![]() VAR(II): XB: 60% on XB / 40% on YB YB: 5% on XB / 95% on YB For forecast step 20, the FEVD returns the following values: Now we conduct forecast error variance decomposition on the two VAR-models. YB = daily time series of stock market volatility in country B XB = daily time series of trading volume on stock exchange in country B YA = daily time series of stock market volatility in country A XA = daily time series of trading volume on stock exchange in country A I have set up two bivariate VAR-models with lag length 1. Is someone familiar with vector autoregressive models (VAR-models) and forecast error variance decomposition (FEVD) and can help me with following issue?
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