2016) is established via an asymptotic representation result involving Wigner-Ville spectra.
Quantile Spectral Analysis for Locally Stationary Time Series
Stefan Birr, Stanislav Volgushev, Tobias Kley +2
Classical spectral methods are subject to two fundamental limitations: they only can account for covariance-related serial dependencies, and they require second-order stationarity.…