We propose four different estimators that take into account the autocorrelation structure when
reconciling forecasts in a temporal hierarchy. Combining forecasts from multiple temporal …

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, where …

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 …

Regime-based asset allocation has been shown to add value over rebalancing to static
weights and, in particular, reduce potential drawdowns by reacting to changes in market …

Hidden Markov models are often applied in quantitative finance to capture the stylised facts
of financial returns. They are usually discrete-time models and the number of states rarely …

The intermittency of renewable energy sources, such as wind and solar, means that they
require reliable and accurate forecasts to integrate properly into energy systems. This review …

In this article, model predictive control is used to dynamically optimize an investment portfolio
and control drawdowns. The control is based on multi-period forecasts of the mean and …

Hidden Markov models are often used to model daily returns and to infer the hidden state of
financial markets. Previous studies have found that the estimated models change over time, …

Heat load forecasts are crucial for energy operators in order to optimize the energy production
at district heating plants for the coming hours. Furthermore, forecasts of heat load are …

Regime shifts present a big challenge to traditional strategic asset allocation. This article
investigates whether regimebased asset allocation can effectively respond to changes in …