| Library: | finance |
| See also: | stocksim stockestsim |
| Quantlet: | stockest | |
| Description: | estimates for a given dataset of a random process the parameters of the following two models: a Wiener Process (model 1) and a compounded Poisson Jump Process mixed with a Wiener Process (model 2) |
| Usage: | dat=stockest(data) | |
| Input: | ||
| data | n x 1 vector , data of a random process | |
| Output: | ||
| mue | scalar , mean rate of return in model 1 | |
| sigma | scalar , volatility of the returns in model 1 | |
| lambda | scalar , number of jumps in model 2 | |
| mue2 | scalar , mean rate of return in the diffusion part of model 2 | |
| sigma2 | scalar , volatility of the returns in the diffusion part of model 2 | |
| jump | scalar , volatility of the height of jumps in model 2 | |
library("finance")
data=read("motorola")
data=data[,2]
dat=stockest(data)
dat
Contents of dat.mue [1,] 7.0066 Contents of dat.sigma [1,] 44.191 Contents of dat.lambda [1,] 4 Contents of dat.mue2 [1,] 3.2302 Contents of dat.sigma2 [1,] 38.819 Contents of dat.jump [1,] 10.9