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Google Data Downloader

Ajeet Singh October 22, 2017
Sincere thanks to RMIKE for this wonderful utility





  1. This is a Python distributable utility to download 1 min historical data for NSE from Google finance. This is compiled to work on Microsoft Windows OS. Will not work for Mac and Linux OS.
  2. Important – Follow all instructions regarding package and file placement. Don’t modify the name of any file or folder!!!
  3. Download the zip package from the provided link, unzip the package to the root directory of your C: drive. This will place the ‘PyDownloader’ Folder in C: drive, like so “C:\PyDownloader”.
  4. Inside the PyDownloader Folder, you’ll find the following :-

    (a) ‘TickerList’ Text File – Enter Ticker symbols for which data is required. The sample Tickers viz. Nifty & BANKNIFTY are placed in the list as reference example. Input to list each desired Ticker in a separate line. The maximum limit of the TickerList is 100 Tickers
    (b) ‘Data’ Folder – The downloaded 1 min historical data by the utility will be written to this folder as a csv file for each individual Ticker in the TickerList. Historical 1 min IEOD can be downloaded for a maximum of 15 trading days.
    (c) ‘PyD.format’ File – If you wish to manually import the downloaded IEOD into Amibroker, place this file in the ‘Formats’ Folder of your Amibroker installation. You’ll also need to edit the ‘import.types’ file in the Formats folder by inserting the following instruction.PyDownloader (*.*)|*.*|PyD.format

    (d) ‘PyDn_v1.0_Lic’ – The License file for the utility.(e) ‘PyDn_v1.0 Help’ Pdf File – Help file.(f) ‘PyDownloader_nse_v1.0.exe’ – The executable distro package of the utility.
  5. After inputting desired Tickers in TickerList, double click on PyDownloader_nse_v1.0.exe. A console window will pop up. This window will remain inactive for some while (approx. 40 to 65 seconds, depending upon your rig’s CPU and RAM configuration) during which the Python virtual environment is loaded for the utility to function.
  6. After the virtual environment loading is complete, the console window becomes active. As the utility executes, it will ask the user to input the desired no. of days for which IEOD is required to be downloaded.
  7. Input the no. of days as a NUMBER. For e.g Three days = 3 and NOT 03 OR Three. And Fourteen days = 14 and NOT 014 OR Fourteen. After providing input, press Enter/ Return. The utility will then execute as per the user input for no. of days and no. of Tickers in TickerList. The image below illustrates the example of downloading IEOD for 1 day for NIFTY & BANKNIFTY.
  8. After the process is complete, the utility and the console window will auto exit. The IEOD can then be imported from the ‘Data’ Folder
  9. This utility is distributed ‘as is’ without any cost to user for providing retail traders with means to utilize publically available data from Google Finance for analytical purposes. No user is authorized to distribute this utility without credit to the copyright holder(s). No user is authorized to commercialize this utility in any form.





PairTrading Recommendations

Ajeet Singh October 17, 2017


Recommendations for Pair Trade:





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Fetching Intraday data from Google using Python

Ajeet Singh October 09, 2017
All credits to RMIKE

Here is an yet another interesting python tutorial to fetch intraday data using Google Finance API , store the data in csv format and also plot the intraday data as candlestick format. We are using plotly library for plotting candlestick charts and pandas to manage time-series data. Luckily found and interesting python code which fetches google intraday data and store in csv format. Done some little modification in the code (exchange added to the Google API) so that one can fetch data for any exchange.
In our example we try to retrieve the data (Date,Time,Symbol,Open,High,Low,Close,Volume data) for RCOM (Reliance Communication) and plot as candlesticks using plotly library. Download the sample RCOM CSV file fetched from Google Finance
Sample IPython Notebook using Plotly and pandas to plot Interactive Intraday Candlestick Charts using Google Finance API :
In [1]:
import requests.packages.urllib3
requests.packages.urllib3.disable_warnings()

In [2]:
import plotly
plotly.__version__
Out[2]:
'1.9.0'

Code to Fetch Google Intrday Data and Save in CSV Format
In [7]:

# Copyright (c) 2011, Mark Chenoweth
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted 
# provided that the following conditions are met:
#
# - Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
#
# - Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following 
#   disclaimer in the documentation and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, 
# INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS 
# OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, 
# STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF 
# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import urllib,time,datetime
import  pandas as pd


class Quote(object):
  
  DATE_FMT = '%Y-%m-%d'
  TIME_FMT = '%H:%M:%S'
  
  def __init__(self):
    self.symbol = ''
    self.date,self.time,self.open_,self.high,self.low,self.close,self.volume = ([] for _ in range(7))

  def append(self,dt,open_,high,low,close,volume):
    self.date.append(dt.date())
    self.time.append(dt.time())
    self.open_.append(float(open_))
    self.high.append(float(high))
    self.low.append(float(low))
    self.close.append(float(close))
    self.volume.append(int(volume))
      
  def to_csv(self):
    return ''.join(["{0},{1},{2},{3:.2f},{4:.2f},{5:.2f},{6:.2f},{7}\n".format(self.symbol,
              self.date[bar].strftime('%Y-%m-%d'),self.time[bar].strftime('%H:%M:%S'),
              self.open_[bar],self.high[bar],self.low[bar],self.close[bar],self.volume[bar]) 
              for bar in xrange(len(self.close))])
    
  def write_csv(self,filename):
    with open(filename,'w') as f:
      f.write(self.to_csv())
        
  def read_csv(self,filename):
    self.symbol = ''
    self.date,self.time,self.open_,self.high,self.low,self.close,self.volume = ([] for _ in range(7))
    for line in open(filename,'r'):
      symbol,ds,ts,open_,high,low,close,volume = line.rstrip().split(',')
      self.symbol = symbol
      dt = datetime.datetime.strptime(ds+' '+ts,self.DATE_FMT+' '+self.TIME_FMT)
      self.append(dt,open_,high,low,close,volume)
    return True

  def __repr__(self):
    return self.to_csv()

class GoogleIntradayQuote(Quote):
  ''' Intraday quotes from Google. Specify interval seconds and number of days '''
  def __init__(self,symbol,interval_seconds=300,num_days=5):
    super(GoogleIntradayQuote,self).__init__()
    self.symbol = symbol.upper()
    url_string = "http://www.google.com/finance/getprices?q={0}".format(self.symbol)
    url_string += "&x=NSE&i={0}&p={1}d&f=d,o,h,l,c,v".format(interval_seconds,num_days)
    csv = urllib.urlopen(url_string).readlines()
    for bar in xrange(7,len(csv)):
      if csv[bar].count(',')!=5: continue
      offset,close,high,low,open_,volume = csv[bar].split(',')
      if offset[0]=='a':
        day = float(offset[1:])
        offset = 0
      else:
        offset = float(offset)
      open_,high,low,close = [float(x) for x in [open_,high,low,close]]
      dt = datetime.datetime.fromtimestamp(day+(interval_seconds*offset))
      self.append(dt,open_,high,low,close,volume)
   
   
if __name__ == '__main__':
  q = GoogleIntradayQuote('RCOM',300,30)
  #print q                                           # print it out
  q.write_csv('c://data//rcom.csv')


Read the CSV file and Convert into Dataframe


In [4]:
dateparse = lambda x: pd.datetime.strptime(x, '%Y-%m-%d %H:%M:%S')  
df = pd.read_csv('c://data//rcom.csv',sep=',',header=None, parse_dates={'datetime': [1, 2]}, date_parser=dateparse)
df.columns = ['Datetime', 'Symbol','Open','High','Low','Close','Volume']
#df.index = df['Datetime']
#df.index.name = None
df.head(5)
Out[4]:

DatetimeSymbolOpenHighLowCloseVolume
02015-10-14 09:20:00RCOM77.8078.5077.6078.40552244
12015-10-14 09:25:00RCOM78.4079.0578.3078.85546950
22015-10-14 09:30:00RCOM78.7578.8578.2578.25223054
32015-10-14 09:35:00RCOM78.3078.5078.2578.35125523
42015-10-14 09:40:00RCOM78.4078.6578.3578.55105811

Plot the intrday data as charts using plotly

In [5]:
from datetime import date
import plotly.plotly as py
from plotly.tools import FigureFactory as FF
from datetime import datetime

In [9]:
fig = FF.create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index)
fig['layout'].update({
    'title': 'RCOM Intraday Charts',
    'yaxis': {'title': 'RCOM Stock'}})
py.iplot(fig, filename='finance/intraday-candlestick', validate=False)

The draw time for this plot will be slow for all clients.
Out[9]:

TD Sequential

Ajeet Singh October 07, 2017 ,

Tom Demark Sequential

Books which I have found and have read:
New Market Timing Techniques - Thomas R. Demark. Written by Tom Demark itself but it is difficult to read and understand. I have needed several months to understand the idea and to summarize the information bellow.... and than I found the following book:
DeMark INDICATORS - Jason Perl. A great book about Demark indicators easy to read and understand. The theory is presented in a way which is very easy to understand. I recommend you to read it. But Murphy's law I have found it one week later... when I already had the information which I have needed:)

The post is not intended to be a comprehensive guide how to trade using Tom Demark's technique there is books about that. In "DeMark INDICATORS by Jason Perl" for example you can find the info - when trading signal is appearing/entry level/stop level etc. and much more TD indicators and techniques.
The post is intended to be a quick reference so we do not need to look for the rules each time on Internet or in the books:) I will post my thoughts and some charts which will help you to understand how to apply Tom Demark's method in the practice. I am not a Pro but I hope that the post will be a good starting point for you to start using TD Sequential in real trading.

------------------------------------------------------------------------------------------------------------------------------------

TD Sequential indicator consist of two components. TD Setup is the first one and it is a prerequisite for the TD Countdown – the second component.

1.TD Setup
TD Setup compares the current close with the corresponding close four bars earlier. There must be nine consecutive closes higher/lower than the close four bars earlier.

TD Buy Setup - prerequisite is a bearish price flip, which indicates a switch from positive to negative momentum.
– After a bearish price flip, there must be nine consecutive closes, each one less than the corresponding close four bars earlier.
– Cancellation - If at any point a bar closes higher than the close four bars earlier the setup is canceled and we are waiting for another price flip
- Setup perfection – the low of bars 8 or 9 should be lower than the low of bar 6 and bar 7 (if not satisfied expect new low/retest of the low).

TD Sell Setup - prerequisite is a bullish price flip, which indicates a switch from negative to positive momentum.
– After a bullish price flip, there must be nine consecutive closes, each one higher than the corresponding close four bars earlier.
– Cancellation - If at any point a bar closes lower than the close four bars earlier the setup is canceled and we are waiting for another price flip
- Setup perfection – the high of bars 8 or 9 should be greater than the high of bar 6 and bar 7 (if not satisfied expect new high/retest of the high).
----------------------------------------------

2. TD Countdown - after a setup is finished the countdown can begin from bar 9 of the setup.
TD Countdown compares the current close with the low/high two bars earlier and you count 13 bars. Unlike the Setup, the Countdown doesn’t have to be a sequence of 13 consecutive price bars. If it is interrupted you just do not count the bars and when it resumes you continue counting further.

TD Buy Countdown starts after the finish of a buy setup. The close of bar 9 should be less than the low two bars earlier. If satisfied bar 9 of the setup becomes bar 1 of the countdown. If the condition is not met than bar 1 of the countdown is postponed until the conditions is satisfied and you continue to count until there are a total of thirteen closes, each one less than, or equal to, the low two bars earlier.
Countdown qualifier - The low of Countdown bar thirteen must be less than, or equal to, the close of Countdown bar eight.
Countdown cancellation:
- A sell Setup appears. The price has rallied in the opposite direction and the market dynamic has changed.
- close above the highest high for the current buy Setup (break of TDST for the current Setup)
- recycle occurs ( new Setup in the same direction and recycle activated )

TD Sell Countdown starts after the finish of a sell setup. The close of bar 9 should be greater than the high two bars earlier. If satisfied bar 9 of the setup becomes bar 1 of the countdown. If the condition is not met than bar 1 of the countdown is postponed until the conditions is satisfied and you continue to count until there are a total of thirteen closes, each one greater than, or equal to, the high two bars earlier.
Countdown qualifier - The high of Countdown bar thirteen must be greater than, or equal to, the close of Countdown bar eight.
Countdown cancellation:
- A buy Setup appears. The price has rallied in the opposite direction and the market dynamic has changed.
- close below the lowest low for the current sell Setup(break of TDST for the current Setup)
- recycle occurs (new Setup in the same direction and recycle activated)

Aggressive TD Sequential – the difference is the Countdown phase. You compare high/low (not the close ) with the high/low two price bars earlier.
Aggressive Sequential always produces buy and sell signals before Sequential does.
----------------------------------------------

3. TD Combo
TD Combo is better when you have sharp directional moves, because it requires only thirteen price bars from start to finish compared to TD Sequential which needs at least 22 bars. The criteria for a Setup within TD Combo are the same with those required for a Setup within TD Sequential. The difference is that the count starts at bar 1 of the setup and not from bar 9 and TD Combo requires four conditions to be satisfied simultaneously.

Requirements for a TD Combo Buy Countdown 
- close lower or equal than the low 2 trading days earlier.
- The low of a countdown day should be less than the previous "trading day‘s" low
- The close of a countdown day should be less than the previous "trading day‘s" close
- The close of a countdowns day should be less than the previous "countdowns day‘s" close
- bars 11,12,13 each one should just close successively lower and the other rules above are not applied

Requirements for a TD Combo Sell Countdown 
- close higher or equal than the high 2 trading days earlier.
- The high of a countdown day should be greater than the previous "trading day‘s" high
- The close of a countdown day should be greater than the previous "trading day‘s" close
- The close of a countdowns day should be greater than the previous "countdowns day‘s" close
- bars 11,12,13 each one should just close successively higher and the other rules above are not applied
----------------------------------------------

Bearish Price Flip - occurs when the market records a close greater than the close four bars earlier, immediately followed by a close less than the close four bars earlier.
Bullish Price Flip - occurs when the market records a close less than the close four bars before, immediately followed by a close greater than the close four bars earlier.

TDST level – this is the highest high(usually the high of bar 1) for a buy setup or the lowest low(usually the low of bar 1) for sell setup, also called true high/low for a Setup.
- If a move cannot close above or below the TDST level of the most recently completed Setup in the opposite direction that means the momentum is weak and this is just a corrective move.
- If a move closes above/below the TDST level of the most recently completed Setup in the opposite direction that means that the momentum is strong enough and the price should then continue in that direction , and with high probability a TD Countdown will be completed before a reversal occurs.

True low/True high – is the lowest and the highest point for a setup, BUT including gaps before bar 1 and the days after the 9-th bar, qualifying for a setup bar.

Sell zone/Buy zone after finished TD Sequential – find the bar which records the highest high/lowest low for the countdown, find the range of the bar plus gaps and project it from the high/low of the bar. After finished TD Sequential/Combo the price should make a top in this zone not later than 12 price bars after bar 13 for the countdown. If the market breaks this level the signal is negated and we are witnessing renewed strength.

Setup Recycle - A second setup appears in the same direction before/on/after a Countdown - that usually means strength. The question is recycle and start a new Countdown? (there must be a price flip to divide the two setups or the first just continuous)
Compare the size of the two setups. The size is the difference between the true high and true low of a setup.
- if the second setup is equal or greater than the previous one , but less than 1.618 times its size, then Setup recycle will occur – the trend re-energize itself. Whichever Setup has the larger true range will become the active Setup.
- ignore setup recycle if the new setup is smaller or 1.618 times and more, bigger than the previous one – most probably price exhaustion area.

TD Sequential Reinforcement - 9-13-9 sequence
After a Buy Countdown the market temporarily trades higher and produces a Price Flip and subsequently a TD Buy Setup appears, this is known as a TD Sequential 9-13-9 Buy Count.
Requirements for a valid Sequential 9-13-9 Buy Count:
- The Buy Setup must not begin before or on the same price bar as the completed Buy Countdown
- The second Buy Setup must be preceded by a bullish Price Flip
- There must be no completed Sell Setup prior to the appearance of the Buy Setup.

After a Sell Countdown the market temporarily trades lower and produces a Price Flip and subsequently a TD Sell Setup appears, this is known as a TD Sequential 9-13-9 Sell Count.
Requirements for a valid Sequential 9-13-9 Sell Count:
- The Sell Setup must not begin before or on the same price bar as the completed Sell Countdown
- The second Sell Setup must be preceded by a bearish Price Flip
- There must be no completed Buy Setup prior to the appearance of the Sell Setup. 

Excel File: Download
AFL Code: Copy from Here
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