English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Although the scalar components methodology used to build VARMA models is rather difficult, the VAR models application being easier in practice, the forecasts based on the first models have a higher degree of accuracy. This statement is demonstrated for variables like the 3-month Treasury bill rate and the spread between the 10 year government bond yield, where the quarterly data are from the U.S. economy (horizon: first quarter of 2001 - second quarter of 2013). It was used a better measure of accuracy than those used in literature till now, the generalized forecast error of second moment, that was adapted to measure relative accuracy.

The Use of Varma Models in Forecasting Macroeconomic Indicators