A first-order binomial-mixed Poisson integer-valued autoregressive model with serially dependent innovations. [PDF]
J Appl Stat, 2023 Chen Z, Dassios A, Tzougas G.
europepmc +1 more source
Spatial Autoregressive Model untuk Pemodelan Angka Harapan Hidup (AHH) di Provinsi Jawa Timur
, 2018 Nova Ratih Intan, Edy Sulistiyawan
openalex +2 more sources
On the Estimation and Performance of One-dimensional Autoregressive Integrated Moving Average Bilinear Time Series Models [PDF]
, 2010 J. F. Ojo
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Deep Learning for Bond Yield Forecasting: The LSTM‐LagLasso
International Journal of Finance &Economics, EarlyView.ABSTRACT We present long short‐term memory (LSTM)‐LagLasso, a novel explainable deep learning approach applied to bond yield forecasting. Our method involves feature selection from a large universe of potential features and forecasts bond yields using dynamic LSTM networks.
Manuel Nunes +4 more
wiley +1 more source
A non-linear integer-valued autoregressive model with zero-inflated data series. [PDF]
J Appl StatPopović PM, Bakouch HS, Ristić MM.
europepmc +1 more source
Information Flows, Stock Market Volatility and the Systemic Risk in Global Finance
International Journal of Finance &Economics, EarlyView.ABSTRACT Information flows are a theoretical explanation for stock market volatility, but controversy remains regarding how to measure them. Based on cross‐sectional and temporal properties of information flows, we decompose total trading volume into four types: cross‐country shocks and country‐specific shocks due to arrivals of private information ...
Yen‐Hsiao Chen +3 more
wiley +1 more source
On the Bayesian generalized extreme value mixture autoregressive model with adjusted SNR in non-standard actuarial data. [PDF]
MethodsXLande CR, Iriawan N, Prastyo DD.
europepmc +1 more source
Enabling Autoregressive Models to Fill In Masked Tokens [PDF]
Daniel Israel +2 more
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Noncausal AR‐ARCH Model and Its Applications to Financial Time Series
International Journal of Finance &Economics, EarlyView.ABSTRACT We extend the noncausal autoregressive models by introducing noncausality into the variance component, allowing the volatility to depend on future prices as well. We refer to this model as the noncausal AR‐ARCH model, and it enables us to account for shocks arising from market agents who possess more information and engage in forward‐looking ...
Yaosong Zhan +3 more
wiley +1 more source
MARS: a motif-based autoregressive model for retrosynthesis prediction. [PDF]
BioinformaticsLiu J +6 more
europepmc +1 more source