[00:04] ourselves. Of course, trading requires research and technical analysis, which not everyone understands. I'm one of those people who tried trading and lost money because I didn't understand stock and cryptocurrency analysis.
[00:18] So, in today's project, we'll talk about how we can use artificial intelligence in the how we can use artificial intelligence in the technical analysis of stocks or currencies and let AI guide our buying and selling. I don't want to go into too
[00:33] much detail. Your brother, Abdul Hamid Shaheen, let's begin. [Music] Now, I opened the bot and asked it to analyze Amazon stock. I pressed Enter. If you notice, the bot started working and went to the toolkit chart
[00:50] to analyze the Amazon stock. Note that after the AI ​​retrieves the analysis from the chart, it saves after the AI ​​retrieves the analysis from the chart, it saves and stores this data in an airtable so that
[01:04] if we want to analyze it again in the future, it can provide it. Now, if I go back to Telegram, it should give me the result. If you notice, it gave me a chart, and this chart is an you notice, it gave me a chart, and this chart is an analysis of Amazon stock from stock exchange websites
[01:19] analysis of Amazon stock from stock exchange websites or analysis.  For stocks, it also gave me the technical analysis for Amazon stock, and this is its symbol, which is a ticker, using a candlestick pattern. It gives you the ticker, using a candlestick pattern. It gives you the complete analysis and can also give you a
[01:32] technical analysis so that if you want to buy or sell a stock today, let's now talk about the components of the project and what exactly we want and the goal of this project. Of course, the idea is that today I want to trade certain stocks, instead of me
[01:49] researching and searching myself, even if I don't have experience, I can let artificial intelligence do this process and perform the analysis. Of course, we will use some tools, and I will remind you of them in the project plan. Now, this is the plan for the analysis that we
[02:06] will do as follows: through Telegram or WhatsApp or another communication method, we will send an WhatsApp or another communication method, we will send an inquiry about the stock that we want to execute or analyze. We will send the inquiry, and through this tool that we built, it will contact a website
[02:21] called Chart.com. I will send the inquiry to this website, and it will retrieve the data for the stock that I want to analyze, and then give it to this tool. You give it to the
[02:33] AI ​​agent, and then the process of responding to the user or the user requesting the inquiry will take place. At the same time, the AI ​​agent will store the data in
[02:45] AirTable for future use in any analysis processes. If you notice now, I have an AirTable in which I put a trading sheet, and in this trading sheet I put the stocks or currencies
[02:57] that I want to analyze in the future. Let's move on now to the workflow, and I will explain to you exactly what things we did and the steps we will build now. The steps we will build are as follows: First, we need to create a Telegram or WhatsApp connection,
[03:14] which is the credentials. We need to create this connection. We need to create an account in Chart Age to extract the create an account in Chart Age to extract the IPK that we will use in the stock process. We will also have an account for the AirTable Sheet in which we will put and store the data of
[03:29] the stocks that need to be analyzed in the future.  The point of all this is that the AI ​​agent all this is that the AI ​​agent will always call this tool, ChartEgg, and send it data to get the chart result. This
[03:44] data to get the chart result. This creating an account on the ChartEgg website. Creating an account is very easy; all you have to do is sign in and register.
[03:56] Creating an account is very easy; all you have to do is sign in and register. Once you register, you'll be taken to the dashboard, which will automatically take you to the main screen. From there, you can access the IPK, generate a new key,
[04:12] IPK, generate a new key, and receive a key that allows you 50 queries per day. This is the free plan. If you're interested in more details, you can subscribe and upgrade to the plan. The goal here is to
[04:28] create the account and get the key you need to execute. If you need to work with it today, I'll show you
[04:42] Now, the next step I need to take is to build my Air Table Sheet so I can use it build my Air Table Sheet so I can use it in my workflow. We'll build the Air Table Sheet we need. After you register
[04:56] your account, all you have to do is create it. your account, all you have to do is create it. sheet, which I call the Trade Sheet. In this Trade Sheet, I put the field tickers
[05:12] and notes. You put the fields you need in it. I need tickers to store the information. After building this information, I go to the profile icon and then to Builder Up.
[05:33] token and give it the necessary permissions. When I build it, let's say I want to do an N8, I press the scope button and select the scopes.
[05:45] For me...  I select them all OK so that I don't have any restrictions in the permissions process. After that, I give it and tell it to add all resources and create the token. After that, I get a
[05:57] number. I take this number to build what is the connection or credentials with the Workflow. If I move to the Workflow directly, I go to the Airtable through the node, which is the
[06:10] Airtable, and I add the tool specific to the iAgent and I go and create credentials. To connect with whom? With my AirTable, I go to Create New Credits. All I need to do is enter
[06:22] Credits. All I need to do is enter the token I copied and save. The connection process is then established. After that, we specify the resource while creating it because we want to the resource while creating it because we want to save it in this sheet or AirTable. I want to save the
[06:35] currencies or stocks I'm searching for from the List Traden Sheet I searching for from the List Traden Sheet I created, and Table 1 Fallows, which is the ticker I obtained through the AI ​​agent. That's why you see it through the
[06:49] AI. I click on it, and it's selected directly. In this process, I've established the connection with the AirTable so that I can use it in the future. Now, let's move on to
[07:02] AN10 and look at the setup or settings we made in building this chart. Of course, the first step is to create a folder to save in our project so that I have an
[07:14] organized way to manage projects. Now, inside this folder, I have three charts: the main chart, which is the Traden Agent Main Workflow.  These are the main steps. Let's
[07:26] look at the main one and explain it today. If you notice, at the beginning of the message, I send a message through WhatsApp via the trigger, whatever method you want. But Telegram, since it's easy to use and everyone can use it
[07:42] use and everyone can use it in the application process, Telegram is the best way now. Today, when I send the message, I specify its type: is it a voice message or a text message? We talked in previous videos about how I deal with audio and how I deal with text.
[07:58] You can go back to the Telegram videos and see how I download. Now I'll explain it to you quickly. This is the first step in the sending process. The second step is the web home. What does that mean?  This means that I can send this workflow—which contains
[08:13] that I can send this workflow—which contains all the data stored in AirTable— when I send a message about a specific stock. This stock is stored in AirTable so that in stock is stored in AirTable so that in the future, if I want, this workflow can
[08:26] give me an analysis of the stocks every five minutes to know whether to buy or sell. So, the first step now is to talk about the private message in Telegram and the workflow. I just Telegram and the workflow. I just sent it a message through Telegram and wrote, "I want an
[08:40] sent it a message through Telegram and wrote, "I want an analysis of Apple stock." I pressed Enter. Now, the execution that happens is that it goes to the GetChart tool. We'll explain this goes to the GetChart tool. We'll explain this in detail now. How do I get the Apple stock so that the
[08:55] AI ​​agent can give me the analysis based on the image that was brought from the ChartEd website? Now I'm waiting for the message. Now, if you notice, it has given me a
[09:07] message containing the image of the analysis or the trading chart for Apple, and it also gave me the technical analysis based on this image. It gave me all the information that I can use to
[09:20] buy or sell this stock.  Now you'll notice the switch here is determining if it's a text message. So today I'm going to use this switch, which is what I use to determine
[09:33] if this message is text or voice. Of course, if it's text, you'll find that I have a text in the chat ID. I have something called "text," so I'm going to tell it something called "text," so I'm going to tell it if this text is present. What does "present" mean? It
[09:48] means this is a text message. Now, if this is the voice message, it means that instead of text, what I have is the file ID. Let me give you another example.
[10:00] I go to Telegram and record a voice message. I want an analysis of Apple's stock. The first step is to see how Telegram will take the voice ID. Now, if you notice, instead of
[10:14] bringing me the chat, it brought me the voice message. That's why, in this switch, in this process and in this note, I'm determining that I have the file ID present and I don't have the voice ID present.  What's showing this today? The chat here doesn't have a
[10:29] field text, so it's not present. What is present is the voice file ID. This switch is where I determine whether to where I determine whether to send a text message through this field text
[10:44] or through the file ID. If it's a voice message, I rename the output, naming this one "voice" and this one "text." The second step: if it's a text message, it will go to the field text and enter the AI ​​agent, which will perform the operation. If it's a voice message, it will be
[11:01] If it's a voice message, it will be converted to a download file, and we'll go to the transcript to translate it. It will perform the same process of fetching this data from the chart and start giving me the image and technical analysis. If I now go to
[11:17] the switch and execute the Execute Step, it should give me the tab or root for the voice message. give me the tab or root for the voice message. After it determines that this root is the voice message, we'll go to the download file and do the following.  Execute Step is used to download the audio file. The
[11:32] AI ​​agent needs to understand the message within the audio. So, the audio downloaded into 10 is then entered into into 10 is then entered into Transcribe. Transcribe converts the
[11:47] audio into text. If I perform Execute Step, it gives me the same text: I want an analysis of Apple. This text is what goes into the AI ​​agent, which uses the
[12:00] GetChart tool from AgeChart to retrieve the current stock image. The AI ​​agent then analyzes the stock and delivers the message. This is the first step,
[12:13] which is done through Telegram. Now, let's move to the next step. The AI ​​agent will analyze this text based on Apple's stock and the stock image it
[12:27] retrieved from AgeChart to deliver the message. Notice that the AI ​​agent is using the GetChart tool. Now, let's see
[12:39] GetChart tool. Now, let's see how we'll use GetChart today and how we'll send the message we want.  This is to get it to the workflow, which is specific to GetChart. If I access the AI ​​agent now, I'll see that today I have a Prompt.
[12:54] I'll give you this Prompt by copy and paste through the JESSEN file. I'll upload the project file to the blog; you can download and use it as is. This is the GetChart tool that I'm telling to pull all the data for
[13:09] GetChart using the API. We've always agreed that if I want to deal with the external environment because of A10, I have to use an API. The way to use the
[13:21] API is through HTTP requests. If we move now inside the Traden folder and If we move now inside the Traden folder and go to the GetChart, you'll notice the following, and it's very important that you understand today how I'm calling a workflow inside the main chart.
[13:38] Today I'm building this workflow, and I'm building it using a workflow input trigger. Today, what do I want to access in this workflow? I want to access the arrow, and I want to access the method.
[13:50] The presentation: If I go to the inbot here, today I'll use the ticker, which is the name of the sample, and the chart today I'll use the ticker, which is the name of the sample, and the chart style. There are different types of chart styles: bar, circle, pi, and many others. Okay, of course, trading experts are the ones who can
[14:05] help us with this. But this workflow—when I send it from the main chart, I tell it I want an analysis of Apple. I want to give it the shape of Apple's stock or its symbol, plus the style or presentation method
[14:19] we want. As soon as this inbot enters this workflow, we'll go to a node called Six Flow. I take this flow and put it in a field so that I can arrange my presentation. I put this ticker that I received and this chart style that I
[14:35] received and this chart style that I received from the nodes of the inbot trigger received from the nodes of the inbot trigger that came from my workflow. Now, when we call up Chart Edge, I'll put an HTTP request. We agreed that we can't
[14:48] We agreed that we can't use IBES except through HTTP requests, so this node now goes  I'll put the Method Post in it and take this URL. This is a constant from the Chartage website. I'll show you how in a bit. I send the header, the API key,
[15:05] through the same website. So, if I now go to the website, which is iChart, and go to the website, which is iChart, and go to the API key section, I'll take this API key and go back to iItem and paste this API key. Of course, here you have the NameType
[15:22] API key. Of course, here you have the NameType application, Jason. This is constant. Now, the document, I want the document to be application, Jason. This is constant. Now, the document, I want the document to be Jason. I send code in it. This code is constant. I specify the style that I entered on this workflow. Of course, these are
[15:37] constant values. Let me enlarge them. And you have the sample. This sample is what the AI ​​agent specified sample is what the AI ​​agent specified when I told it I wanted the Amazon stock, and it went and got the Amazon stock and put it in the ticker so I could send it to the Subworkflow. These are
[15:53] so I could send it to the Subworkflow. These are constant values ​​that you can explore through its documentation. But in short, today I have this URL. I send it through the API key so it can go and get me a  This moment is the stock
[16:09] that I requested, in addition to the style that I want to display. Of course, you can change this text. After that, we will do a download process for the chart. This is an HTTP request in which I put the URL that is coming from where?  The result of executing my private SAM query
[16:27] in the previous node's HCTP request is that this getchart retrieves the image URL from ChartEgg. It's then uploaded to ChartEgg. It's then uploaded to NE10 and fed into GPT Chat,
[16:42] NE10 and fed into GPT Chat, which analyzes the image. Since I performed the analysis today, the uploaded image needs further analysis. GPT Chat performs a complete image analysis, providing a technical analysis of the
[16:57] selected stock. It then sends the chart to Telegram or WorkFlows to send the image directly via the AI ​​agent.
[17:15] WorkFlows receives the information from the getchart, processes the analysis, and sends it to Telegram or the user who requested the execution. This completes the trading process via text
[17:31] trading process via text or voice message. Now, let's try a command we can give to Telegram.  I told him I wanted to analyze told him I wanted to analyze Apple stock and save it for future
[17:47] reference. The idea here is that when I give it the data and want to save it, it will store the when I give it the data and want to save it, it will store the stock in the airtable for future transactions. I press Enter in the same way. Now, if I execute the request, it will receive the information and
[18:01] Now, if I execute the request, it will receive the information and go to the chart. Notice that it saved the stock in the airtable. go to the chart. Notice that it saved the stock in the airtable. Additionally, the AI ​​agent is now waiting for information from the AI ​​agent in the sub-workflow
[18:14] AI ​​agent in the sub-workflow that we've linked to the GetChart to start the analysis and send the response to the user who requested the information. The AI ​​agent has now sent the data to Telegram. So, in the trading folder, I now have
[18:31] three charts: the main chart, the GetChart chart that interacts with the ChartImage website, and the third chart, the SCADWLD workflow, which runs every five minutes. It retrieves all the stocks from the airtable and sends them to the main chart
[18:48] to begin the analysis and then sends them to Telegram Node.  The way you want to extract the data, of course, is the goal of the video in which we learned today how we can use which we learned today how we can use artificial intelligence in trading operations. There are many
[19:03] examples and projects on this topic. We can also create an We can also create an AI agent that performs trading operations on our behalf AI agent that performs trading operations on our behalf through global platforms like TradeView and others.
[19:16] If you want to develop yourself and learn, don't forget to subscribe to the channel and activate learn, don't forget to subscribe to the channel and activate the bell so you receive all the updates.