4 papers
nabqr: Python package for improving probabilistic forecasts
Bastian Schmidt Jørgensena, Jan Kloppenborg Møller, Peter Nystrup +1
We introduce the open-source Python package NABQR: Neural Adaptive Basis for (time-adaptive) Quantile Regression that provides reliable probabilistic forecasts. NABQR corrects ense…
Optimal Forecast Reconciliation with Uncertainty Quantification
Jan Kloppenborg Møller, Peter Nystrup, Poul G. Hjorth +1
We propose to estimate the weight matrix used for forecast reconciliation as parameters in a general linear model in order to quantify its uncertainty. This implies that forecast r…
Multi-Period Trading via Convex Optimization
Stephen Boyd, Enzo Busseti, Steven Diamond +4
We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, wher…
Greedy Gaussian Segmentation of Multivariate Time Series
David Hallac, Peter Nystrup, Stephen Boyd
We consider the problem of breaking a multivariate (vector) time series into segments over which the data is well explained as independent samples from a Gaussian distribution. We…