Using large models and time series forecasting for market reaction analysis. [PDF]
He H, Li X.
europepmc +1 more source
A Type‐3 fuzzy ambiguity encoder converts rolling wind, price, reserve‐activation, and confidence features into central estimates and nested uncertainty bounds. These parameters are updated within a receding‐horizon MILP/MIQP that coordinates wind, battery, and supercapacitor capacity across day‐ahead and ancillary‐service markets.
Shurong Yan +5 more
wiley +1 more source
Dynamic forecasting and mechanisms of volatility synchronization in complex financial systems. [PDF]
Li JC, Guo J, Ma R, Zhong G.
europepmc +1 more source
Abstract Background The success of in vitro embryo production (IVEP) is influenced by donor mare and stallion. Objectives To determine whether donor mare and stallion influence the pregnancy rate after transfer of in vitro produced (IVP) blastocysts and to identify factors influencing the likelihood of obtaining one or more pregnancies from a single ...
M. Papas +11 more
wiley +1 more source
The quantile domain volatility shock transmission between carbon emission trading system and European emerging stock markets: Practical implications for portfolio optimization. [PDF]
Aljughaiman AA +3 more
europepmc +1 more source
A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting
ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
wiley +1 more source
Midterm Outcomes of Revision Total Hip Arthroplasty With Cementation of a Monoblock Dual-Mobility Bearing Cup in a Porous Revision Acetabular Shell. [PDF]
Antonioli SS +5 more
europepmc +1 more source
A Novel Text‐Based Framework for Forecasting Carbon Prices
ABSTRACT This study proposes a text‐based framework for predicting EU carbon prices. Using weekly data from 2020 to 2024, we construct a multivariate dataset combining financial indicators, commodity prices, Google Trends measures, and news‐based sentiment extracted using FinBERT.
Christian Oliver Ewald, Yaoyu Li
wiley +1 more source
Large language model-driven time-series forecasting of financial network indicators. [PDF]
Wang MH, Yeung Y.
europepmc +1 more source
Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan +3 more
wiley +1 more source

