Zobrazeno 1 - 10
of 146
pro vyhledávání: '"Mattera, Raffaele"'
We introduce a dynamic spatiotemporal volatility model that extends traditional approaches by incorporating spatial, temporal, and spatiotemporal spillover effects, along with volatility-specific observed and latent factors. The model offers a more g
Externí odkaz:
http://arxiv.org/abs/2410.16526
In this paper, we present an extension of the spatially-clustered linear regression models, namely, the spatially-clustered spatial autoregression (SCSAR) model, to deal with spatial heterogeneity issues in clustering procedures. In particular, we ex
Externí odkaz:
http://arxiv.org/abs/2407.15874
Autor:
Mattera, Raffaele, Otto, Philipp
This paper presents a novel dynamic network autoregressive conditional heteroscedasticity (ARCH) model based on spatiotemporal ARCH models to forecast volatility in the US stock market. To improve the forecasting accuracy, the model integrates tempor
Externí odkaz:
http://arxiv.org/abs/2303.11064
Publikováno v:
In Energy Economics November 2024 139
Autor:
Mattera, Raffaele, Otto, Philipp
Publikováno v:
In International Journal of Forecasting October-December 2024 40(4):1539-1555
Publikováno v:
In Socio-Economic Planning Sciences October 2024 95
Publikováno v:
In Socio-Economic Planning Sciences October 2024 95
Publikováno v:
Electron J Appl Stat Anal 14 (2021) 230-253
Selecting an appropriate statistical model to forecast exchange rates is still today a relevant issue for policymakers and central bankers. The so-called Meese and Rogoff puzzle assesses that exchange rate fluctuations are unpredictable. In the liter
Externí odkaz:
http://arxiv.org/abs/2106.00283
Publikováno v:
International Journal of Approximate Reasoning (2021)
This paper develops a new time series clustering procedure allowing for heteroskedasticity, non-normality and model's non-linearity. At this aim, we follow a fuzzy approach. Specifically, considering a Dynamic Conditional Score (DCS) model, we propos
Externí odkaz:
http://arxiv.org/abs/2104.00271
Publikováno v:
In Journal of Environmental Management 14 February 2024 352