A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.
A vector-autoregressive analysis of the effects COVID-19 had on the German stock market
Time Series Modeling in R: ARIMA & VAR Models
Python implementation of Gourieroux-Jasiak's (2025) mixed causal-noncausal VAR models. Features probabilistic forecasting, nonlinear innovation filtering, and state-dependent IRF analysis for financial time series with explosive dynamics. Enables robust risk assessment and structural analysis of speculative behavior.
Time series analysis of the APEC countries. Search for structural shifts in data. Checking for the ARCH effect. Building ARMA- and VAR-models. Forecasting GDP in several ways. / Анализ временных рядов стран АТЭС. Поиск структурных сдвигов в данных. Проверка наличия ARCH-эффекта. Построение ARMA- и VAR-моделей. Прогнозирование ВВП.
VARLMHET: Stata module to calculate heterokedasticity tests for VAR, VEC models
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