0:00  
Hello everybody and welcome to our video we are the routing triad and we will be presenting our project the runner trader. My name is Diego Leon, Alejandro Hernandez, Javier Isaiah. And then with without further ado, let's start the video.

0:18  
Hey, yo, talk to me. Hey man. So have you heard about this this hype about stocks lately, man, people getting rich without trading and stuff like that? Yeah, yeah, go keep hearing about that. Yeah. Yeah, man. So I've been looking into a man and that is really interesting. I've been I've been doing some research, man. But all these websites and applications are really confusing. There's a lot of lingo and words that I don't understand man. Like, look at this one here. What is all is this is really confusing, like, super confusing. I've been trying to understand it, it just it just difficult to me. And then look at this one. This one. This one's even worse, man. What, what does this mean? Why do I need all this information?

1:00  
You know, to to to trade. However, I haven't invested into it. And I've read online that I need all these monitors, man. And you know what? I think I'm almost there. I think if I use if I if I can add maybe two more? I'll be done with the setup. What do you think, man? I don't know. Um, I feel like given up to be honest. I think i think that i think there's a better way. There's a trading web app that I suggest you look into it's a it's a rowdy trader app retreated. Oh, man, that sounds really interesting. This is a simple use. Do you think I'd be able to get the hang of it? I think so.

1:41  
Can you see it? Can we there it is side trading way but designed to help inexperienced folks like like us, like you like myself.

1:50  
And the goal of this Runner Trader app is to make the stock market more information digestible for more people.

2:01  
It helps users find profitable stocks, stocks with value. And finally is able to try use an algorithmic trading and

2:12  
it's a

2:14  
it's just one example. You know, you might someone might say, Hey, I'm also on it's too expensive. Can I just buy like Sears stock, because, you know, it's so cheap. But you know, um, this app, it's based on a basis, some of the stock tickers based based on an analyst data

2:36  
are using a web API. And so it's looking for

2:42  
a stock stocks that are profitable and have value that have a potential to grow. Okay, next slide.

2:53  
Alright, so why we chose a trading platform. So if you look on the figure on the left hand side, you can see that most millennials these days are the ones using Robo traders. And that's no coincidence given with the growth of the market and the advent of technology. Stock data and information has grown as exponential exponentially. This mass amount of data has been intimidating for people discouraging folks are trying out training firsthand. Our target audience is people who desire simplicity and more streamlined data. And we are targeting baby boomers and millennials who want to understand it.

3:32  
We also chose this project because it's new and fun and challenging to us. And

3:39  
none of the three of us have dive deeply into this subject. He skipped. Next slide do I so here's a summary of how we kind of tackled what what we kind of did to tackle this project. We use Angular, single app user interface, which is a JavaScript package.

3:57  
This presents the user with a variety of strategies. And we use JavaScript packages such as node Express and MongoDB for the server side, and we use Python to handle the algorithmic trading on the server. So the RSI and other technical indicators go to skip the next slide.

4:15  
So here's our timeline. On the left hand side, you have the goal that we had in mind and on the right hand side you have the time taken to achieve

4:24  
so

4:26  
so the first goal that we had was to research and how to build a trading platform and educate ourselves in the market. So you follow the Udemy courses. We read certain textbooks, which is subject and we asked different Cal State Bakersfield professors how to tackle this and this was done in the first semester alone. The next goal we had in mind was using the beanstack to build our front end back end connection. This took about four weeks.

4:53  
And then next goal we had in mind was to implement a recommendation system and an algorithmic trader using Python. This took about three weeks to accomplish.

5:01  
And then the next.

5:04  
The next goal we had in mind was making the connection between the MEAN stack and Python so that we had a fully functioning website. And again, these are all high level tasks that we had in mind. But oh, and this one was to five weeks. And yeah, these are all high level tasks that we had in mind. So next slide.

5:23  
So this, what we have accomplished so far, so, so far, we've used a MEAN stack, and we're about to build a functioning trading platform. We've added a login page transactions page, we use server side strategy execution page,

5:41  
we were able to display historic stock data in the graph, and we use Python as a back end to calculate our different technical indicators.

5:50  
All right, next slide.

5:52  
Alright, so here's our demo app. For our demo, we're gonna create a brand new user, and we're gonna

5:59  
show some practice and data on this, let's see, runner, whatever password doesn't matter.

6:06  
We're gonna do a sign up,

6:13  
sign up, and then click login,

6:20  
which is application, there's transactions page with transaction summary. But we haven't initiated any trips with this brand new user. So cool. Well, we'll get into that.

6:31  
Let's look into a strategy now. So let's say I wanted to invest in

6:38  
for this one is to

6:42  
cosmetic clean, cyclical,

6:46  
will do.

6:48  
Still, Amazon

6:51  
going to strategy, we want to

6:54  
attempt to trade I'm just going to do

6:57  
still standard deviation, we're going to do back testing, we're going to give this bot 10,000 To start with, and then we're going to initiate the trade. This is gonna be us practicing. So the data will be

7:11  
instant, using historical data. So the results will be more quicker than if you had set it up as a life running. Because then it has to wait for the minute by minute data. So let's go on.

7:29  
Okay, who here saw transactions is the very last thing that he executed. But we can also look at the transaction page, or transaction transactions.

7:40  
This is all the transactions that are executed the buy and sell

7:46  
for that for the brand new user.

7:49  
I also want to show how

7:52  
one of the tests users that we had, we're gonna do a quick logout. And we're gonna try another 100. Yeah, look out. And then.

8:06  
So here's another user. And different information will be shown here.

8:13  
of some of the trades that this particular

8:16  
user traded, we can also check out the

8:24  
the whole history of transactions made by this particular bot for this particular user.

8:31  
And then I like to go back to

8:35  
the previous user.

8:45  
And you know how this just depending on whatever would use are

8:51  
tested there the data. So as you can see does user I finally started trading. So here's information from one of the transactions one of our bots trading. I also want to show this recommendations of stocks that we we scrap from the web, and then we'll display them so it could be the trade for one of these. For example, you wanted to do this one, you do help her and then let's do

9:24  
yes, back testing

9:28  
and trade trade

9:33  
to a lot of time for the backend to just go back

9:38  
to

9:40  
here

9:43  
and now we should have the formation from this other bot.

9:53  
We also have added a front end for Robin Hood in case

9:58  
a user wants to attempt this with Robin

10:00  
There's no point in trying this one since this one will be live and the markets closed. But

10:05  
this will be more like, just like data. But you can also do strategy and just choose not for the backtest. And that is our demo.

10:17  
Thank you, Alex for that demonstration. looking great. So now for what we learned. Throughout the process of creating this trading platform, we learned a lot. Like it was said before, everything was new to us, we use the MEAN stack

10:31  
to implement the trading platform. We all have learned. mangler Express no Mongo, we also have to dive deep dive into pandas and matplotlib. Live

10:46  
and REST API. So all that

10:50  
we have learned all that, basically, for from scratch. I know, some of the team members have already a little bit of experience, but not it wasn't deep.

10:59  
Also, we learned a lot of stock market lingo and how to understand the basics on market terms, which is really fundamental for for beginners. That would be using this platform so to know, we also learn how to understand the technical indicators and how to read Starcraft. And using all this, this information that we learn is how we we ended up being able to to create the final product which were presented to you today.

11:29  
For future clients for the project. As you all saw in the demo, we did create a Robinhood page

11:36  
for the robo trader. But since it does use live trading, we kept it out of the demo, because we don't want to show any

11:48  
private information for the user.

11:51  
Also, we want to give the ability to trade with other broker broker brokerage that allow it to be trading and at the cryptocurrency algorithmic trading to the platform as well

12:06  
for the conclusion, or our goal

12:10  
was just to make it easy for beginners to understand trading, and make it easy for them to be able to trade without getting overwhelmed with all the lingo and all the graphs and all stats. And to achieve this goal, we use mean

12:30  
combined with Python, to be able to transfer the data over to the user and for them to be able to see it.

12:37  
And we use the knowledge that we all gain from from point deep into this this application or to build a program which is a trading platform. And like I said before our goals for the project here after or to include live trading with many brokers and include a cryptocurrency.

13:02  
Thank you all for watching our video. We hope you enjoyed it. And this is it for us.

Transcribed by https://otter.ai