I will explain the meaning and calculation method of Calmar Ratio.
Return from the start date to the current day of a certain issue [follows this definition](https://qiita.com/NT1123/items/096dc41c24751934747e#2-1-return%E3%81%AE%E5%AE%9A % E7% BE% A9).
It is an expression that evaluates the rate at which Return falls and bottoms out after the maximum of Return. </ b>
Specifically, let the maximum value of Return be $ R_ {max} ^ {(n)} $ in the period from the start date to n business days.
R_{max}^{(n)}=max\left\{R_{i} | 0<i≦n \right\}
Here, Maxdrowdown $ MDD_ {max} ^ {(n)} $ is defined by the following formula.
MDD_{max}^{(n)}=max\left\{\frac{R_{max}^{(n)}}{R_{i}} | 0<i≦n \right\}
Definition formula of Calmar Ratio
Calmar Ratio=\frac{CAGR(n)}{MDD_{max}^{(n)}}
The CAGR definition formula is listed here.
Supplement: Compared to Shapen Ratio, Calmar Ratio is an index that considers the worst rate of decline. </ b>
test.py
def CAGR(DF):
df = DF.copy()
df["daily_ret"] = DF["Close"].pct_change() #Calculate the rate of change from the day before the closing price of the stock price.
df["cum_return"] = (1 + df["daily_ret"]).cumprod() #cumprod(Returns the cumulative product of all elements in a scalar y.
n = len(df)/252 #The trading day for one year is set to 252 days.
print( "df[cum_return]" )
print( df["cum_return"] )
print( "df[cum_return][-1] ")
print( df["cum_return"][-1] )
CAGR = (df["cum_return"][-1])**(1/n) - 1
return CAGR
def max_dd(DF):
"function to calculate max drawdown"
df = DF.copy()
df["daily_ret"] = DF["Close"].pct_change()
df["cum_return"] = (1 + df["daily_ret"]).cumprod() #cumprod()Multiply all elements.
print(df["cum_return"])
#ax.legend() #Draw a legend
df["cum_roll_max"] = df["cum_return"].cummax()
df["drawdown"] = df["cum_roll_max"] - df["cum_return"]
df["drawdown_pct"] = df["drawdown"]/df["cum_roll_max"]
max_dd = df["drawdown_pct"].max()
ax=df["cum_return"].plot(marker="*",figsize=(10, 5))
ax=df["cum_roll_max"].plot(marker="*",figsize=(10, 5))
ax=df["drawdown"].plot(marker="*",figsize=(10, 5))
ax=df["drawdown_pct"].plot(marker="*",figsize=(10, 5))
ax.legend() #Draw a legend
return max_dd
def calmar(DF):
"function to calculate calmar ratio"
df = DF.copy()
clmr = CAGR(df)/max_dd(df)
return clmr
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