Change the future

Collecting & Analyzing Financial Data

Alex Xu

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No matter what type of investor you are, short term swing trader or long term fundamentalist, we all agree that data is an important element to making a financial decision. This poster will outline the details of how one can use Python and Scipy to collect and analyze data in the arena of the stock market using real time data from various sources to help outline some key numbers to help investors.


The data comes from using ystockquote, an open source Python API, to connect to Yahoo Finance, which allows users to setup everything for no cost. By using the ystockquote setup, we can create files that select certain information such as looking at when a certain security has reached its highest and lowest price point. Addionally, we can create files that select certain information to setup some very interesting charts and graphs of different useful information by using Scipy, or extrapolate other data all of which allows key financial investment decision marking. Some features include looking at a technical perspective of volume and setting different time periods from a day to a month out. With the technical aspect, you can draw out different MA averages from 20 to even 100. From this and including fundamentals included, we can then accurately make a judgment and extrapolate this data to make a key financial investment decision. While the market changes so fast, these numbers & data will rapidly change alongside it, therefore it is not 100% accurate to receive the technical perspective for short side investors. One way to accommodate this is to take real time data put though different standards depending on the preference of the investor.