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Portfolio Optimization (Stock Market)

Basically, we want to assign weight to history stock price, higher weight means good stock. So the question is: I need to maximize cost D, where we define as,

D = w' * std / sqrt (w' * Sigma * w)

where

• w is portfolio weight

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Hosting web on S3

Hosting web on Amazon S3

• http://docs.aws.amazon.com/AmazonS3/latest/dev/WebsiteHosting.html

Install LAMP stack on Ubuntu

• http://codesamplez.com/web-server/lamp-stack-on-ubuntu

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Link to Knowledge Lab

Github for Knowledge Lab

• Knowledge Lab Github

UniversalIngester User Guide

• http://www.knowledgelab.org/docs/UniversalIngester-UsersGuide-v1.1.pdf

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Email Fetching Stuff

Sending Email using Python

• See Stack overflow link here
• Python also has documentation here

Parsing Email using Python

• See how to parse email to python here

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SSN for J-1 student at Northwestern University

• Here is the link to International Office at Northwestern U

Complete the following application steps:

• Obtain a Job Offer Letter (see a sample below) from the NU office/department that will employ you.
• Using this Job Offer Letter, F-1 and J-1 students on-campus must request a Social Security Letter from the International Office.
• F-1 Student Social Security Letter Request form

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Can you test this?

def normalize(X):
    count = X.shape[1]
    for i in range(count):
        x = X[:,i]
        # There may be some nans, from missing values in data. 
        # A better strategy would be interpolate, but for now we just
 # use the mean.

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##Repository Related to parsing string

• https://github.com/datamade/parserator
• https://github.com/CeON
• Affiliation Parser
  • Github page for CERMINE
• NameParser

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So here we load useful library from python

import pandas as pd
import numpy as np
from datetime import datetime

You can use pd.read_csv to read csv file. They have function to read SQL table or excel too.

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Load all PDF from provided link

wget --content-disposition  -i urls.txt