var.vio: Violation Process

In yzhao7322/CurVol: Curve Data Volatility Analysis

Description

var.vio function returns a violation process for the intra-day VaR curves.

Usage

var.vio(yd, var_curve)

Arguments

yd	A (grid_point) x (number of observations) matrix drawn from N functional curves.
var_curve	A (grid_point) x (number of observations) matrix storing the forecasts of intra-day VaR curves.

Details

Given the intra-day return curves x_i(t), and the forecasts of intra-day VaR curves \widehat{VaR}_i^τ(t) obtained from var.forecast, the violation process Z_i^τ(t) can be defined as,
Z_i^τ(t)=I(x_i(t)<\widehat{VaR}_i^τ(t)), for 1≤q i ≤q N, t\in[0,1], and τ \in [0,1],
where I(\cdot) is an indicator function.

Value

A violation process of the intra-day return curves based on the forecasts of intra-day VaR curves.

References

Rice, G., Wirjanto, T., Zhao, Y. (2020). Forecasting Value at Risk via intra-day return curves. International Journal of Forecasting. <doi:10.1016/j.ijforecast.2019.10.006>.

See Also

var.forecast var.backtest

yzhao7322/CurVol documentation built on Sept. 5, 2021, 8:41 p.m.