# Tag Info

Suppose that you are riskless asset with return $r_{ft}$ and a risky asset with return $r_t$ and conditional volatility $\sigma_t(r_t) := \sqrt{V_t(r_t)}$. We build a portfolio using weights $(w_1, w_2) \in \mathbb{R}$, or as you wrote it $w_t := w_{1t}$, $w_{2t} := 1 - w_t$. This portfolio will have a time $t$ return of $r_{pt}$. Its volatility is given by $... 0 I have just found out what the code is. Note that theta and delta come from the copula selected for you through the BiCopSelect() command. theta <- selectedCopula$par delta <- selectedCopula$par2 gfBB1 <- gofCopula(BB1Copula(c(theta, delta)), as.matrix(mydata), N = 50) 1 Note that Boyle (1988) introduces$\lambda$because the CRR parameterisation$u=e^{\sigma\sqrt{h}}$yielded negative probabilities (and probabilities above one) for reasonable parameter values. Instead, he uses$u=e^{\lambda\sigma\sqrt{h}}$, where$\lambda>1$and$h=\frac{T}{n}$is the length of one time step. If you perform the limits,$p_u\to0$and$...