A statistical model is autoregressive if it predicts future values based on past values (i.e., predicting future stock prices based on past performance).

This paper gives necessary and sufficient conditions for stationarity and existence of second moments in mixtures of linear vector autoregressive models with autoregressive conditional ...

The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...

The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...

This paper discusses a consistent bootstrap implementation of the likelihood ratio (LR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The ...

Abstract This paper employs a threshold vector autoregressive (TVAR) model to analyze a possible asymmetric behavior of exchange rate pass-through (ERPT) or pricing-to-market (PTM) in Japanese exports ...

Constructing a structural vector autoregressive model with the monetary policy rate, the pattern of monetary transmission to financial markets is examined over three distinct periods of regime changes ...

Using a Global Vector Autoregressive model with quarterly data from 1987 to 2022, we find that external factors such as the imported inflation from main trading partners, mainly driven by China, and ...

For more information on this research see: A Hybrid Model for Forecasting Realized Volatility Based on Heterogeneous Autoregressive Model and Support Vector Regression. Risks, 2024,12 (1).