Is the empirical out-of-sample variance an informative risk measure for the high-dimensional portfolios?

The main contribution of this paper is the derivation of the asymptotic behavior of the out-of-sample variance, the out-of-sample relative loss, and of their empirical counterparts in the high-dimensional setting, i.e., when both ratios p/n and p/m tend to some positive constants as m→∞ and n→∞, where p is the portfolio dimension, while n and...

A sensitivity study on the natural frequency of high-rise structures in the Netherlands

As the world's population keeps increasing and the rate of urbanizations increases, The rate at which high-rise structures are being built is skyrocketing. In the Netherlands, this is no different. It is expected that the amount of high-rise structures taller than 70 meters will more than double in the coming 20 years. As these structures become...

A multiple spiking neural network architecture based on fuzzy intervals for anomaly detection: a case study of rail defects

In this paper, a fuzzy interval-based method is proposed for solving the problem of rail defect detection relying on an on-board measurement system and a multiple spiking neural network architecture. Instead of outputting binary values (defect or not defect), all data will belong to both classes with different spreads that are given by two fuzzy...

Parameter Uncertainty Analysis in Precise Pointing Control of Flexible Spacecraft

This article focuses on the validation of a classical PID controller scheme for flexible spacecraft with regards to the effect of parameter uncertainty on system stability and pointing precision. A high-fidelity simulation environment with external disturbances was built in Simulink using a control-oriented model of an Earth-observing...

Quantifying parameter uncertainty in predictions of coastal mega-nourishments: A case study on the Sand Engine at the Dutch coast

Continuous sea level rise and growing environmental awareness have led to increasing implementation of nature-based solutions to counter coastal erosion. An example in the Netherlands is the Sand Engine---a mega-scale sand nourishment designed to feed the Dutch coast over a period of 20 years. For such designs to work, a good understanding of...

Sampling distributions of optimal portfolio weights and characteristics in small and large dimensions

Optimal portfolio selection problems are determined by the (unknown) parameters of the data generating process. If an investor wants to realize the position suggested by the optimal portfolios, he/she needs to estimate the unknown parameters and to account for the parameter uncertainty in the decision process. Most often, the parameters of...

Trench Siltation near the ETM of a Well-mixed Estuary

To exploit its socio-economic functions, engineering measures are regularly applied in estuaries. Estuaries are, however, known to be very complex systems. Stemming from this complexity is the generation of a so-called estuarine turbidity maximum (ETM), which poses great siltation problems to the engineering measures. An engineering measure,...

Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty

The paper solves the problem of optimal portfolio choice when the parameters of the asset returns distribution, for example the mean vector and the covariance matrix, are unknown and have to be estimated by using historical data on asset returns. Our new approach employs the Bayesian posterior predictive distribution which is the distribution...

Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of models. One of multi modelling approaches called ...