写出下列时间序列问题的大致的R语言代码。现已知股票市场的3只股票的日简单收益率数据。使用GARCH模型得到这些股票的条件协方差矩阵。给定样本周期为2008年9月29日到2010年12月31日。对于样本周期，得到最小方差组合的权重和相应的波动率。并绘制权重和波动率曲线

以下是大致的R语言代码：

# 加载所需库
library(rugarch)
library(tseries)
library(zoo)

# 导入数据
data <- read.csv("stock_returns.csv")

# 将数据转换为时间序列对象
data_ts <- as.ts(data[, -1], start = c(2008, 9), frequency = 252)

# 计算简单收益率
returns <- diff(log(data_ts))

# 用GARCH模型拟合条件协方差矩阵
garch_spec <- ugarchspec(mean.model = list(armaOrder = c(0, 0)),
variance.model = list(garchOrder = c(1, 1), model = "sGARCH"),
distribution.model = "norm")
garch_fit <- ugarchfit(spec = garch_spec, data = returns)

# 得到最小方差组合的权重
weights <- solve(garch_fit@fit$vcov) %*% rep(1, ncol(returns))
weights <- weights / sum(weights)

# 得到最小方差组合的波动率
portfolio_volatility <- sqrt(t(weights) %*% garch_fit@fit$vcov %*% weights)

# 绘制权重和波动率曲线
dates <- as.Date(rownames(data_ts)[-1])
plot(dates, weights, type = "l", xlab = "Date", ylab = "Weights")
plot(dates, portfolio_volatility, type = "l", xlab = "Date", ylab = "Portfolio Volatility")