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Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering

Matteo Barigozzi · Luca Trapin首次提交 2025-02-06 · 修订 2026-01-07 · v3arXiv预印本

基于 EM 算法与卡尔曼滤波的大型近似动态矩阵因子模型估计AI 解读

This paper considers an approximate dynamic matrix factor model that accounts for the time series nature of the data by explicitly modelling the time evolution of the factors. We study estimation of the model parameters based on the Expectation Maximization (EM) algorithm, implemented jointly with the Kalman smoother which gives estimates of the factors. We establish the consistency of the estimated loadings and factor matrices as the sample size $T$ and the matrix…This paper considers an approximate dynamic matrix factor model that accounts for the time series nature of the data by explicitly modelling the time evolution of the factors. We study estimation of the model parameters based on the Expectation Maximization (EM) algorithm, implemented jointly with the Kalman smoother which gives estimates of the factors. We establish the consistency of the estimated loadings and factor matrices as the sample size $T$ and the matrix…

宏观 · 时间序列宏观 · 因子模型

关联记录被引 0 次 ↗OpenAlex · 核验 2026-09-30

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Measuring tail risk at high-frequency: An $L_1$ -regularized extreme value regression approach with unit-root predictorsMeasuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors

Julien Hambuckers · Li Sun · Luca Trapin首次提交 2023-01-03 · 修订 2023-01-03 · v1arXiv预印本

高频尾部风险测度：含单位根预测变量的 L1 正则化极值回归AI 解读

We study tail risk dynamics in high-frequency financial markets and their connection with trading activity and market uncertainty. We introduce a dynamic extreme value regression model accommodating both stationary and local unit-root predictors to appropriately capture the time-varying behaviour of the distribution of high-frequency extreme losses. To characterize trading activity and market uncertainty, we consider several volatility and liquidity predictors, and propose a…

金融 · 波动率单位根与协整正则化与变量选择

关联记录被引 1 次 ↗OpenAlex · 核验 2026-09-30

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Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering

Measuring tail risk at high-frequency: An L1L_1L1​-regularized extreme value regression approach with unit-root predictorsMeasuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors

Measuring tail risk at high-frequency: An $L_1$ -regularized extreme value regression approach with unit-root predictorsMeasuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors