Results 141 to 150 of about 29,634 (253)

A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting

open access: yesJournal of Forecasting, EarlyView.
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

Mathematical Methods in Economics (MME 2020) International Conference [PDF]

open access: yesStatistika: Statistics and Economy Journal, 2020
Petra Zýková, Josef Jablonský
doaj  

Hybrid Temporal Autoencoder and Similarity Matching for Low Aggregation Level Long Time Series Forecasting

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data sparsity undermine the ...
Hanbyeol Park   +5 more
wiley   +1 more source

International Conference Mathematical Methods in Economics (MME 2019) [PDF]

open access: yesStatistika: Statistics and Economy Journal, 2020
Petra Zýková, Josef Jablonský
doaj  

A Novel Text‐Based Framework for Forecasting Carbon Prices

open access: yesJournal of Forecasting, EarlyView.
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

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol. [PDF]

open access: yesBMJ Open
Tchouaket E   +10 more
europepmc   +1 more source

Forecasting Duration in High‐Frequency Financial Data Using a Self‐Exciting Flexible Residual Point Process

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents a method for forecasting limit order book durations using a self‐exciting flexible residual point process. High‐frequency events in modern exchanges exhibit heavy‐tailed interarrival times, posing a significant challenge for accurate prediction.
Kyungsub Lee
wiley   +1 more source

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