In this work, we focus on the problem of loss function design in the context of Intermittent Demand Forecasting (IDF). In particular, this paper aims to resolve two shortcomings of an existing metric that has been introduced in prior work, namely Stock-keeping-oriented Prediction Error Costs (SPEC). We introduce our own loss function based on some of the same core assumptions made for the design of SPEC. More concretely, our loss also distinguishes stock-keeping and opportunity costs. However, contrary to SPEC, our loss is also applicable to time series that exhibit negative values. Furthermore, we define a set of hyperparameters that enable us to introduce nonlinear temporal dependencies in our loss calculation.      «

In this work, we focus on the problem of loss function design in the context of Intermittent Demand Forecasting (IDF). In particular, this paper aims to resolve two shortcomings of an existing metric that has been introduced in prior work, namely Stock-keeping-oriented Prediction Error Costs (SPEC). We introduce our own loss function based on some of the same core assumptions made for the design of SPEC. More concretely, our loss also distinguishes stock-keeping and opportunity costs. However, c...     »