extr_mkt_events: Extreme market events dataset

In bayesRecon: Probabilistic Reconciliation via Conditioning

Extreme market events dataset

Description

Count time series of extreme market events in five economic sectors. The data refer to the trading days between 2004/12/31 and 2018/12/19 (3508 trading days in total).

Usage

extr_mkt_events

Format

A multivariate time series of class ts.

Details

The counts are computed by considering 29 companies included in the Euro Stoxx 50 index and observing if the value of the CDS spread on a given day exceeds the 90-th percentile of its distribution in the last trading year. The companies are divided in the following sectors: Financial (FIN), Information and Communication Technology (ICT), Manufacturing (MFG), Energy (ENG), and Trade (TRD).

There are 6 time series:

• 5 bottom time series, corresponding to the daily counts for each sector

• 1 upper time series, which is the sum of all the bottom (ALL)

Source

Zambon, L., Agosto, A., Giudici, P., Corani, G. (2024). Properties of the reconciled distributions for Gaussian and count forecasts. International Journal of Forecasting (in press). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.ijforecast.2023.12.004")}.

References

Zambon, L., Agosto, A., Giudici, P., Corani, G. (2024). Properties of the reconciled distributions for Gaussian and count forecasts. International Journal of Forecasting (in press). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.ijforecast.2023.12.004")}.

Agosto, A. (2022). Multivariate Score-Driven Models for Count Time Series to Assess Financial Contagion. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2139/ssrn.4119895")}

bayesRecon documentation built on Sept. 11, 2024, 9:08 p.m.