def test_get_quote_comma_name(self):
_yahoo_codes.update({'name': 'n'})
try:
df = web.get_quote_yahoo(['RGLD'])
except ConnectionError:
pytest.xfail(reason=XFAIL_REASON)
del _yahoo_codes['name']
assert df['name'][0] == 'Royal Gold, Inc.'
def test_get_quote_string(self):
_yahoo_codes.update({'MarketCap': 'j1'})
try:
df = web.get_quote_yahoo('GOOG')
except ConnectionError:
pytest.xfail(reason=XFAIL_REASON)
assert not pd.isnull(df['MarketCap'][0])
def import_stock_market_data():
import time
from datetime import datetime
import pandas_datareader.data as web
from pandas_datareader.yahoo.quotes import _yahoo_codes
_yahoo_codes.update({'MarketCap': 'j1'})
_yahoo_codes.update({'LastTradeDate': 'd1'})
stock_queryset = Stock.objects.filter(stock_code__endswith='.asx')
for stock in stock_queryset:
yahoo_code = stock.stock_code[0:3].upper() + '.AX'
stock_quote = web.get_quote_yahoo(yahoo_code)
if not stock_quote.empty:
try:
last_trade_date_str = stock_quote.loc[yahoo_code,
'LastTradeDate']
if last_trade_date_str != 'N/A':
stock.market_data_date = datetime.strptime(
last_trade_date_str, '%m/%d/%Y')
market_cap_str = stock_quote.loc[yahoo_code, 'MarketCap']
market_cap_unit = market_cap_str[-1:]
if market_cap_unit == 'M':
stock.market_value = float(market_cap_str[:-1]) * 1e6
elif market_cap_unit == 'B':
stock.market_value = float(market_cap_str[:-1]) * 1e9
else:
raise Exception(
'Unknown yahoo stock market value unit - {}'.format(
market_cap_str))
stock.save()
except Exception as exception:
print(exception)
continue
# Do not do too quickly, or the Yahoo finance may block us
time.sleep(0.01)
def test_get_quote_comma_name(self):
_yahoo_codes.update({'name': 'n'})
df = web.get_quote_yahoo(['RGLD'])
del _yahoo_codes['name']
assert df['name'][0] == 'Royal Gold, Inc.'
def test_get_quote_string(self):
_yahoo_codes.update({'MarketCap': 'j1'})
df = web.get_quote_yahoo('GOOG')
assert not pd.isnull(df['MarketCap'][0])
def test_get_quote_comma_name(self):
_yahoo_codes.update({'name': 'n'})
df = web.get_quote_yahoo(['RGLD'])
del _yahoo_codes['name']
self.assertEqual(df['name'][0], 'Royal Gold, Inc.')
def test_get_quote_string(self):
_yahoo_codes.update({'MarketCap': 'j1'})
df = web.get_quote_yahoo('GOOG')
self.assertFalse(pd.isnull(df['MarketCap'][0]))
- Figure out why posterior covariance is so small
"""
import cvxopt as opt
import datetime as dt
import numpy as np
import pandas as pd
import pandas_datareader.data as data
import re
import requests
from cvxopt import blas, solvers
from pandas_datareader.yahoo.quotes import _yahoo_codes
from bs4 import BeautifulSoup
# setup
_yahoo_codes.update({'Market Cap': 'j1'})
np.random.seed(123)
solvers.options['show_progress'] = False
# Various functions
def posterior_return_100_one_view(prior_returns, risk_multiplier, returns_cov,
view_link_vector, view):
"""
"""
factor1 = risk_multiplier * returns_cov @ view_link_vector
factor2 = np.linalg.inv(
view_link_vector.T @ (risk_multiplier * returns_cov)
@ view_link_vector)
factor3 = view - view_link_vector.T @ prior_returns
# -*- coding: utf-8 -*-
"""
Created on Fri May 12 23:54:33 2017
@author: Aniwat
"""
import csv
import pandas_datareader.data as data
from pandas_datareader.yahoo.quotes import _yahoo_codes
stocklist = ['advanc.bk']
#http://www.jarloo.com/yahoo_finance/
#https://greenido.wordpress.com/2009/12/22/yahoo-finance-hidden-api/
_yahoo_codes.update({'Market Cap': 'j1'})
_yahoo_codes.update({'Div Yield': 'y'})
_yahoo_codes.update({'Bid': 'b'})
_yahoo_codes.update({'Ask': 'a'})
_yahoo_codes.update({'Prev Close': 'p'})
_yahoo_codes.update({'Open': 'o'})
_yahoo_codes.update({'1 yr Target Price': 't8'})
_yahoo_codes.update({'Earnings/Share': 'e'})
_yahoo_codes.update({"Day’s Range": 'm'})
_yahoo_codes.update({'52-week Range': 'w'})
_yahoo_codes.update({'Volume': 'v'})
_yahoo_codes.update({'Avg Daily Volume': 'a2'})
_yahoo_codes.update({'EPS Est Current Year': 'e7'})
_yahoo_codes.update({'EPS Est Next Quarter': 'e9'})
data.get_quote_yahoo(stocklist).to_csv('test.csv',
