ADV FML pg 44 name error

[cl7805]

This code is a snippet from Lopez De Prado Advances in Financial Machine Learning page 44

def getDailyVol(close,span0=100):
# daily vol reindexed to close

df0=close.index.searchsorted(close.index-pd.Timedelta(days=1))
df0=df0[df0>0]   
df0=(pd.Series(close.index[df0-1], 
               index=close.index[close.shape[0]-df0.shape[0]:]))   

try:
    df0=close.loc[df0.index]/close.loc[df0.values].values-1 # daily rets
except Exception as e:
    print(f'error: {e}\nplease confirm no duplicate indices')
df0=df0.ewm(span=span0).std().rename('dailyVol')
return df0

---

getDailyVol(close,100)

---

NameError Traceback (most recent call last)

in ()
1
----> 2 getDailyVol(close,100)

NameError: name 'close' is not defined

Thks

[ghgr]

You need to feed it a series of prices:

getDailyVol(df.price,100)

[cl7805]

getDailyVol(df0['Adj Close'],100)

UnboundLocalError Traceback (most recent call last)

in ()
1
----> 2 getDailyVol(df0['Adj Close'],100)

in getDailyVol(Close, span0)
1 def getDailyVol(Close,span0=100):
2 # daily vol reindexed to close
----> 3 df0=df0['Adj Close'].index.searchsorted(Close.index-pd.Timedelta(days=1))
4 df0=df0[df0>0]
5 df0=(pd.Series(df0['Adj Close'].index[df0-1],

UnboundLocalError: local variable 'df0' referenced before assignment

[ghgr]

The function was fine before, you just need to call it with a Series of prices.

[cl7805]

ser = pd.Series(df0['Adj Close'])
print(ser)

ValueError Traceback (most recent call last)

in ()
----> 1 ser = pd.Series(df0['Adj Close'])
2 print(ser)

2 frames

/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in nonzero(self)
1328 def nonzero(self):
1329 raise ValueError(
-> 1330 f"The truth value of a {type(self).name} is ambiguous. "
1331 "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
1332 )

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

[ghgr]

I just used the function you posted in the first post. I don't know where it comes from (in my copy of the book it's slightly different although functionally identical):

import numpy as np
import pandas as pd
import time

def getDailyVol(close,span0=100):
    # daily vol reindexed to close

    df0=close.index.searchsorted(close.index-pd.Timedelta(days=1))
    df0=df0[df0>0]
    df0=(pd.Series(close.index[df0-1],
                   index=close.index[close.shape[0]-df0.shape[0]:]))

    try:
        df0=close.loc[df0.index]/close.loc[df0.values].values-1 # daily rets
    except Exception as e:
        print(f'error: {e}\nplease confirm no duplicate indices')
    df0=df0.ewm(span=span0).std().rename('dailyVol')
    return df0

def get_prices():
    indices = np.arange(1622483891, 1625075912, 60)
    random_prices = 100*(np.exp(np.random.normal(0,0.005,len(indices)))).cumprod()
    prices = pd.Series(random_prices, indices)
    prices.index= pd.to_datetime(prices.index, unit='s')
    return prices


prices = get_prices()
res = getDailyVol(prices)

[PanPip]

@ghgr Thank you for helping to solve this issue!

@cl7805 is this now resolved?