发布时间 : 星期六 文章【原创】R语言garch模型与 EWMA 模型案例 附代码数据更新完毕开始阅读
【原创】附代码数据
有问题到淘宝找“大数据部落”就可以了
R语言garch模型与 EWMA 模型案例
#读取package library(openxlsx) library(fGarch) library(qcc)
#读取数据
#预设参数
# specify arch(1) model T=1000
#process parameters
eta =as.numeric(data[10:nrow(data),2]) #eta = 0 is equivalent to Geometric Brownian Motion
mu =1#the mean of the process
#生成garch模型模拟参数
#GARCH volatility model
specs =garchSpec(model =list(omega =0.1, alpha =0.1, beta =0.8)) sigma =garchSim(spec = specs, n = T)
#输出参数
write.csv(sigma,\) P_0 =mu #starting price, known
【原创】附代码数据
有问题到淘宝找“大数据部落”就可以了
P =rep(P_0,T)
for(i in 2:T){
P[i] =P[i-1] +eta[i] *(mu -P[i-1]) +sigma[i] *P[i-1] }
write.csv(P,\)
#sigma参数 # ?计算 sigma^ 2 head(sigma^2)
## GMT
## garch ## 2015-01-17 0.09667231 ## 2015-01-18 0.14013957 ## 2015-01-19 0.05962823 ## 2015-01-20 2.70189640 ## 2015-01-21 0.36587459 ## 2015-01-22 0.62896480
【原创】附代码数据
有问题到淘宝找“大数据部落”就可以了
# ?计算EWMA variance
q <-ewma(sigma, lambda=0.2, nsigmas=3)
summary(q)
##
## Call:
## ewma(data = sigma, lambda = 0.2, nsigmas = 3) ##
## ewma chart for sigma ##
## Summary of group statistics:
## Min. 1st Qu. Median Mean 3rd Qu. Max. ## -2.985000 -0.619300 0.050490 0.009825 0.632700 2.948000 ##
## Group sample size: 1 ## Number of groups: 1000
## Center of group statistics: 0.009824546 ## Standard deviation: 0.9711321 ##
## Smoothing parameter: 0.2 ## Control limits:
## LCL UCL