回撤

Financial Trading in Python

Chelsea Yang

Data Science Instructor

什麼是回撤？

回撤是資產或交易帳戶在特定期間從高點跌至低點的降幅。

回撤圖

最大回撤

$\text{Max Drawdown} = (V_p - V_l)/ V_l $

$V_p$：最大下跌前的高點值

$V_l$：創新高前的最低值

最大回撤範例

最大回撤

= （A 點值 − D 點值）/ A 點值 = (1700 - 800)/1700 = 53%

從回測統計取得回撤指標

resInfo = bt_result.stats

# Get the max drawdown
max_drawdown = resInfo.loc['max_drawdown']
print('Maximum drawdown: %.2f'% max_drawdown)

# Get the average drawdown
avg_drawdown = resInfo.loc['avg_drawdown']
print('Average drawdown: %.2f'% avg_drawdown)

# Get the average drawdown days
avg_drawdown_days = resInfo.loc['avg_drawdown_days']
print('Average drawdown days: %.0f'% avg_drawdown_days)

Maximum drawdown: -0.59
Average drawdown: -0.11
Average drawdown days: 22

Calmar 比率

CALMAR：California Managed Accounts Report（加州管理帳戶報告）

$ Calmar = CAGR / \text{Max Drawdown} $

Calmar 比率越高，代表策略在風險調整後的表現越好。
一般而言，Calmar 比率大於 3 被視為表現極佳。

手動計算 Calmar 比率

resInfo = bt_result.stats
# Get the CAGR
cagr = resInfo.loc['cagr']
# Get the max drawdown
max_drawdown = resInfo.loc['max_drawdown']


# Calculate Calmar ratio mannually
calmar_calc = cagr / max_drawdown * (-1)
print('Calmar Ratio calculated: %.2f'% calmar_calc)

Calmar Ratio calculated: 4.14

從回測統計取得 Calmar 比率

resInfo = bt_result.stats

# Get the Calmar ratio
calmar = resInfo.loc['calmar']
print('Calmar Ratio: %.2f'% calmar)

Calmar Ratio: 4.14

一起來練習吧！

Financial Trading in Python