Using monthly data for Belgium, France, Germany, Italy and Spain for the period 2002-2019, we build a Hierarchical Euro Area Dynamic Nelson-Siegel model that allows for time varying exposures of national factors on the common components, and for stochastic volatility both at the regional and...

In this paper we combine a random effects model with different machine learning algorithms via an iterative process when predicting commercial real estate asset values. Using both random effects and machine learning allows us to combine the strengths of both approaches. The random effects will...

A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

A recent strand of the literature has proposed stochastic time-varying coefficient models for modelling structural change in the macroeconomy under both exogeneity and endogeneity. Subsequently, a new class of kernel based non-parametric estimators has been introduced for these models. These...

An (s, S) inventory system with service facilities has been investigated in this study. Demands arrive as a Poisson process with parameter λ (0) to an infinite capacity pool at any given time t. When the inventory is greater than the buffer size a customer will transfer to the buffer with rate...

We show how solutions to a large class of partial differential equations with nonlocal Riccati-type nonlinearities can be generated from the corresponding linearized equations, from arbitrary initial data. It is well known that evolutionary matrix Riccati equations can be generated by projecting...

In this paper we study an incomplete Brownian motion market and use filtration reduction to obtain a complete market, and hence a unique pricing measure. We then uplift the obtained measure to the original market and study valuation and hedging via the uplifted measure. We show how a general...

Uncertainty is becoming a constant throughout the global supply chain as reliability of suppliers and fluctuations in demand are increasingly prevalent worries for companies today. To account for this uncertainty, it is vital to implement mitigation strategies, such as purchasing and exercising...

In transportation systems with mobile and modular facilities, decisions related to facility location and facility capacity management during the planning horizon are critical; because the parameters effective in these decisions change over time, and it is necessary for the decision-maker to...

Easy to compute exact maximum likelihood estimators (MLEs) for parameters of a stochastic bivariate Itô Susceptible-Infected-Recovered (SIR) model and for parameters of an extension that treats undercounting are presented here