AI is changing the world in an entirely new way that people work throughout history. When we go through these major technological changes, a lot of people get left behind. You do not want to be the guy who never learned how to use a computer or go on the internet, and while

some of you are already living in fear about being replaced by AI, you have to view it as a tool. Learn it, take advantage of its capabilities, and use it to increase your own productivity. Now, some of you may have tried ChatGPT when it first launched a few years ago and

came to the conclusion that it was bad for complex and data-intensive tasks like stock analysis, and you were kind of right. I also thought that there were way too many hallucinations and just poor responses overall. Plus, I already had my preferred methods for stock analysis. However, the newer models are getting a

lot better, and these companies, whether it's OpenAI and Anthropic, xAI, Meta, they are investing billions and billions of dollars into training the next-generation models. And when you combine that with real-time verified financials and data visualizations, AI is starting to get very useful. So today I'm going to

share the four key use cases I have found to use AI for stock analysis. I will share the exact prompts with the example outputs and also mention the mistakes to avoid. But hey, why should you be listening to me? Well, I have an interesting combination of skill sets

here. First off, I'm a trained data scientist. I have a pretty technical background, as I was able to build this whole stock research platform myself. I've been studying stock analysis for over 5 years, and a lot of that has been learning from greats like Warren Buffett.

and Charlie Munger, so I would say that they have a very good understanding of all the team metrics you need to look at, whether that's for value investors, dividend investors, dividend growth investors, or growth investors. My tips today are really not for short-term

trading. I've grown my personal investment accounts to over $300,000, and I'm 25 years old, so that's not that bad, that's $148,000 of gains. And for years, I've been sharing my stock analysis videos here on YouTube where I break

down exactly how a company makes their money and give my updated thoughts and an estimated valuation. And I'm telling you, AI has started to get very useful in my research, but let's be real, this is still a rather novel technology, and you have to know what prompts to use. If you

enter a bad prompt, you're going to get a bad result. It can take a lot of trial and error, but eventually, you can shape the responses to get exactly what you're looking for, and the results are powerful. For example, today I'm going to share how

I use AI to summarize earnings calls and quarterly reports, learn exactly how and where a business makes their money, calculate the intrinsic value of a stock using financial models like discounted cash flow, and using to find stocks that fit specific financial metrics. And to do so, I will be using my newest tool which

just launched over on dividenddat.com. Think of this as ChatGPT but specifically trained for financial analysis and loaded with real-time financial data. If you want to try it out, now is the best time to sign up. We have our Black Friday sale where you can get

50% off membership for life. You are locking in that 50% discount. There's also a 30-day money-back guarantee, so no risk in trying it out. And you have to act fast. This offer will no longer be available after Cyber Monday, so if you

find this tool to be interesting and want to start learning how to use AI for stock analysis, then click the link in the description and pinned comment or enter the promo code Black Friday 2024 at checkout. Also, after signing up, you'll get sent this PDF, which is basically my

cheat sheet to help you use AI for stock analysis. And I will be making even more detailed versions of this to be sent out soon. So first, let's go over summarize. So in example prompt here, you would say something like, "Summarize the latest quarter and earnings call for NVIDIA",

ticker symbol, and then you can see that it reads from the real-time data and then it will start to formulate a response. And this basically lets you save an hour of listening to an earnings call and get the key details right away. Plus, this is all sourced directly from

the earnings transcript. So I don't know about you, but I like to actually closely follow most of my investments. Plus, I have a watch list of tons of other companies that I find interesting or follow because I want to learn more before investing in them. But realistically, I

can't listen to every earnings call. But because of this, I'm actually able to keep up with way more companies. And as I've been using this over the past month, this has become one of my power user features, especially during peak earning seasons when there's like five stocks a

day I want to look at plus you can view the company's Revenue by product segment so you know exactly how they're making their money and that's especially important with a stock like Nvidia where the entirety of their growth is their Data Center business by the way you will

not be getting charts like this in something like chat gbt all right the next major use case I have found is analyze and I like to view this as a launching pad to learn a lot about a business that may have taken hours to get from other sources so say you had a

company you didn't know a lot about and you wanted to figure out really how they make their money let's use Microsoft as an example I would write a prompt like write a research report on Microsoft stock ticker symbol msft it's very good to be specific and make sure you include

the name of the company and the ticker and then I add some more details for how I want the response to be framed so I said how do they make money what are the key business metrics and then I also wanted to know what some analyst price targets were so I said provide price

targets and here you can see that it's reading from the data and starts to write its response and here you can see it generated this whole Report with all the key financial metrics the latest data on their various business segments key insights and growth initiatives such as Microsoft's largest growth business

Microsoft Azure growing Revenue 33% year-over-year in the latest quarter you can see the latest analyst price targets with the average being $54.90 and the recommendation score with it being very bullish and then of course you get data visualizations breaking down their key metrics so you can see

how this can be pretty useful if you didn't know anything about a company to then in a few seconds be able to get a full picture look of exactly how they make money, where it comes from, etc. Plus, you can ask follow-up questions. For example, if I wanted to know about

Microsoft's dividend yield, it will respond with the yield and the latest dividend payments. Plus, you can view the daily yield that Microsoft stock traded at over the years. Some dividend investors really like this, as for some stocks, they like to optimize the entry point of yield. And you can even view the

total return, so including dividends reinvested. Microsoft has just been a crazy compounder. You can use AI to help calculate the intrinsic value, and this gets pretty interesting in how it can do multiple methods. So, one, you can do something like discounted cash flow for

Hershey stock, ticker symbol HSY, and it will use all the financial metrics for Hershey and it will do it for you. And according to the AI's default calculations, there's yourself to make the calculations accurate to what you think will happen.

And you can do your DCF based on a multiple of free cash flow or apply a terminal growth rate in perpetuity. For example, perpetuity is how they got to that 39% upside, but a break down discount cash flow almost needs an entire video itself. So, I'm going to

share another interesting valuation method that I just discovered doing my recent Alphabet stock review video. Given all the news about Google potentially being broken up, I thought it was a good idea to do a sum of the parts valuation. So, I asked, "Can you do a sum of the parts"

valuation for Alphabet, ticker symbol GOOGL. Assign a multiple based on annual revenue and profit to each segment and add them together. And I want to emphasize I didn't even know that the tool could do this. I was just messing around with prompting and I got it to be

able to do this for me. It definitely took some trial and error, but you can get it there. So here it shows each segment and then how it determines the different multiples and then the math of adding it all together. And it gives a sum of the

parts valuation of $2.9 billion. However, if you disagree with any of the multiples it chose, you can just do a follow-up prompt and ask it to keep refining this. This can be like a collaborative process. The final use case

I'm going to share is Discovery. And this is basically where you can get the AI to act like a stock screener, and you can use hundreds of possible different filters. So you could ask something like, "Find US stocks with a 5-year dividend growth rate of greater than 10% and a

current yield of at least 1%". And you can turn a natural language question into an output, and the data in the screen is updated daily. Plus, you can then go and change the options used, adding a lower and upper bound, hit regenerate, and you'll get a new list including a lower

yielding stock like Microsoft. And you can even add countless new filters. For example, let's say I wanted to put "Ford PE ratio", and I only wanted a Ford PE below 30. And boom, you see Ford P is now included and the list is different. Microsoft popped out of the list, and

This has endless possibilities. It's really whatever your mind can think of. AI is just a new tool. It's not always 100% accurate and you shouldn't look at it as the gospel, but it's getting a lot better and it's useful and we're still

in the first inning. This is only going to get better and better, so the best time to learn is now. And yes, I may be biased in that this is on my platform, but the entire purpose of everything I built on this platform is to make what I

want in a stock research tool. I built what I would find useful. So if you want to try it out, then sign up at dividenddat.com. It's much better than ChatGPT for stock analysis, plus you get all of my other stock analysis tools to help

you verify the information. The best time to join is now. We have our Black Friday sale which gets you 50% off for life. You got to sign up now cuz this is about to go away after Cyber Monday. There's a 30-day money back guarantee, so no risk

in trying it out. I would recommend the annual plan, that's our best deal. Just click the link in the description and pin comment to get right to this sale page, or create an account on the web app and enter the promo code Black Friday 2024 at checkout. If you enjoyed the

video, please leave a like, comment, and subscribe to the channel. I'll see you in the next one.

How To Use AI For Stock Analysis: A Complete Beginner’s Guide

Dividend Data

주식 분석을 위한 도구로서의 AI

AI는 사람들의 업무 방식을 혁신하고 있지만, 일부에서는 AI로 대체될 것을 우려하고 있습니다.

초기 AI 모델은 주식 분석과 같은 복잡한 작업에는 부적합했습니다.

기술 기업들의 막대한 투자로 최신 AI 모델이 개선되고 있습니다.

이 연사는 주식 분석에서 AI의 네 가지 주요 사용 사례를 공유합니다.

데이터 과학 및 주식 분석에 대한 연사의 자격이 제시됩니다.

주식 분석에서 AI의 네 가지 주요 사용 사례

AI를 사용하여 실적 발표 및 분기별 보고서를 요약합니다.

배당닷닷컴에 재무 분석을 위한 ChatGPT라는 새로운 도구가 도입되었습니다.

50% 평생 할인과 30일 환불 보장이 적용되는 블랙 프라이데이 세일이 발표되었습니다.

주식 분석에 AI를 사용하는 방법에 대한 PDF 치트 시트가 제공됩니다.

비즈니스를 분석하여 수익 창출 방식을 이해합니다.

할인된 현금 흐름과 같은 방법을 사용하여 내재적 주식 가치를 계산합니다.

사용자 지정 가능한 필터가 있는 스톡 스크리너로 AI를 사용합니다.

도구의 혜택과 블랙 프라이데이 세일에 대해 반복해서 설명합니다.

How To Use AI For Stock Analysis: A Complete Beginner’s Guide

How To Use AI For Stock Analysis: A Complete Beginner’s Guide

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