The increasing share of intermittent renewable energy generation amplifies power price volatility, raising the need for storage technologies such as battery energy storage systems (BESS). However, limited transmission infrastructure, particularly constrained grid connections, poses a major...

Mitigating climate change will require integrating large amounts of highly intermittent renewable energy (RE) sources in future electricity markets. Considerable uncertainties exist about the cost and availability of future large-scale storage to alleviate the potential mismatch between demand...

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

We present a methodology based on Fourier series analysis to compute time series volatility when the data are observations of a semimartingale. The procedure is not based on the Wiener theorem for the quadratic variation, but on the computation of the Fourier coefficients of the process and...

We study the relationship between growth and variability in a DSGE model with nominal rigidities and growth driven by learning-by-doing. We show that this relationship may be positive or negative depending on the impulse source of fluctuations A key role is also played by the Frisch elasticity...

We study the relationship between growth and variability in a DSGE model with nominal rigidities and growth driven by learning-by-doing. We show that this relationship may be positive or negative depending on the impulse source of fluctuations A key role is also played by the Frisch elasticity...

We study the relationship between growth and variability in a DSGE model with nominal rigidities and growth driven by learning-by-doing. We show that this relationship may be positive or negative depending on the impulse source of fluctuations A key role is also played by the Frisch elasticity...

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...

The volatility in a CPG market is modeled using a bottom up simulation approach and validated against disaggregated supermarket transactions data. The simulation uses independent agents, each agent representing unique households in the data. A simple behavioral model incorporates household...

In this paper an in-depth analysis of the estimation of the realized volatility Wishart Autoregressive model is presented. We focus in particular on the estimation of the degrees of freedom. A new estimator is proposed. Monte Carlo simulations show that this novel estimator is more efficient...