neerav1985

library(plyr)
library(lubridate)
library(reshape)
library(zoo)
library(forecast)

#Input data
startdate <- mdy("01-01-2013")
enddate   <- mdy("04-13-2014")
freq      <- "d" #daily

neerav1985

>>>from numpy import * 
>>> # Define a matrix X that has 3 column vectors as the observations variables
>>> X = array([[1, 2, 3],   [2, 4, 5],   [1, 2, 5], [10,2,3], [25,23,1]])
>>> X
array([[ 1,  2,  3],
       [ 2,  4,  5],
       [ 1,  2,  5],
       [10,  2,  3],
       [25, 23,  1]])
>>> # Calculate covariance matrix

neerav1985

#
# $Id: bcp_out_all_tables.py 22322 2013-04-01 18:05:06Z neerav1985 $
#

import sys
import argparse
import textwrap
import workerpool
import commands 
import logging

neerav1985

 '''  
 Created on Oct 26, 2013  
   
 @author: pokerface  
   
 This code gets the spot price and options data from NSE India(www.nseindia.com) website  
   
 '''  
   
 import urllib2  

neerav1985

#install.packages(c("twitteR","ROAuth","tm","wordcloud","RXKCD"))

library(twitteR)
library(ROAuth)
library(plyr)
library(RXKCD)
library(tm)
library(wordcloud)
library(RColorBrewer)

neerav1985

from numpy import *
from scipy.stats import norm
from scipy.optimize import root, fsolve, newton
import logging
 
logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s', level=logging.DEBUG)
 
 
def BlackScholesCall(S, K, T, sigma, r = 0., q = 0.):
        #logging.debug("S=" + str(S) + ",K=" +  str(K) + ",T=" +  str(T) + ",sigma=" +  str(sigma) + ",r=" + str(r) + ",q=" +  str(q) )

neerav1985

import cx_Oracle
import logging

logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s', level=logging.DEBUG)


if __name__ == "__main__":

  conn = cx_Oracle.connect(user,password,server)
  cursor = conn.cursor()