CODEWITHSUNDEEP
pythonfinancequandl
Peter Li
Peter Li

Reputation: 309

Regarding the Quandl module, how would you call any stock without having to know the stock exchange

The Quandl module makes it easy to call stock information if you know the specific label. For example, Apple would be something like GOOG/NASDAQ_APPL which means Quandl gets it from google finance, and apple is traded in NASDAQ. However, it gets annoying when I enter a bunch of stocks into the python call function and I don't know whether it is NYSE or NASDAQ. Is there a more general way to retrieve any arbitrary stock?

Upvotes: 1

Views: 1081

Answers (1)

Pawel
Pawel

Reputation: 41

If your universe of stock tickers is limited to a few major stock exchanges you can follow the description of fetching stock data via Python API in Quandl given here. Quandl provides .csv file of secwiki_tickers.csv with a collection of 3339 stocks for which you can grab e.g. close prices (code .4 below). The Python code for doing that may look as follows:

import numpy as np
import pandas as pd
import Quandl

df = pd.read_csv('secwiki_tickers.csv')

dp = pd.read_csv('portfolio.lst',names=['pTicker'])
pTickers = dp.pTicker.values  # converts into a list
tmpTickers = []

for i in range(len(pTickers)):
test=df[df.Ticker==pTickers[i]]
if not(test.empty):
    tmp=test.Price.values+'.4'  # of <type 'numpy.ndarray'>
    tmp2=tmp.tolist()
    tmpTickers.append(tmp2)

print(tmpTickers)
tmp = []

for i in range(len(tmpTickers)):
    tmp2 = str(tmpTickers[i]).strip('[]')
    print(tmp)
    tmp.append(str(tmp2).strip('\'\''))

QuandlTickers = tmp
print(QuandlTickers)

data = Quandl.get(QuandlTickers, authtoken='YourAuthToken', \
                 trim_start='2014-10-01', trim_end='2014-11-04', \
                 transformation='rdiff')

d=data.values.T # return-series (frequency: daily) based on close-prices
print(d)

where we use portfolio.lst as a plain text file storing a list of N desired stock tickers, e.g.:

AAPL
IBM
TXN

Eventually, a NumPy array with fetched daily return-series for a specified time interval is, e.g.:

[[-0.01558313  0.00725953 -0.0028028   0.         -0.00873319  0.02075949
   0.00218254 -0.00287072 -0.00913333 -0.01062018 -0.01225316 -0.01312282
   0.01464783  0.02139859  0.0271652   0.00507466  0.01786581  0.00372031
  -0.00104543  0.01550756  0.00562114 -0.00335383  0.00953449  0.01296296
  -0.00731261]
 [-0.01401254 -0.00138911  0.0094163   0.0019611  -0.01761532  0.0196543
  -0.01552598 -0.00262847 -0.01296187  0.00152572 -0.01115343 -0.01050894
   0.0122887  -0.0711343  -0.03471319 -0.00882191  0.00241053 -0.0006166
  -0.00129566  0.01068759 -0.00085575  0.00544476  0.00030423 -0.00024331
  -0.01040399]
 [-0.01698469         nan         nan -0.00416489 -0.01319035  0.020213
  -0.01959949 -0.07127336 -0.0189518   0.00906272  0.01063578  0.01941066
   0.00183528  0.01694527  0.05314118 -0.00320718  0.00815101  0.01212766
   0.00798823  0.01147028 -0.00350515 -0.01655287  0.0448138   0.00845751
   0.00638978]]

Be aware, as already mentioned in comments that you can fetch AAPL price-series skipping WIKI database of Quandl.

Upvotes: 1

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