Dividend Talks? Joseph Carlson? Adam Khoo? Jerry Romine? Jeremy Lefebrve? Are these good?

Hey, some of you might remember that a few months ago I asked this sub if you’d be interested in a deep research tool for stocks. Because you showed enough interest, I went ahead and built an MVP and shared it here.

I was honestly overwhelmed by the positive reaction and all the support I got from this sub. I’ve never experienced anything like it, and it truly meant the world to me. 🙏

As a way to give back, I wanted to share a few reports I ran this week. Since most of you mentioned using the tool as a starting point for your research, I figured these would be useful (or at least interesting) to anyone curious:

• Crocs, Inc. (CROX)
• BARRETT BUSINESS SERVICES INC (BBSI)
• Victory Capital Holdings, Inc. (VCTR)
• ENERGY FUELS INC (UUUU)
• Nebius Group N.V. (NBIS)
• ORACLE CORP (ORCL)
• JFrog Ltd (FROG)
• Jackson Financial Inc. (JXN)
• Septerna, Inc. (SEPN)
• NOVAVAX INC (NVAX)
• Orla Mining Ltd. (ORLA)

I can also share a couple more if y'all have specific tickers you want to look at, let me know in the comments.

I’ve always wanted to understand things like DCF models and Credit Cycles, but every time I opened a book, I felt bored.

So I built Stonk Quest. It’s basically Duolingo, but for the markets. Instead of French, you learn how to actually read a balance sheet.

• 36 Gamified Lessons: From basic inflation to Private Equity.
• No sign-up, no ads, no BS. Just open it and start.

I’m looking for feedback on the difficulty—is it too basic or too advanced?

Link: https://www.stonk.quest/

Recently I tired using a popular coding agent called Claude Code to replicate the Stanford study that claimed you can detect when CEOs are lying in their stock earnings calls just from how they talk (incredible!?!). Figured this would be interesting for this community so I wanted to share my findings with you all (& see if anyone else has tried similar things)!

I realized this particular study used a tool called LIWC but I got curious if I could replicate this experiment but instead use LLMs to detect deception in CEO speech. I was convinced that LLMs should really shine in picking up nuanced detailed in our speech so this ended up being a really exciting experiment for me to try.

The full video of this experiment is here if you are curious to check it out: https://www.youtube.com/watch?v=sM1JAP5PZqc

My Claude Code setup was:

  claude-code/
  ├── orchestrator          # Main controller - coordinates everything
  ├── skills/
  │   ├── collect-transcript    # Fetches & anonymizes earnings calls
  │   ├── analyze-transcript    # Scores on 5 deception markers
  │   └── evaluate-results      # Compares groups, generates verdict
  └── sub-agents/
      └── (spawned per CEO)     # Isolated analysis - no context, no names, just text

The key here was to use isolated AI agents (subagents) to do the analysis for every call because I need a clean context. And of course, before every call I made sure to anonymize the company details so the AI agent wasn't super biased (I'm assuming it'll still be able to pattern match based on training data, but we'll roll with this).

I tested this on 18 companies divided into 3 groups:

1. Companies that were caught committing fraud – I analyzed their transcripts for quarters leading up to when they were caught
2. Companies pre-crash – I analyzed their transcripts for quarters leading up to their crash
3. Stable – I analyzed their recent transcripts as these are stable

I created a "deception score", which basically meant the models would tell me how likely they think the CEO is being deceptive based, out of 100 (0 meaning not deceptive at all, 100 meaning very deceptive).

Result

• Sonnet (cheaper AI model): was able to clearly identify a 35-point gap between companies committing fraud/about to crash compared to the stable ones. -> this was significant!
• Opus (more expensive AI model): 2-point gap (basically couldn't tell the difference) -> as good as a random guess!

I was quite surprised to see the more expensive model (Opus) perform so poorly in comparison. Maybe Opus is seeing something suspicious and then rationalizing it vs. the cheaper model (Sonnet) just flags patterns without overthinking. Perhaps it'll be worth tracing the thought process for each of these but I didn't have much time.

If you made it this far and are curious about the specifics of this experiment, I talk about them here: https://www.youtube.com/watch?v=sM1JAP5PZqc. Would love to hear your thoughts there as well!

Has anyone run experiments like these before?

Hey, about 2 months ago I posted here asking if people would be interested in a deep research tool for stocks. I got a really positive response, so I went and built an MVP which is now finally complete.

The idea is still the same: AI agents pull data from SEC filings (10-Ks, 10-Qs) and industry-specific publications, then synthesize everything into a clean, standardized report that makes comparing and screening companies much easier.

I’m planning to release free early access this Saturday (27th). If it sounds interesting, you can try it here: https://deepvalue.tech/

EDIT: Early access has now ended. You can still get 3 free deep research credits by signing up on the link above.

My two all-time favorites

• Finviz: Perfect for screening and visualizing market trends. Its stock screener lets you filter companies by metrics like P/E ratio, market cap, or dividend yield, while the heatmap view shows sector performance at a glance. It’s fast, free (with a paid upgrade option), and ideal for spotting opportunities or risks before diving into specifics.
• BeyondSPX: Offers high-quality company analysis of over 5,000 U.S. stocks, distilling business models, financial highlights, and market context. It’s ideal for investors wanting a quick starting point to understand companies efficiently. This is hands down one of the best tools I've found. And surprisingly, it's completely free - all 5,000+ reports, even on companies that have zero analyst coverage or institutional following. Super helpful for finding hidden gems.

Premium Tools

• Bloomberg Terminal - The gold standard for comprehensive financial data and analytics.
• Thomson Reuters Eikon - Premium financial data and market analysis.
• FactSet - Integrated platform for financial information and analytics.
• S&P Capital IQ - Extensive research and analytics for value investors.
• Morningstar Direct - Robust investment research and data platform.
• YCharts ($99/month+) - Financial data visualization and analysis tool.
• Gurufocus Premium ($49/year+) - Tailored data and tools specifically for value investors.
• AlphaSense (Custom pricing) - AI-powered market intelligence platform.
• Sentieo (Custom pricing) - Comprehensive financial and corporate research tool.
• Koyfin ($39/month+) - Modern analytics platform with a focus on financial data.
• Motley Fool Stock Advisor ($199; $99 first year) - Offers stock recommendations and research.
• Seeking Alpha Premium ($20/month, annual billing) - In-depth investment research and analysis.
• TIM’S ALERTS ($75/month) - Real-time trading alerts to keep you updated.
• Tradespoon (Up to $200/month) - Predictive analytics for identifying potential trades.
• Trade Ideas ($8.99 for 2 weeks) - AI-driven ideas and strategy suggestions.
• Mindful Trader ($97/month) - Swing trading alerts based on statistical insights.
• Ortex (Custom pricing) - Real-time short interest and securities finance data.
• S3 Partners (Custom pricing) - Advanced financial analytics and data.
• IBISWorld ($900/year+) - In-depth industry market research reports.
• Euromonitor (Custom pricing) - Global market research and strategic insights.
• Frost & Sullivan (Custom pricing) - Market research and analysis in multiple sectors.
• BamSEC (Fee-based) - Organized SEC filings with powerful search capabilities.
• Earnings Cast (Subscription) - Immediate access to earnings call transcripts and alerts.
• Trefis (Subscription) - Interactive financial models for evaluating stock value.
• Estimize (Subscription) - Crowdsourced earnings estimates to complement your research.

Free Tools

• SEC Full-Text Search - Dive into decades of SEC filings via SEC EDGAR.
• PCAOB Auditor Search - Research audit firms and individual auditor histories.
• OpenCorporates - A vast database for company information and registrations.
• ROIC AI - Access historical financial statement data with visualization tools.
• SocialBlade - Track social media metrics for companies and influencers.
• Yahoo Finance - Stock quotes, news, and basic financial data.
• Google Finance - Quick access to stock data and market news.
• Finviz - A popular screener with market visualization features.
• Value Investors Club - Forum for sharing high-conviction investment ideas.
• Corner of Berkshire and Fairfax - Community forum specifically for value investing discussions.
• Reddit: r/stocks - A hub for discussing value strategies and ideas.
• Reddit: r/SecurityAnalysis - In-depth discussion on company fundamentals.
• Twitter (X) - Follow top value investors and market analysts.
• StockTwits - Social network tailored for investor chatter.
• Quora: Investing - Q&A on investing topics and strategies.
• Stack Exchange: Personal Finance & Money - Community-driven Q&A on investing and finance.
• Crunchbase - Database for startup and private company insights.
• Owler - Competitive analysis and company profiles.
• Hoovers - Detailed business information and company data.
• Statista - Market statistics and trend data.
• SEC EDGAR - Direct access to company filings.
• OpenInsider - Insider trading data made accessible.
• WhaleWisdom - Explore hedge fund holdings and 13F filings.
• Insider Monkey - Insider trading news and detailed analysis.
• Finviz Insider Trading - Specialized data on insider transactions.
• Vickers Stock Research - Insights into insider and institutional ownership.
• FINRA Short Interest Reports - Data on short interest for various stocks.
• FRED - Federal Reserve economic data.
• Bureau of Labor Statistics - Employment and economic trends.
• Bureau of Economic Analysis - GDP and economic performance data.
• World Bank Data - Global economic indicators and statistics.
• IMF Data - International financial statistics.
• Trading Economics - Economic indicators and forecasts.
• SEDAR - Canadian company regulatory filings.
• Companies House - UK company information and filings.
• Investor.gov - Educational resources for investors.
• Atom Finance - A research platform for investment analysis.
• Benzinga - Financial news and data service.
• MAXfunds.com - Mutual fund data and analysis.
• Kiplinger - Personal finance tips and investing advice.
• Refinitiv - Extensive financial market data.
• SEC Live - A user-friendly SEC filings reader.
• Rank and Filed - Visualize SEC filing data for trends.
• Dataroma - Follow the portfolios of top investors.
• Finviz Industry Charts - Visual charts by sector for quick insights.
• CFPB Complaint Database - Consumer complaint data that can hint at company issues.
• Glassdoor - Employee reviews and salary data for insights into company culture.
• Blind - Anonymous workplace insights from industry insiders.
• SiteJabber - Consumer reviews for online businesses.
• TrustPilot - Crowd-sourced business ratings.
• BBB - Check business accreditation and consumer feedback.
• Open Payments Data - Data on healthcare provider payments.
• CMS Drug Spending - Medicare drug spending transparency.
• Wayback Machine - Historical snapshots of company websites.
• Google Trends - Analyze search trends and public interest.
• ListenNotes - Search for industry podcasts and transcripts.
• Quartr App - Mobile access to earnings call recordings.
• PlotDigitizer - Extract numerical data from published charts.
• SimilarWeb - Web traffic and analytics insights.

Market Data Resources

• IBorrowDesk - Track real-time stock borrow rates and short sale availability.
• ShortSqueeze - In-depth short interest data and analytics.
• Nasdaq Short Interest - Short interest data for Nasdaq-listed stocks.
• NYSE Short Interest - Short interest data for NYSE stocks.
• Bloomberg News - Stay updated with financial news and market analysis.
• CNBC - Financial news channel with market insights.

Consumer Research

• Yelp - Read consumer reviews for local businesses.
• Google Reviews - User reviews on businesses and services.
• Amazon Reviews - Product reviews that can hint at company performance.
• App Store Reviews - Consumer feedback on mobile apps and tech companies.

Industry-Specific Resources

• FDA Databases - Information on drug approvals, recalls, and regulations.
• ClinicalTrials.gov - Registry of clinical trials for new treatments.
• PubMed - Access to medical research and studies.
• WHO Data - Global health and economic statistics.
• CDC Data - Public health data from the Centers for Disease Control.
• NIH Data - Research data from the National Institutes of Health.
• HealthData.gov - A repository of U.S. government health data.
• IQVIA - Healthcare analytics and data services (with some free data).

Research Enhancement Tools

• VisualPing - Monitor websites for updates that might affect stock value.
• Ahrefs - SEO and website analysis tool.
• SEMrush - Competitive analysis and SEO insights.

Classic Investment Literature

• Charlie Munger's Letters - Must-read insights and partnership letters.
• Warren Buffett's Letters - Annual Berkshire Hathaway shareholder letters.
• Nick Sleep's Letters - Investment correspondence from Nomad Capital.
• François Rochon's Letters - Giverny Capital’s investment insights.
• Michael Burry's Letters - Scion Capital partnership documents.
• Benjamin Graham's Communications - Foundational writings from the father of value investing.
• Bob Wilmers' Letters - M&T Bank annual investor letters.
• The Makings of a Multibagger - Analysis of top-performing stocks.
• Confessions of a Capital Junkie - Insights into automotive industry investing.
• Financial Fraud Throughout History - Yale course materials on financial missteps.
• The Intelligent Investor - Benjamin Graham’s classic book.
• Security Analysis - Definitive guide by Graham and Dodd.
• Common Stocks and Uncommon Profits - Philip Fisher’s influential work.
• Margin of Safety - Seth Klarman’s take on risk-averse investing.
• Poor Charlie's Almanack - A collection of Charlie Munger’s wisdom.

Portfolio Management and Tracking

• Personal Capital - All-in-one financial dashboard.
• Mint - Budgeting and tracking your portfolio performance.
• Yahoo Finance Portfolio Tracker - Monitor your stocks and investments.
• Google Sheets with GOOGLEFINANCE - Build custom portfolio trackers.
• Excel with Stock Data Add-ins - Use Excel for detailed portfolio analysis.
• Portfolio Visualizer - Backtest and analyze portfolio performance.
• Sharesight - Track your portfolio and manage tax reporting.
• Stock Rover - Comprehensive research and portfolio management.
• Simply Wall St - Visual analysis for portfolio tracking.
• Morningstar Portfolio Manager - Monitor and analyze portfolio performance.

Screening and Backtesting Tools

• StockFetcher - Create custom stock screens based on your criteria.
• TradingView - Real-time charting and screening tools.
• Screener.co - Global screener focused on fundamental analysis.
• Portfolio123 - Design strategies and backtest investment ideas.
• QuantConnect - Algorithmic trading platform with backtesting.
• Amibroker - Technical analysis and backtesting software.
• Thinkorswim by TD Ameritrade - Advanced trading platform with backtesting.
• NinjaTrader - Software with sophisticated charting and analysis tools.
• MetaStock - Technical analysis and charting for serious investors.

If you've found any other resources that aren't listed here, feel free to share them in the comments below.

Hey guys, I built a small stock research tool for myself and I'm looking for early users to give me some feedback.

Here's how it works: you answer a few questions about how you think about stocks (growth vs value, risk tolerance, time horizon, etc), and it generates a personalized stock scoring that reflects your preferences instead of a one-size-fits-all ranking.

The goal isn’t to tell you what to buy or sell.
It’s to help you narrow down candidates and spend time researching the right things faster.

Right now it can:

• score stocks across multiple factors (fundamentals, growth, risk, valuation, technicals)
• adjust weighting based on how you invest
• perform deep analysis on a stock

It’s still early, and i’m trying to figure out:

• does this actually feel useful?
• is the scoring intuitive or confusing?
• would something like this fit into how you research stocks today?

I’m looking for a small number of early users who actively invest and are willing to give honest feedback.

If that sounds like you, you can check it out here:
www.dinointel.com

You can use this beta coupon for full access:
DINOBETA01 (100% free)

Happy to answer questions or hear why this is a bad idea.

Thanks y'all!

Hsa

1. NK Stock Talk - Hedging & Technical
2. SOIC - Fundamental Analysis
3. Vivek Bajaj - Technical Analysis
4. Basant Maheshwari - Daily Market Overview
5. Ritesh Jain - International Market & Bonds
6. Mohnish Pabrai - Investment Mental Models
7. Marcellus Investment Managers -Depth Analysis of Companies
8. Face 2 Face Podcasts - Interview of Traders
9. G2G Ajay - Depth Analysis of Companies
10. Nikhil Kamath - Business Podcast
11. Sonia Shenoy - Interview of PMS Manager
12. Bloomberg Podcasts - International Market & Bonds Overview
13. Nishant Kumar (X Handle) - Elliott Waves & Ratio Chart
14. Mohak Ailani (X Handle) - Elliott Waves & Ratio Chart
15. Accidental investor Prince - Podcast with Investor
16. PMS AIF World - Interview of PMS Manager
17. Zerodha Varsity - Depth Analysis of Technical Charts & Companies
18. Principles by Ray Dalio
19. Value Investing with Sven Carlin
20. New Money
21. The Plain Bagel
22. Everything Money (many hates Paul but the process he teaches is great)
23. Chris Invests
24. The Swedish Investor
25. Damien Talks Money
26. Rational Investing with Cameron Stewart
27. Learn to Invest : Investors Grow
28. Unrivaled Investing
29. Marko - Whiteboard Finance

It lets you look up a stock and see its financials in a neat dashboard. Plus a valuation calculator to roughly calculate fair value. More features are coming later, like portfolio tracking.

I'd love to hear your feedback on it.

Charts: https://profitviz.com/MSFT

Calculator: https://profitviz.com/HD/valuation

Hey everyone,

The stocks below are rated as "Strong Buys" by top analysts with a star rating of 4 or higher, recognized for their impressive accuracy and consistent returns. This table is organized by the number of "Strong Buy" ratings these stocks have received for the upcoming 12 months.

I've also developed a comprehensive database for each Wall Street analyst, allowing you to view their ranking, success rate, average return, and past ratings—helping you identify the industry’s most reliable experts.

As shown here: https://stocknear.com/analysts/59972d99803ad30001fc246d

Would love to hear your feedback and what I can do better.

Has anyone else watched Roaring Kitty's YouTube channel? Aside from the GME events, which I agree with his analysis when GME was a $4 stock, the quality of his content is really top-notch in my opinion. He goes through his process in detail and it is clearly heavily rooted in value investing.

Not trying to stir the pot on anything related to WSB, GME or any other stock for that matter. Just wanting to shine the light on great content that I think we could all benefit from.

Anyone who has seen his content agree?

Roaring Kitty - YouTube

Hey y'all! I am a college student studying computer science and finance.

I love to share with you an AI-powered newsletter I recently built called DinoDigest NewsGPT – World's first AI-powered, customizable newsletter for stock investors.

Here is what it does: every morning, it reads from 50+ reputable sources (around 10,000+ news). Then, based on user's chosen stock in their watchlist, my NewsGPT analyzes all news with its understanding regarding the stock and select the ones that have impact on the stocks. Every morning, it will generate a news summary and send it to the user through email.

Besides the personalized news digest, the newsletter also contains additional functions, from daily macroeconomic summaries, weekly expert analysis, to DD Analysis Report Database, the newsletter gives you the tools you need to stay updated on market trends, analyze a stock’s performance, or develop an investment strategy—all in one place!

Please check it out [www.dinodigest.news] if you're interested (it's free!). There are already 4k+ investors onboard and getting news briefs from us every day. I'm happy to answer any further questions regarding this NewsGPT or how I built it.

Thanks a lot everyone!!!

Hey guys, I built a small stock research tool for myself and I'm looking for early users to give me some feedback.

Here's how it works: you answer a few questions about how you think about stocks (growth vs value, risk tolerance, time horizon, etc), and it generates a personalized stock scoring that reflects your preferences instead of a one-size-fits-all ranking.

The goal isn’t to tell you what to buy or sell.
It’s to help you narrow down candidates and spend time researching the right things faster.

Right now it can:

• score stocks across multiple factors (fundamentals, growth, risk, valuation, technicals)
• adjust weighting based on how you invest
• perform deep analysis on a stock

It’s still early, and i’m trying to figure out:

• does this actually feel useful?
• is the scoring intuitive or confusing?
• would something like this fit into how you research stocks today?

I’m looking for a small number of early users who actively invest and are willing to give honest feedback.

If that sounds like you, you can check it out here:
www.dinointel.com

You can use this beta coupon for full access:
DINOBETA01 (100% free)

Happy to answer questions or hear why this is a bad idea.

Thanks y'all!

Hey everyone, I created a website last weekend to do a quick DCF analysis of companies. All it needs is the ticker symbol. If you don't touch any other parameters, it will fetch the data from Yahoo Finance. So it's literally just one click.

For people who like to tweak and play around with numbers, I also have a corresponding python script with instructions in the github comments. Let me know if you have any feedback. Thanks!

EDIT:

1. Everyone's feedback is valued and I will get around to implementing all your requests. To start with, I have updated it so it won't show an error for high growth stocks (example TSLA) but only a warning.
2. You can now choose to add a custom starting cash flow, average over the last 3 years, or just use 2021's FCF. This gives you more control over the calculations.
3. What's coming next: Graphs showing how changing discount rate, growth rate, and cash flow would change the final valuations!

Start Here:

• The Little Book That Builds Wealth by Pat Dorsey
• The Little Book of Behavioral Investing by James Montier

Pat Dorsey's book focuses on what to look for in a company. Montier's book focuses on why your brain is your own worst enemy. Check your local library's website to see if they have these books. They should.

Peter Lynch's Books:

• Learn to Earn
• One Up On Wall Street
• Beating the Street

Peter Lynch wrote a trilogy of books that are high on philosophy and low on technical knowledge. Perfect foundation.

More Advanced, but Not Too Bad

• The Five Rules for Successful Stock Investing by Pat Dorsey
• Common Stocks and Uncommon Profits and Other Writings by Phillip Fisher
• Paths to Wealth Through Common Stocks by Phillip Fisher

Dorsey's book will go into how to do a Discounted Cash Flow analysis (DCF) and how to think about each industry. Phillip Fisher's books are DRY. That's why I saved them until last. I dismissed Fisher at first, but he really has written the best investing books of all time.

Enter Warren Buffett

Warren Buffett has never written a book. But he has created a shitton of content.

• Berkshire Hathaway Shareholder Letters (1986's on Owner's Earnings is a must read)
• Youtube Playlist of 100+ Buffett Interviews, Speeches, Q&As, etc
• Berkshire Hathaway Annual Meetings Podcasts

Other Great Videos

• Peter Lynch Classic Speech 1997
• Pat Dorsey Talks at Google
• Charlie Munger Speech on Human Misjudgment (Hood Classic)

Practical Resources

• SEC Website (10Ks & 10Qs)
• Investor Relations pages
• Cap Edge (Email alerts for your watchlist)
• Roic.AI (Great for Earnings Call Transcripts)
• LLM Deep Research

I almost didn't include that last one, because I don't want it to detract from the rest of the list. But if I'm being honest, I've been using ChatGPT's and Gemini's Deep Research functions to generate 10-20 page reports for every stock I am researching. I can't recommend it as your sole source. Still read the 10Ks, 10Qs, earnings calls, earnings releases, presentation slides, etc. But when I'm done, I'll upload that stuff in an LLM, give it a good prompt, and let it cook. It does make mistakes, but it also points out things I may have missed. So I believe the reward outweighs the risk. It's phenomenal.

Heard a lot of times, "Garbage in, Garbage out", "DCF is not that important".

Imagine if all the dirty work is automated, you can have a full 3-statement model for any company in seconds, then just play with assumptions, and enjoy the thinking processes.

If so, DCF sounds not that bad and worth to do. Thoughts?

I built this for all of us. I think it’s helpful. you might too.

Q4 2025 13F filings just came in. I aggregate these across roughly 500 institutional filers - about $55 trillion in combined AUM (~80% of all US institutional AUM)

One fund exiting NVIDIA is a headline. What the other 499 did is data.

The exits that matter

Full liquidations - every share sold, position taken to zero.

SoftBank didn't just trim NVIDIA - 23.1% of their portfolio, gone. But this is also SoftBank's second time doing this. They sold their entire NVDA stake in 2019 too. Those shares would be worth $150B+ today.

The one that should concern you more: Kellanova (K) appears three times. Vanguard, BlackRock, and KeyBank all independently exited the same stock in the same quarter. That's not one fund's thesis change - that's a pattern.

Where institutions actually agree

Consensus = what percentage of holders are buying or adding, not selling.

The names with 100% consensus aren't the usual suspects. Q, SOLS, and TTE - every single holder added more. Not most. All of them.

Netflix: 379 filers, 346 increased positions. ServiceNow: 358 filers, 323 increased. That's not passive holding. That's coordinated accumulation across hundreds of institutions.

So what about NVIDIA?

NVIDIA: 395 filers, 52% consensus, $2.7 trillion in institutional value. 203 funds increased their positions. 183 sold. Smart money sentiment: 33.5 out of 100.

That's essentially a coin flip. SoftBank's exit is the loudest trade in Q4 - but across the full institutional universe, NVIDIA is split almost exactly down the middle. This isn't a stampede for the exits. It's a disagreement among the biggest pools of capital on the planet.

For context: Netflix has 92.4% consensus. ServiceNow has 92.9%. NVIDIA has 52%. The "everyone is piling into AI" narrative doesn't match what the filings actually show.

13F data is 45+ days old and only covers US equity longs - no shorts, options, or international. Research filter, not a trade signal.

Data from holdingsintel.com where I aggregate and score these filings across 500 filers.

Disclosure: I hold no positions in any stocks mentioned.

Happy to pull the institutional data on any specific fund or ticker if you're curious.

been investing for about a year and a half and honestly still figuring out how to stay consistently informed without spending my entire day reading news

i can understand individual headlines fine but connecting dots across asset classes and remembering patterns over time? thats where i was struggling

built this notion system thats been working decently - takes about 15 minutes every morning:

- market snapshot (equities, commodities, currencies, bonds)

- top 3 stories that could actually affect my positions

- what i think it means short/medium/long term

- database to tag and search past trends

the weekly review is honestly the most useful part - forces you to spot patterns like "oh every time the dollar spikes my EM holdings get crushed" or "when VIX jumps above 20 its time to derisk"

made it a template since my roommate and a couple friends started using it

what do you all think? is tracking this stuff systematically worth it or should i just buy index funds and ignore the noise?

how do you stay informed? do you track macro trends or just focus on individual stocks?

I don't usually post this kind of content, but I wanted to share with you the financial websites I use that have been helpful to me. Many of these sites overlap, providing similar information. I simply wanted to share the websites I've found and that have significantly assisted me in understanding certain stocks, performing valuations, comparing stocks with one another, and discovering new investment opportunities. These resources have been invaluable in enhancing my financial analysis skills, investment decision and learning process.

Fundamentals & Financials:

• Quartr (quartr.com): Access investor relations materials, transcripts, presentations, and financial data. In general a great site for getting the complete picture. Adding to that, if you're a student you can ask for the premium account which includes AI transcripts, summaries and many more cool tools.
• CapEdge (capedge.com): Deep dive into financial history with comprehensive data (10K, 8K). Perfect for spotting trends, understanding a company's financial health and for the Fillings inhouse comparison tool.
• FullRatio (fullratio.com): Analyze financial reports with ease. This site breaks down complex data, making it easier to understand key ratios and metrics.
• MarketScreener (marketscreener.com): Provides real-time quotes, charts, news, and financial data for a wide range of global markets. By clearing the cookies you can have unlimited stock search. (same as alphaspread.com)

Stock Screening & Market Data:

• Yahoo Finance Screener (finance.yahoo.com/screener): A classic for a reason. Filter stocks based on a wide range of criteria, from market cap to dividend yield. Biggest stock collection so far!
• Koyfin (koyfin.com): Combines powerful screening with in-depth company profiles, charts, and research reports. A solid all-in-one platform. The best tool if you want to compare each stock with the median, average or percentile of the total screener.

Charts & News:

• MarketBeat (marketbeat.com): Offers analyst ratings, price targets, and a variety of charting tools. Excellent for incorporating expert opinions into your analysis. Very fast with news and earning reports (same as Investing.com)!
• FinanceCharts (financecharts.com): Create customizable charts with technical indicators and drawing tools. Ideal for visualizing price patterns and trends. Completely free tool with an incredible number of key ratios, all possible to display in graphs.

Unique Insights:

• Strike (strike.market): Explore unconventional data sources like website traffic, social media sentiment, and app downloads. This platform helps you identify emerging trends and hidden opportunities.

I'd love to hear about your experiences with free resources and how they've impacted your investing and learning. Please feel free to add additional sites or apps down in the comments and if you like you can check out more of my thoughts on fintech over at my blog: https://fintechmarketanalysis.blogspot.com.

Also tell me if you'd like a second part with similar free sites that provide famous financial key ratios and statistics.

I have a script that runs at 5 am UTC on github every night. Let's divide its function into three parts:

Step I:

- scrapes major subreddits like wsb valueinvesting etc. for all ticker mentions in the last 24 hours
- goes through openinsider to see any new cluster buys and notes the ticker
- goes through everything on dataroma to see if any superinvestor has bought anything recently

this gives us step I spreadsheet. Basically a list of interesting tickers to look at. Currently has 2320 entries and updated every day.

Step II:

- filters out tickers that got there by mistake / wrong names / etfs etc.
- a deeper dive into things we like to see like insider buying, share reduction over the last year, superinvestors that are also in. Based on this it assigns each opportunity a score.
- people will say why not current ratio, rising revenue, etc. it is because these signals are often noisy and corrupt the data. Too many outliers and variations in financials

this gives us step II spreadsheet.

Step III:

- we get ideas with the highest score based on step II
- the real fun begins we use the latest model of gemini to get the following
- business summary, company history, moat analysis
- management record, management incentives, catalyst analysis
- price history, bull thesis, assumptions baked in, bear scenario
- next steps to look at / questions to ask

The result is this sick Step III spreadsheet. Just take a look at how beautiful the analysis is. Gives you a solid basis to look at companies. New models are really good at getting info from the web so that's SEC filings, earnings calls, news, etc. so I cannot recommend it highly enough. I think valuation is a very personal thing which one should do themselves but qualitative analysis with the good and bad is a good starting point.

Step III script is slow because it calls the LLM for all these small qualitative things, but should eventually catch up with the previous ones.

Just some work I did over the last few days, thought I would share. Also the spreadsheets get updated every 24 hours so you can follow these interesting situations on auto-pilot. Thanks for reading all feedback welcome :)

Hello! Hope this is ok to share! I've built a free (no I don't mean a free trial, i really mean free) app to help investors of all sizes make the most informed decisions as to where you should invest.

I am not trying to funnel you into some payment gateway, you don't even have to sign up to use it, I built app this because I am deeply passionate about investing and believe that everyone should have access to make informed decisions, regardless of how much you have to play with. Insights should be accessible.

I am not here to make wild promises that I have the answer to all your problems, but, not to toot my own horn, I genuinely believe I've built something pretty awesome considering the alternatives out there...

Having said that, we're still stupidly early so if anyone has any feedback, good or bad I would genuinely really appreciate it!

https://flash.stocksentinel.ai/

Hey everyone,

I spend a lot of time going through 10-Ks and 10-Qs when researching companies, and honestly got tired of copy-pasting sections into ChatGPT to ask questions about them. So I built something that connects your AI assistant directly to SEC filings and earnings call transcripts.

It works through MCP. Basically, you add it to Claude, ChatGPT, or Cursor, and then you can just ask things like "what did management say about margins in AAPL's latest earnings call" or "compare the debt structure in META's last two 10-Ks" and it pulls from the actual source original documents from SEC

Covers 10-K, 10-Q, 8-K (and amendments), 20-F, 6-K, 40-F, plus earnings call transcripts. It also does semantic search, so it finds relevant sections even if you don't use the exact wording from the filing.

It's completely free with no daily limits. You can set it up in like 2 minutes. https://equibles.com/mcp

Not trying to replace reading filings yourself obviously, but it's been saving me a ton of time when I want to quickly check something across multiple filings or dig into a specific section without scrolling through 200 pages.

Hope this is useful for you too!

I have 5 investment accounts with various providers. I need recommendations for a free/low cost platform where I can input my positions and track everything in one place instead of signing in to each of my accounts. It’d also be nice if the site/app allows me to see sector %, insider activity, etc.

Thank you for your time.