优化回测

R 中级投资组合分析

Ross Bennett

Instructor

优化回测：执行

# 运行带定期再平衡的优化
opt_base <- optimize.portfolio.rebalancing(R = returns,
                    optimize_method = "ROI",
                    portfolio = base_port_spec,
                    rebalance_on = "quarters",
                    training_period = 60,
                    rolling_window = 60)

# 计算组合收益
base_returns <- Return.portfolio(returns,    
                                   extractWeights(opt_base))
colnames(base_returns) <- "base"

优化回测：分析

# 绘制最优权重
chart.Weights(opt_base)

时间与投资组合权重的图

优化回测：分析

# 合并基准与组合收益
ret <- cbind(benchmark_returns, base_returns)

# 年化绩效
table.AnnualizedReturns(ret)

                          benchmark   base
Annualized Return            0.0775 0.0772
Annualized Std Dev           0.1032 0.0436
Annualized Sharpe (Rf=0%)    0.7509 1.7714

优化回测：细化约束

时间与投资组合权重的图

# 复制组合规范
box_port_spec <- base_port_spec

# 更新约束
box_port_spec <- add.constraint(portfolio = box_port_spec, 
                                type = "box",
                                min = 0.05, max = 0.4, 
                                indexnum = 2)

# 回测
opt_box <- optimize.portfolio.rebalancing(R = returns,
                                          optimize_method = "ROI",
                                          portfolio = box_port_spec,
                                          rebalance_on = "quarters",
                                          training_period = 60,
                                          rolling_window = 60)

# 计算组合收益
box_returns <- Return.portfolio(returns, extractWeights(opt_box))
colnames(box_returns) <- "box"

优化回测：分析精细化约束

# 绘制最优权重
chart.Weights(opt_box)

时间与投资组合权重的图

优化回测：分析精细化约束

# 合并盒约束组合的收益
ret <- cbind(ret, box_returns)

# 年化绩效
table.AnnualizedReturns(ret)

                          benchmark   base    box
Annualized Return            0.0775 0.0772 0.0760
Annualized Std Dev           0.1032 0.0436 0.0819
Annualized Sharpe (Rf=0%)    0.7509 1.7714 0.9282

Vamos praticar!

R 中级投资组合分析