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Hey guys,

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it's Angela here and welcome to Day 36 of 100 Days of Code. Today

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we've got a fun project for you.

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We're going to be building a stock news monitoring project.

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So I don't know how many of you guys trade stocks out there,

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but I've recently started learning about it.

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And one of the pictures that always come to my mind when I think of people

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trading stocks is something like this,

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where if you will sit in front of a million screens,

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looking at all of the data and all of the news.

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Now I did a bit of research into this

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and it seems like a lot of the people who trade stocks professionally have

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access to what's that a Bloomberg terminal, which looks something like this.

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And it provides you with a number of things,

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the current stock prices of whichever companies you're looking at,

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and also the breaking news that's relevant to those companies. So 

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depending on whether if they had some good news

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say they earned a lot of money in the last quarter, or

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they built a really great product or they developed a new vaccine.

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Then obviously you can imagine the price of their company's stock go up or down

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depending on the type of news that comes out. And finally these platforms

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also give you the ability to alert you when relevant pieces of news happen that are

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related to stocks that you're following.

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So I found out for my friend that to subscribe to one of these Bloomberg

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terminals,

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it costs something like $24,000 a year.

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So that was the end of that research. Um,

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but I thought about it and I thought about the kind of things that would be

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really useful to somebody who trades stocks.

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And I thought about how we could turn this into a Python project.

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So here's what's going to happen.

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We're going to DIY our own a Bloomberg terminal or at least the parts of the

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functionality that are quite useful. First,

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let's take a look at what stock market data looks like. So here,

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I've got a website up called tradingview.com and I'm looking at the large cap

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companies.

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So these are well known companies that you've probably heard of like Apple or

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Microsoft or Amazon.

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And let's say that we had an interest in a particular stock.

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Let's say that we bought shares in Tesla,

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and we want to know how it's doing. Well,

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we could take a closer look at it and we could take a look at

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the full featured chart.

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And this shows us the price of the Tesla stock over the past few days.

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Now I'm going to change the time zone here to the actual time zone of the

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exchange. And if I change the view to one day view,

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then you can see the points at which the market is open and when it's closed.

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So these blue sections highlight when the market is closed.

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Currently it's the 22nd of July. So because this day's

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data is not yet complete, we're going to look at the previous day's data.

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So this is yesterday.

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And you can see that NASDAQ opens at 9:30 AM New York time

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and it closes down at 4:00 PM on the same day.

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And often when you're getting data on stocks,

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you can get the price of a particular stock at the point when the market opens

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and when the market closes. For example,

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we could compare the price of the Tesla stock at market close yesterday.

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So that was about $1,567 and at market close the previous day

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so that's four o'clock on the 20th of July,

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and that was at around $1,641.

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So there was a big difference between the end of the 20th of July and the end of

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the 21st of July. As a stock trader would be quite 

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interested in these big fluctuations because it might mean that we would want to

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buy more, or we might want to sell our stocks in Tesla.

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When you look at a lot of these services

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be it Bloomberg terminals or something much simpler like this,

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they often give you a whole bunch of other data as well.

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One of the most useful things is actually to look at the news that's related to

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the company that you're investigating. So for example,

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these are the current headlines for Tesla,

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and it comes from various news sources like Reuters or my Wall Street or

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Bloomberg. And it gives us some information to start analyzing.

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For example, well why was there this big drop, what's the reason,

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and there's various news sources that might tell us why. For example,

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maybe they're experiencing problems with servicing staff,

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or maybe as this news piece suggests, the stock is probably going to rise again.

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So these are really interesting things

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if we were to trade this particular stock.

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If we were to create a Python program that's going to help us trade stocks,

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then this is how it might work. First,

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we're going to pull in the stock prices of the stocks that we're interested in.

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So we would be using an API to get this data.

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And let's say that we were monitoring the Tesla stock cause we bought some

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shares and we want to know how it's doing. Well,

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it might pull in the data for the price of Tesla stock that was at market close.

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Let's say that today was March the 11th.

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So we're pulling in yesterday's closing price and let's just say, for example,

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it is $1,000.

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Now the next thing our program is going to do is it's going to pull in the

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closing price on the previous day.

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And we're going to compare these two values. So over the course of one day,

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what was the difference. And in this case,

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there's a difference of a hundred dollars and the direction is up.

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So it increased in value, right? Going from March 9th to March 10th.

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So that's good news for us if we bought in. Now,

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we can also calculate what is the percentage that this rise represents.

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So if we look at this difference of a hundred dollars and calculate it as a

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percentage of yesterday's closing price,

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then we can see that the price on March 9th was 10% lower than on March 10th.

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So let's say that in our Python program,

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we set the program to run and fetch us some news

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whenever we get a slightly extraordinary rise or an extraordinary fall.

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So you can define that as anything you want, but let's say it's 10%.

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If there was a difference of 10% or more between yesterday's closing price and

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the previous day, then we want to know about it.

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So we're going to get our API to fetch us some relevant news.

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That way we can figure out what is the reason for this rise or what is the

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reason for this fall.

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And it might just turn out well because Tesla launched a new product,

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or because they've acquired a new factory.

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Some sort of indicator that says, well,

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this company is going to do a lot better. Now,

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once the stock prices have triggered this alert and we fetched the news data,

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then we're going to send ourselves an SMS.

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So we're going to send ourselves a message telling us what was the big

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fluctuation that happened and what is the relevant news so that we can decide

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there and then whether if you want to sell our stock,

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or if we want to buy more.

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We're aiming for messages from Twilio that look a bit like this.

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That way

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when you wake up in the morning and you're wondering what's happening with my

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Tesla stock and it just so happens that over the last two days,

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it experienced huge fluctuations,

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then you would get sent the relevant pieces of news to help you decide and help

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you figure out what you should do with your trades. That's the goal.

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And the best part of this project is the fact that it's going to be mostly up to

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you as to how you create it

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In the course resources I've got links

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to starting projects with the comment and hints,

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and depending on which level of difficulty you want to choose, normal,

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hard or extra hard, you can pick the starting project that's right for you.

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Once you pick the starting project,

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then you are going to work through each of the comments

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and you're going to try and complete the functionality of this program.

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Now I want you to spend at least a half an hour to 45 minutes working on this

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project, just because it has quite a few APIs that you need to tap into.

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And most importantly,

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I want you to read through the API documentation yourself so that you can

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understand how to work with it and how to figure out things on your own.

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Because after all, there are millions of APIs out there

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and if you're going to need it for a special project of your own,

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you're going to need to go through this process that all developers go through

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which is digging through documentation and understanding how to work with an

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external piece of  software

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or code.

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That's the challenge I've set for you. Head over to the course resources now and

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get the starting code so that you can get started working on the project.

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Good luck.