How can I run my Maximum Drawdown Code without this ValueError Exception? - python-3.7

Question

Im trying to follow an exercise on calculating the maximum drawdown and maximum drawdown duration of a market market neutral vs a long-only trading strategy.
I followed the code to the T and has worked perfectly up until now, and I seem to be getting a ValueError Exception. What code do I need to change for my code to work?
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from MaxDD_Function import calculateMaxDD
# CALCUALTING MAXDD AND CREATING THE FUNCTION.
def calculateMaxDD(cumret):
highwatermark = np.zeros(cumret.shape)
drawdown = np.zeros(cumret.shape)
drawdownduration = np.zeros(cumret.shape)
for t in np.arange(1, cumret.shape[0]):
highwatermark[t] = (np.maximum(highwatermark[t -1]), cumret[t])
drawdown[t] = ((1+ cumret[t] )/(1 + highwatermark[t]) - 1)
if drawdown[t] == 0:
drawdownduration[t] == 0
else:
drawdownduration[t] = drawdownduration[t -1] + 1
maxDD, i = np.min(drawdown, np.argmin(drawdown)) # drawdown < 0 always
maxDDD = np.max(drawdownduration)
return (maxDD, maxDDD, i)
# First part of example. Read the csv data and calculate.
#The first dataframe/set for my strategy
df = pd.read_csv('IGE_daily.csv')
#print (df.head())
df.sort_values(by= 'Date', inplace = True)
dailyret = df.loc[:, 'Adj Close'].pct_change()
excessRet = ((dailyret - 0.04)/252)
sharpeRatio = ((np.sqrt(252)*np.mean(excessRet))/np.std(excessRet))
print (sharpeRatio)
#Second part of example
#This is the second dataframe/set for my strategy.
df2 = pd.read_csv('SPY.csv')
#The new data frame, with both datasets.
df = pd.merge (df, df2, on = 'Date', suffixes = ('_IGE', '_SPY'))
df['Date'] = pd.to_datetime(df['Date'])
df.set_index('Date', inplace = True)
df.sort_index(inplace = True)
dailyret = df [['Adj Close_IGE', 'Adj Close_SPY' ]].pct_change() # Daily
Returns
dailyret.rename(columns = {"Adj Close_IGE": "IGE", "Adj Close_SPY": "SPY"
}, inplace = True)
netRet = (dailyret['IGE'] - dailyret['SPY'])/2
sharpeRatio = np.sqrt(252) * np.mean(netRet)/np.std(netRet)
print (sharpeRatio)
cumret = np.cumprod(1 + netRet) - 1 #Cumalative return
#print (plt.plot(cumret))
#print (plt.show()) # Remember to always run plt.show to see the plot in
terminal.
maxDrawdown, maxDrawdownDuration, startDrawdownDay =
calculateMaxDD(cumret.values)
maxDrawdown = calculateMaxDD(cumret.values)
print (maxDrawdown)
Here are the results I got from my above mentioned code:
Ivies-MacBook-Pro:Quant_Trading Ivieidahosa$ python Ex3_4.py
-46.10531783058014
0.7743286831426566
Traceback (most recent call last):
File "Ex3_4.py", line 76, in <module>
maxDrawdown = calculateMaxDD(cumret.values)
File "Ex3_4.py", line 15, in calculateMaxDD
highwatermark[t] = (np.maximum(highwatermark[t -1]), cumret[t])
ValueError: invalid number of arguments
I expected the output on themaxDrawdown to be -0.09529268047208683,maxDrawdwnduration to be 497 andstartDrawdownday to be 1223.

Answer 1

Q: What code do I need to change for my code to work?
Your code uses a call to a numpy function having a defined a minimum-call-signature as: np.maximum( <array_like_A>, <array_like_B> )
This simply fails to meet the expected behaviour once only one of the expected pair of values was delivered in the reported line ( see the closing parenthesis ), or a scalar or any other, non-array-like type of object(s) were attempted to be delivered into the call-signature:
highwatermark[t] = ( np.maximum( highwatermark[t-1] ), cumret[t] )
where a tuple was attempted to get constructed on the right hand side of the value-assignment (well, actually an object-reference gets assigned in python, sure, but was trying to remain short here to tell that fast for an easy reading ), the first item of which was expected to get assigned to a returned value from a call to the above documented np.maximum(...) function. And Hic Sunt Leones ...
May like to start further bug-tracing with a cross-check-ing of the state of objects and the call-signature:
try:
for t in np.arange( 1, cumret.shape[0] ):
print( "The shape of <highwatermark[t-1]>-object was: ",
highwatermark[t-1].shape, " for t == ", t
)
except:
print( "The <highwatermark[t-1]>-object was not a numpy array",
" for t == ", t
)
finally:
print( np.maximum.__doc__ )