Variance share of event learning

Fraction of total return variance over the tenor attributable to learning about the event: \((1 + \sigma^2 T / v)^{-1}\) with \(v = (\Delta\eta\, q(1-q))^2 A\).

Usage

ec_variance_share(sigma, deta, q, A, tenor)

Arguments

sigma

Numeric, annualized no-learning volatility (decimal, e.g. 0.19 for 19%).

deta

Numeric, the event exposure \(\Delta\eta = \eta_1 - \eta_2\).

q

Numeric vector of current event probabilities in \((0,1)\).

A

Numeric vector of event-clock time (non-negative).

tenor

Numeric, option tenor \(T - t\) in years.

Value

Numeric vector in \([0, 1]\).

Examples

# Brexit 2W: about 0.2%; US election 2W: about 1.1%
ec_variance_share(sigma = 0.10590, deta = -0.012, q = 0.195,
                  A = 0.166, tenor = 14 / 365)
#> [1] 0.001367446
ec_variance_share(sigma = 0.19326, deta = -0.099, q = 0.172,
                  A = 0.046, tenor = 14 / 365)
#> [1] 0.006342542