[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"blog-list-blogEn":3},[4,289,507,724,904,1150,1373,1594,1791],{"id":5,"title":6,"author":7,"body":8,"date":257,"description":258,"extension":259,"faq":260,"featured":276,"mentionsTickers":276,"meta":277,"metaTitle":278,"navigation":279,"ogImage":28,"path":280,"readMinutes":281,"seo":282,"stem":283,"tags":284,"translationKey":287,"__hash__":288},"blogEn\u002Fblog\u002Fen\u002Fhow-to-read-stock-fundamentals.md","How to read a stock's fundamentals (without being an accountant)","Nikolaos Drongitis",{"type":9,"value":10,"toc":245},"minimark",[11,29,38,55,60,63,85,88,92,95,134,137,141,144,176,179,183,190,197,201,209,217,221,224,227,231,234,237],[12,13,21],"div",{"className":14},[15,16,17,18,19,20],"not-prose","mb-8","rounded-xl","overflow-hidden","border","border-surface-3",[22,23],"img",{"alt":24,"className":25,"src":28},"The three financial statements: income statement, balance sheet, cash flow",[26,27],"w-full","block","\u002Fblog\u002Fog-fundamentals.svg",[30,31,32,33,37],"p",{},"A company's fundamentals scare most beginners. Filings are huge, full of jargon and numbers. The good news: ",[34,35,36],"strong",{},"you don't have to read all of it."," You need a few things, in the right order.",[12,39,49],{"className":40},[15,16,41,42,43,19,44,45,46,47,48],"px-4","py-3","bg-warning\u002F10","border-warning-border\u002F40","rounded-lg","text-sm","text-warning-text","leading-relaxed",[30,50,51,54],{},[34,52,53],{},"Research, not advice."," What follows is educational and is not personalised investment advice. You are solely responsible for your decisions. Full disclosure at the end.",[56,57,59],"h2",{"id":58},"the-3-statements-one-sentence-each","The 3 statements, one sentence each",[30,61,62],{},"Every company publishes three core financial statements. You don't need accounting, you need to know what each one asks:",[64,65,66,73,79],"ul",{},[67,68,69,72],"li",{},[34,70,71],{},"Income statement:"," does the company make a profit? It shows revenue, costs, and what's left at the end.",[67,74,75,78],{},[34,76,77],{},"Balance sheet:"," what does it own and owe? It shows assets, debt, and equity at a point in time.",[67,80,81,84],{},[34,82,83],{},"Cash flow statement:"," do the earnings turn into real cash? It shows the money that actually comes in and goes out.",[30,86,87],{},"The third is the most underrated. A company can show profit on paper but generate no cash, and that's where a lot of problems hide.",[56,89,91],{"id":90},"the-5-point-quick-scan","The 5-point quick scan",[30,93,94],{},"Before you dig deep, this filter saves you hours. Look at five things:",[96,97,98,104,110,116,128],"ol",{},[67,99,100,103],{},[34,101,102],{},"Profitability."," Does it earn consistent operating profit, or live on narrative? Look at the 3-5 year trend, not one year.",[67,105,106,109],{},[34,107,108],{},"Debt."," Can it survive a bad year? Compare debt to operating profit (e.g. debt-to-EBITDA). Too much debt = fragile.",[67,111,112,115],{},[34,113,114],{},"Cash flow."," Is free cash flow positive and close to reported earnings? If earnings are far bigger than cash, find out why.",[67,117,118,121,122,127],{},[34,119,120],{},"Valuation."," Are you paying reasonably or pricing in a perfect future? This is where ",[123,124,126],"a",{"href":125},"\u002Fblog\u002Fwhat-is-an-undervalued-stock","fair value and margin of safety"," help.",[67,129,130,133],{},[34,131,132],{},"Quality of the numbers."," Are there signs something is being inflated? (More below.)",[30,135,136],{},"If any of these flags a problem, you stop there. You don't need to read 200 pages on a company with collapsing margins.",[56,138,140],{"id":139},"three-quality-scores-that-summarise-a-lot","Three quality scores that summarise a lot",[30,142,143],{},"Instead of weighing dozens of figures, three classic scores give a quick read:",[64,145,146,156,166],{},[67,147,148,151,152,155],{},[34,149,150],{},"Piotroski F-Score (0-9):"," uses 9 simple checks to show whether fundamentals are ",[34,153,154],{},"improving or deteriorating",". An 8-9 is a strong quality signal.",[67,157,158,161,162,165],{},[34,159,160],{},"Altman Z-Score:"," estimates ",[34,163,164],{},"bankruptcy risk",". It tells you whether the balance sheet is in a safe or dangerous zone.",[67,167,168,171,172,175],{},[34,169,170],{},"Beneish M-Score:"," surfaces the likelihood of ",[34,173,174],{},"earnings 'cooking'",". Not proof of fraud, but a signal to look more closely.",[30,177,178],{},"They're not magic, but a clearly bad score on these saves a lot of wasted time.",[56,180,182],{"id":181},"the-most-insidious-red-flag","The most insidious red flag",[30,184,185,186,189],{},"The most dangerous sign in a company isn't one big hole that shouts. It's when ",[34,187,188],{},"no red flag shows",", because the 'cooking' has been spread a little everywhere: in how they capitalise R&D, in depreciation, in stock compensation, in adjusted or non-GAAP earnings that conveniently make the ugly parts disappear.",[30,191,192,193,196],{},"A practical rule: always go back to the ",[34,194,195],{},"GAAP"," numbers (the official ones), not the adjusted ones the company serves you. Non-GAAP gives a 'clean' story, and then you have to roll it back to GAAP to see what was removed or added.",[56,198,200],{"id":199},"where-tools-take-it-from-here","Where tools take it from here",[30,202,203,204,208],{},"The mechanical part, gathering and checking all of this, is time-consuming but automatable. With one condition: the numbers have to be real. A general-purpose language model often ",[123,205,207],{"href":206},"\u002Fblog\u002Fwhy-ai-stock-tools-hallucinate","invents figures with confidence",", so a tool is only worth it if its data comes from the official filings, not from its \"memory\".",[30,210,211,212,216],{},"If you want to see these checks run automatically in one structured analysis, with the sources in front, you can ",[123,213,215],{"href":214},"\u002Fanalyze","run one"," on a stock you know well.",[56,218,220],{"id":219},"what-this-means-for-you","What this means for you",[30,222,223],{},"You don't need to become an accountant. You need to know what each statement asks, run the 5-point quick scan, and not blindly trust adjusted numbers. With that, in a few minutes you can separate what's worth digging into from what to leave.",[225,226],"hr",{},[56,228,230],{"id":229},"important-disclosure","Important disclosure",[30,232,233],{},"This article is educational. It is not investment advice and does not take into account your personal circumstances, objectives, or financial situation.",[30,235,236],{},"The scores (Piotroski, Altman, Beneish) and financial figures are analytical tools, not guarantees. Investing in stocks carries risk, including the possible loss of all invested capital. Past performance is not a reliable indicator of future results.",[30,238,239,240,244],{},"You are solely responsible for your investment decisions. See the ",[123,241,243],{"href":242},"\u002Fterms","Terms"," for the full disclaimer.",{"title":246,"searchDepth":247,"depth":247,"links":248},"",3,[249,251,252,253,254,255,256],{"id":58,"depth":250,"text":59},2,{"id":90,"depth":250,"text":91},{"id":139,"depth":250,"text":140},{"id":181,"depth":250,"text":182},{"id":199,"depth":250,"text":200},{"id":219,"depth":250,"text":220},{"id":229,"depth":250,"text":230},"2026-06-10","Filings are huge, but you don't have to read all of it. The 3 statements, a 5-point quick scan, and 3 quality scores in plain English.","md",[261,264,267,270,273],{"q":262,"a":263},"What are a stock's fundamentals?","They are the financials of the business behind the stock: revenue, earnings, debt, cash flow, margins. Fundamental analysis looks at the health and value of the company, as opposed to technical analysis, which looks at the price and the chart.",{"q":265,"a":266},"What are the 3 core financial statements?","The income statement (does the company make a profit?), the balance sheet (what does it own and owe?), and the cash flow statement (do the earnings turn into real cash?). Together they give the full picture.",{"q":268,"a":269},"Do I have to read the whole 10-K?","No. A 10-K is hundreds of pages, but for a first read a few figures are enough: profitability, debt, cash flow, valuation, and the quality of the numbers. If any of those flags a problem, you stop there.",{"q":271,"a":272},"What is the Piotroski score?","A 0-9 score that uses 9 simple checks to show whether a company's fundamentals are improving or deteriorating (profitability, leverage, efficiency). An 8-9 is a quality signal, a 2-3 a warning.",{"q":274,"a":275},"What is the most insidious red flag?","When it looks like there is none. Spread-thin 'cooking', a little in R&D capitalisation, a little in depreciation, a little in adjusted\u002Fnon-GAAP earnings, is hard to filter because no single figure screams.",false,{},"How to read stock fundamentals (for beginners)",true,"\u002Fblog\u002Fhow-to-read-stock-fundamentals",8,{"title":6,"description":258},"blog\u002Fen\u002Fhow-to-read-stock-fundamentals",[285,286],"investing","basics","how-to-read-stock-fundamentals","GzxoAKiIu8LgbbwJMD_2j6NAdK-rSBWCeyPZYxvusM4",{"id":290,"title":291,"author":7,"body":292,"date":257,"description":481,"extension":259,"faq":482,"featured":276,"mentionsTickers":276,"meta":498,"metaTitle":499,"navigation":279,"ogImage":301,"path":125,"readMinutes":500,"seo":501,"stem":502,"tags":503,"translationKey":505,"__hash__":506},"blogEn\u002Fblog\u002Fen\u002Fwhat-is-an-undervalued-stock.md","What does 'undervalued' really mean: margin of safety and value traps",{"type":9,"value":293,"toc":472},[294,302,305,312,316,326,329,333,345,348,352,363,366,380,388,392,399,402,428,435,439,442,444,454,459,461,463,465,468],[12,295,297],{"className":296},[15,16,17,18,19,20],[22,298],{"alt":299,"className":300,"src":301},"Price below fair value, with the margin of safety in between",[26,27],"\u002Fblog\u002Fog-margin-of-safety.svg",[30,303,304],{},"One of the most misunderstood words in investing is \"undervalued\". Most people confuse it with \"cheap\", meaning a low number on the ticker. They are not the same, and the difference is the whole game.",[12,306,308],{"className":307},[15,16,41,42,43,19,44,45,46,47,48],[30,309,310,54],{},[34,311,53],{},[56,313,315],{"id":314},"price-vs-value","Price vs value",[30,317,318,321,322,325],{},[34,319,320],{},"Price"," is what you pay. ",[34,323,324],{},"Value"," is what you get. A stock is undervalued when its price is below the intrinsic value of the business, regardless of whether the price number is large or small.",[30,327,328],{},"A stock at 500 can be undervalued if the company is worth 800. A stock at 2 can be expensive if the company is worth 1. \"Cheap as a number\" tells you nothing on its own.",[56,330,332],{"id":331},"how-you-approach-value","How you approach \"value\"",[30,334,335,336,339,340,344],{},"Intrinsic value is not visible on the ticker, you estimate it. The most common way is a ",[34,337,338],{},"DCF (Discounted Cash Flow)",": you work out how much cash the company will generate in the future and discount it back to today. A DCF is not a crystal ball, it's a model, and it's only as good as its assumptions. For how it works and why analyst price targets so often miss, see the ",[123,341,343],{"href":342},"\u002Fblog\u002Fwhat-is-dcf-valuation","guide to DCF valuation",".",[30,346,347],{},"Because every value estimate carries uncertainty, it isn't enough to buy \"at value\". You need a buffer.",[56,349,351],{"id":350},"margin-of-safety-the-most-important-part","Margin of safety: the most important part",[30,353,354,355,358,359,362],{},"The ",[34,356,357],{},"margin of safety"," is the idea that made Benjamin Graham and Warren Buffett famous: buy far enough ",[34,360,361],{},"below"," your estimate of value that, even if your estimate is wrong, you aren't ruined.",[30,364,365],{},"If you estimate a company is worth 100 per share and you buy at 70, you have a 30% margin. That protects you from two things:",[64,367,368,374],{},[67,369,370,373],{},[34,371,372],{},"Being wrong on the estimate."," Maybe the company is actually worth 85, not 100. Buying at 70, you still come out ahead.",[67,375,376,379],{},[34,377,378],{},"Bad luck."," An unexpected bad year, a sector shock. The margin absorbs part of the hit.",[30,381,382,383,387],{},"The more uncertain the company (cyclical, no strong ",[123,384,386],{"href":385},"\u002Fblog\u002Fwhat-is-an-economic-moat","economic moat","), the bigger the margin you want.",[56,389,391],{"id":390},"the-trap-value-traps","The trap: value traps",[30,393,394,395,398],{},"This is where most people lose. A stock that looks cheap (low P\u002FE, beaten-down price) is not automatically an opportunity. It can be a ",[34,396,397],{},"value trap",": cheap for a reason.",[30,400,401],{},"Signs you are looking at a value trap, not an opportunity:",[64,403,404,410,416,422],{},[67,405,406,409],{},[34,407,408],{},"A declining business."," Revenue or margins shrinking year after year.",[67,411,412,415],{},[34,413,414],{},"Losing share"," to a faster competitor or a new technology.",[67,417,418,421],{},[34,419,420],{},"Burning cash"," or carrying debt that is strangling it.",[67,423,424,427],{},[34,425,426],{},"The \"cheap\" never closes."," The price keeps falling and the low P\u002FE just trails the falling earnings.",[30,429,430,431,434],{},"The difference between an opportunity and a trap is not in the price. It's in the ",[34,432,433],{},"business",": is it temporarily misunderstood, or permanently broken?",[56,436,438],{"id":437},"the-special-case-companies-with-no-earnings","The special case: companies with no earnings",[30,440,441],{},"When a company has no earnings yet (many tech, early-stage), P\u002FE doesn't help, there isn't one. There, valuation becomes purely forward-looking: you have to estimate when and how much it will become profitable, based on the business. It's the hardest case, and where most people either dramatically over- or under-estimate.",[56,443,220],{"id":219},[30,445,446,447,449,450,453],{},"\"Undervalued\" does not mean \"cheap\". It means: you estimate the value of the business, you buy far enough below it, and you make sure the discount is due to the market misunderstanding something, not a real problem. The two tools are the ",[34,448,357],{}," (buying discipline) and ",[34,451,452],{},"understanding the business"," (so you don't fall into a value trap).",[30,455,456,457,216],{},"If you want to see fair value computed with DCF, margin of safety, and a read of the business in one structured analysis, you can ",[123,458,215],{"href":214},[225,460],{},[56,462,230],{"id":229},[30,464,233],{},[30,466,467],{},"Valuation concepts (DCF, margin of safety, fair value) are estimates based on assumptions and may prove wrong. Investing in stocks carries risk, including the possible loss of all invested capital. Past performance is not a reliable indicator of future results.",[30,469,239,470,244],{},[123,471,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":473},[474,475,476,477,478,479,480],{"id":314,"depth":250,"text":315},{"id":331,"depth":250,"text":332},{"id":350,"depth":250,"text":351},{"id":390,"depth":250,"text":391},{"id":437,"depth":250,"text":438},{"id":219,"depth":250,"text":220},{"id":229,"depth":250,"text":230},"A low price doesn't mean undervalued. See what intrinsic value is, what margin of safety means, and how to tell a real opportunity from a value trap.",[483,486,489,492,495],{"q":484,"a":485},"What does 'undervalued' mean?","An undervalued stock is one whose market price is below the intrinsic (real) value of the business. It has nothing to do with whether the price is a small number. A stock at 500 can be undervalued and one at 3 can be expensive.",{"q":487,"a":488},"What is margin of safety?","It is the safety buffer: you buy far enough below your estimate of value that, even if your estimate is somewhat wrong, you don't lose. If you estimate value at 100 and buy at 70, you have a 30% margin of safety.",{"q":490,"a":491},"How do I work out a stock's real value?","The most common method is a DCF: you discount the company's future cash flows back to today. It's an estimate, not an exact number, and it depends on your assumptions, which is exactly why you also need a margin of safety.",{"q":493,"a":494},"What is a value trap?","A stock that looks cheap (low P\u002FE, low price) but is cheap for a reason: the business is declining, losing share, or burning cash. The price keeps falling and the 'discount' never closes.",{"q":496,"a":497},"Does a low P\u002FE mean a stock is undervalued?","Not necessarily. A low P\u002FE can mean the market expects earnings to fall (value trap), or that the sector is cyclical. P\u002FE is a hint, not proof of undervaluation.",{},"What does undervalued mean (margin of safety)",7,{"title":291,"description":481},"blog\u002Fen\u002Fwhat-is-an-undervalued-stock",[504,286],"valuation","what-is-an-undervalued-stock","XaqpIjVTVJU_GBNrYhCMNpKhBIe9P7AjPEsrDXS2fwI",{"id":508,"title":509,"author":7,"body":510,"date":704,"description":705,"extension":259,"faq":706,"featured":276,"mentionsTickers":276,"meta":716,"metaTitle":717,"navigation":279,"ogImage":519,"path":718,"readMinutes":500,"seo":719,"stem":720,"tags":721,"translationKey":722,"__hash__":723},"blogEn\u002Fblog\u002Fen\u002Fhow-long-to-analyze-a-stock.md","How long does it take to analyze a stock (and where the time actually goes)",{"type":9,"value":511,"toc":695},[512,520,523,530,538,542,545,552,559,563,570,576,582,584,587,614,617,621,627,633,636,640,651,658,670,672,675,678,680,682,684,687,690],[12,513,515],{"className":514},[15,16,17,18,19,20],[22,516],{"alt":517,"className":518,"src":519},"A time spectrum from minutes to weeks for analyzing a stock",[26,27],"\u002Fblog\u002Fog-research-time.svg",[30,521,522],{},"Ask ten investors how long it takes them to analyze a stock and you will get ten different answers. The most honest one usually sounds like this: \"anywhere from a few minutes to several weeks, depending.\" And the whole point hides in that \"depending\".",[30,524,525,526,529],{},"The question is not how much time, but ",[34,527,528],{},"where"," the time goes. Because once you understand where it goes, you can cut the part that is merely tedious and keep the part that actually matters.",[12,531,533],{"className":532},[15,16,41,42,43,19,44,45,46,47,48],[30,534,535,537],{},[34,536,53],{}," Ploutos AI is an automated research tool. What follows is educational and is not personalised investment advice. You are solely responsible for your own investment decisions. Full disclosure at the end of the article.",[56,539,541],{"id":540},"why-the-time-varies-so-much","Why the time varies so much",[30,543,544],{},"Two things decide whether an analysis takes you ten minutes or ten days.",[30,546,547,548,551],{},"The first is ",[34,549,550],{},"how well you already know the industry",". A software company that looks like five others you have worked through is fast. A biotech, an insurer, or a shipping company, if you have never touched the sector, takes time just to grasp what it actually sells and how it makes money.",[30,553,554,555,558],{},"The second is ",[34,556,557],{},"what decision you are trying to make",". A quick \"is this even worth a closer look?\" is minutes. A \"I am putting in a meaningful amount and holding for years\" justifies weeks. Not every stock needs the same depth, and treating them all the same is the surest way to waste time.",[56,560,562],{"id":561},"where-the-time-actually-goes","Where the time actually goes",[30,564,565,566,569],{},"Here is the surprise: the time does ",[34,567,568],{},"not"," go into the numbers. Revenue, earnings, debt, margins, you find all of that in minutes. The real time goes into two things that no quick lookup solves.",[30,571,547,572,575],{},[34,573,574],{},"understanding exactly what the company does and where it makes money",". It is easy to buy something you do not understand, then sell it on the first dip because you have no conviction about what you hold. Plenty of people have sold good stocks far too early for exactly this reason, not because they got the entry wrong, but because they had no clear picture of the business to hold through the noise.",[30,577,554,578,581],{},[34,579,580],{},"checking whether the numbers are real",". Some companies massage things a little everywhere, in how they capitalise R&D, in depreciation, in adjusted earnings that conveniently make the ugly parts disappear. Spotting that takes time and experience, and it is exactly the part most people skip.",[56,583,91],{"id":90},[30,585,586],{},"Before you dig deep, a fast filter saves hours. The goal is not to decide, but to quickly figure out whether it is worth continuing. Look at five things:",[64,588,589,594,599,604,609],{},[67,590,591,593],{},[34,592,102],{}," Does it earn consistent operating profit, or does it live on promises and narrative?",[67,595,596,598],{},[34,597,108],{}," Can it survive a bad year, or is it so leveraged that one wrong turn sends it into the wall?",[67,600,601,603],{},[34,602,114],{}," Do the earnings turn into actual cash, or do they sit on paper as receivables and accounting entries?",[67,605,606,608],{},[34,607,120],{}," Are you paying a reasonable price for what you get, or pricing in a perfect future that has to play out exactly?",[67,610,611,613],{},[34,612,132],{}," Are there signs something is being inflated? This is where ratios like Piotroski (fundamental quality), Altman Z (bankruptcy risk), and Beneish (possible manipulation) help.",[30,615,616],{},"If any of these flags a problem, you stop right there and save the weeks. That is the point of the quick scan, to let you say \"no\" fast, so you can spend your time where it is worth it.",[56,618,620],{"id":619},"the-genuinely-hard-part","The genuinely hard part",[30,622,623,624],{},"If it passes the filter, the hard part begins, and it is almost always the same: ",[34,625,626],{},"understanding the business well enough to know what you hold.",[30,628,629,630,632],{},"It is not the math. The math is time-consuming but not hard. The hard part is answering questions that have no ready-made number: why do customers pick this company over the next one? How easily could someone copy it? What has to happen for today's price to make sense? That \"how hard is it to copy\" is essentially the company's ",[123,631,386],{"href":385},", and it is one of the most decisive pieces of the picture.",[30,634,635],{},"When you have clear answers to these, a 20% drop is an opportunity or a signal, not a reason to panic. When you do not, every move in the price scares you, because you cannot tell whether what you own changed or the market just had a bad day.",[56,637,639],{"id":638},"how-to-save-time-without-losing-depth","How to save time without losing depth",[30,641,642,643,646,647,650],{},"The key is not to read less. It is to automate the ",[34,644,645],{},"mechanical"," part, gathering and checking the data, and keep your time for the part that needs ",[34,648,649],{},"judgment",", understanding the business and the risk scenarios.",[30,652,653,654,657],{},"That is where tools that read the official filings for you and surface a few understandable figures with the sources help, instead of leaving you to dig through hundreds of pages. With one condition: the numbers have to be real. A general-purpose language model often ",[123,655,656],{"href":206},"invents figures with total confidence",", so a tool is only worth it if its data is pulled from a verifiable source, not from the model's \"memory\".",[30,659,660,661,665,666,669],{},"That is exactly the logic behind Ploutos AI: the mechanical part happens automatically and with citations, and the judgment part stays with you, with the \"why\" alongside the \"what could go wrong\". If you want to see how the stages fit together, there is a ",[123,662,664],{"href":663},"\u002Fblog\u002Fhow-ploutos-analyzes-a-stock","detailed walkthrough of the pipeline",", or you can just ",[123,667,668],{"href":214},"run an analysis"," on a stock you know well and compare.",[56,671,220],{"id":219},[30,673,674],{},"The right question is not \"how much time does it take\". It is \"where is my time worth spending\". A few minutes to quickly cut anything that does not hold up, and the bulk of your time where the real decision hides: understanding the business and confirming the numbers are real.",[30,676,677],{},"If you have those two clear, analysis stops being a chore and becomes conviction. And conviction is what keeps you in a good position when the market tests you.",[225,679],{},[56,681,230],{"id":229},[30,683,233],{},[30,685,686],{},"The output of any analysis run on Ploutos AI is for informational and educational purposes only. Ratings, fair-value estimates, and any other quantitative output are produced by an automated system at a given moment and may become outdated as market conditions, fundamentals, or news change. They are analytical reference points, not price targets or instructions to act.",[30,688,689],{},"Investing in stocks carries risk, including the possible loss of all invested capital. Past performance is not a reliable indicator of future results. Different investors reach different conclusions from the same information, depending on their objectives, time horizon, tax situation, and risk tolerance.",[30,691,239,692,694],{},[123,693,243],{"href":242}," for the full disclaimer and disclosures.",{"title":246,"searchDepth":247,"depth":247,"links":696},[697,698,699,700,701,702,703],{"id":540,"depth":250,"text":541},{"id":561,"depth":250,"text":562},{"id":90,"depth":250,"text":91},{"id":619,"depth":250,"text":620},{"id":638,"depth":250,"text":639},{"id":219,"depth":250,"text":220},{"id":229,"depth":250,"text":230},"2026-06-09","From a few minutes to several weeks. See where the time actually goes when you analyze a stock, a 5-point quick scan, and how to save time without losing depth.",[707,710,713],{"q":708,"a":709},"How long does it take to analyze a stock?","Anywhere from a few minutes to several weeks, depending on how well you already know the industry and what decision you are trying to make.",{"q":711,"a":712},"Where does the time actually go?","Not into the numbers. It goes into understanding exactly what the company does and where it makes money, and confirming the numbers are real.",{"q":714,"a":715},"How do I save time without losing depth?","Automate the mechanical part (gathering and checking data) and keep your time for the part that needs judgment.",{},"How long does it take to analyze a stock","\u002Fblog\u002Fhow-long-to-analyze-a-stock",{"title":509,"description":705},"blog\u002Fen\u002Fhow-long-to-analyze-a-stock",[285,286],"how-long-to-analyze-a-stock","Grywzss8ufgeqrR3bC3yA6XZL1nXo0SqdRNoIj-kQkM",{"id":725,"title":726,"author":7,"body":727,"date":878,"description":879,"extension":259,"faq":880,"featured":276,"mentionsTickers":276,"meta":893,"metaTitle":894,"navigation":279,"ogImage":736,"path":895,"readMinutes":896,"seo":897,"stem":898,"tags":899,"translationKey":902,"__hash__":903},"blogEn\u002Fblog\u002Fen\u002Fhow-we-track-our-track-record.md","How we track our own track record (and why most pickers hide theirs)",{"type":9,"value":728,"toc":869},[729,737,740,743,752,756,763,770,773,777,780,787,791,798,801,805,808,815,819,822,825,829,846,848,852,855,858,861,864],[12,730,732],{"className":731},[15,16,17,18,19,20],[22,733],{"alt":734,"className":735,"src":736},"Tracked picks plotted against a market benchmark over time",[26,27],"\u002Fblog\u002Fog-track-record.svg",[30,738,739],{},"Watch finance content for a week and you will see a hundred confident calls and almost no scorecards. Every screenshot is a winner. Every \"I told you so\" arrives after the fact. The losing calls quietly evaporate, and the ones that worked get pinned to the top of the feed.",[30,741,742],{},"This is not usually fraud. It is something more ordinary and more corrosive: a thousand small choices about what to show and what to forget, all leaning in the same flattering direction. A research tool that wants to be trusted has to do the opposite, and it has to do it by design, not by good intentions.",[12,744,746],{"className":745},[15,16,41,42,43,19,44,45,46,47,48],[30,747,748,751],{},[34,749,750],{},"This is research, not advice."," Ploutos AI is an automated research tool. The analyses it produces are not personalised investment advice, do not consider your individual circumstances, and are not instructions to transact. Past performance is not a reliable indicator of future results. Full disclosures at the end of this article.",[56,753,755],{"id":754},"survivorship-bias-why-most-track-records-are-fiction","Survivorship bias: why most track records are fiction",[30,757,758,759,762],{},"The technical name for the trick is ",[34,760,761],{},"survivorship bias",": you judge a strategy only by the examples that survived, because the failures are no longer in front of you. A pundit who makes fifty predictions and reminds you of the five that landed looks like a genius. The other forty-five are not lies, they are just gone.",[30,764,765,766,769],{},"It has a close cousin, ",[34,767,768],{},"hindsight bias",": the temptation to describe a call as cleaner and more confident than it actually was at the time. \"I always said that sector would rebound\" is easy to write once it has rebounded.",[30,771,772],{},"Both biases share one root cause: there is no fixed, timestamped record of what was actually claimed, and when. Remove that record and any track record becomes a story you tell about the past. Keep it, rigorously, and the story has to match the receipts.",[56,774,776],{"id":775},"we-timestamp-every-pick-at-decision-time","We timestamp every pick at decision time",[30,778,779],{},"The foundation is simple and unglamorous: the moment an analysis produces a verdict, that verdict is recorded, with its date, its rating, and the price at that instant. It is frozen. Nothing about it can be quietly edited later to look smarter.",[30,781,782,783,786],{},"That timestamp is what makes the whole thing honest. Performance is always measured from the price on the day the call was made, not from some flattering entry point chosen afterwards. There is no reaching back to start the clock at a convenient low. The clock starts when the analysis ran, and you can see the analysis that produced it, the same ",[123,784,785],{"href":663},"structured output and Devil's Advocate critique"," you saw on the day.",[56,788,790],{"id":789},"benchmark-against-the-market-not-against-zero","Benchmark against the market, not against zero",[30,792,793,794],{},"\"Up 12%\" sounds great until you learn the whole market was up 15% over the same window. A number on its own is not a result, the only honest scorecard is ",[795,796,797],"em",{},"relative to the alternative you actually had.",[30,799,800],{},"So every tracked pick is measured against a broad market benchmark over the same period. The question is never just \"did this go up,\" it is \"did this do better or worse than simply owning the index instead.\" That is a far harder bar to clear, and it is the only one that tells you whether the research added anything at all. Beating zero is luck in a bull market. Beating the market is the thing that has to be earned.",[56,802,804],{"id":803},"we-show-the-losers-too","We show the losers too",[30,806,807],{},"A scorecard that only contains winners is not a scorecard. The track record surfaces the full distribution, the best calls and the worst ones side by side, not a curated highlight reel. If a thesis underperformed, it stays on the record underperforming.",[30,809,810,811,344],{},"This is uncomfortable on purpose. A tool that hides its misses is optimising for how it looks, and the moment it does that it stops being useful to you. Seeing where the process was wrong is exactly how you calibrate how much weight to give it, and it is information a marketing page will never volunteer. The same discipline runs through the product itself: every submitted ticker gets an honest verdict even when that verdict is negative, and the analysis ",[123,812,814],{"href":813},"\u002Fblog\u002Fwhy-we-refuse-to-analyze-a-stock","stops rather than guess when the data is too thin",[56,816,818],{"id":817},"why-past-performance-still-is-not-a-promise","Why past performance still is not a promise",[30,820,821],{},"Here is the part that honesty requires us to say plainly, even though it undercuts the marketing: a good track record is not a guarantee of future results, and you should distrust anyone who implies otherwise.",[30,823,824],{},"Markets change regimes. A process that suited the last few years can struggle in the next. Sample sizes are smaller than they look, and luck and skill are genuinely hard to separate over short windows. A transparent track record is valuable not because it predicts the future, but because it tells you the truth about the past, which biases, sample size, benchmark, and all. That is the most any honest scorecard can offer, and it is a great deal more than most offer at all.",[56,826,828],{"id":827},"see-it-for-yourself","See it for yourself",[30,830,831,832,836,837,841,842,845],{},"The point of tracking openly is that you do not have to take any of this on faith. You can look at the ",[123,833,835],{"href":834},"\u002Ftrack-record","public track record"," and your own ",[123,838,840],{"href":839},"\u002Fperformance","performance history",", timestamps, benchmark comparison, winners and losers included. Then read how the underlying analysis is produced in our ",[123,843,844],{"href":663},"walkthrough of the pipeline",", and decide for yourself how much weight the process has earned.",[225,847],{},[56,849,851],{"id":850},"important-information","Important information",[30,853,854],{},"This article describes the methodology behind a research tool. It is not investment advice and does not take into account your personal circumstances, objectives, or financial situation.",[30,856,857],{},"The output of any analysis run on Ploutos AI is for informational and educational purposes only. Model ratings, fair-value estimates, margin-of-safety metrics, and any other quantitative outputs are generated by an automated system at a point in time and may become outdated as market conditions, company fundamentals, or news change. They are analytical reference points produced by a model, not price targets or instructions to transact.",[30,859,860],{},"Investing in equities involves risk, including the possible loss of all capital invested. The past performance of any analysis, methodology, or strategy is not a reliable indicator of future results. Different investors will reach different conclusions from the same information depending on their objectives, time horizon, tax situation, and risk tolerance.",[30,862,863],{},"You are solely responsible for your investment decisions. Before acting on any information from this site, you should assess whether it is appropriate for your circumstances and consult an appropriately qualified financial professional if you are in any doubt.",[30,865,866,867,694],{},"See ",[123,868,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":870},[871,872,873,874,875,876,877],{"id":754,"depth":250,"text":755},{"id":775,"depth":250,"text":776},{"id":789,"depth":250,"text":790},{"id":803,"depth":250,"text":804},{"id":817,"depth":250,"text":818},{"id":827,"depth":250,"text":828},{"id":850,"depth":250,"text":851},"2026-05-25","Most stock pickers quietly bury their misses. Here is how Ploutos AI records every pick at decision time and benchmarks it against the market, openly.",[881,884,887,890],{"q":882,"a":883},"How is the track record measured?","Each pick is tracked from its entry price, marked to market, and compared against the index (SPY) over the same period.",{"q":885,"a":886},"What is alpha?","How a pick did relative to the market (S&P 500). Positive alpha means it beat the index.",{"q":888,"a":889},"Why make it public?","Because the right way to earn trust isn't 'trust me', it's showing what actually happened, the good moves and the bad.",{"q":891,"a":892},"Do a few weeks of track record mean anything?","No. A forward track record needs months to mean something. A few weeks is an indication, not proof.",{},"How we track our own track record","\u002Fblog\u002Fhow-we-track-our-track-record",6,{"title":726,"description":879},"blog\u002Fen\u002Fhow-we-track-our-track-record",[900,901],"product","methodology","how-we-track-our-track-record","MPbMUfMkazsr3qm2BqBlEk8fejPn0ikJA1GqcHeAykE",{"id":905,"title":906,"author":7,"body":907,"date":878,"description":1130,"extension":259,"faq":1131,"featured":276,"mentionsTickers":276,"meta":1144,"metaTitle":1133,"navigation":279,"ogImage":916,"path":385,"readMinutes":281,"seo":1145,"stem":1146,"tags":1147,"translationKey":1148,"__hash__":1149},"blogEn\u002Fblog\u002Fen\u002Fwhat-is-an-economic-moat.md","What is an economic moat, and how do you actually measure it?",{"type":9,"value":908,"toc":1121},[909,917,924,931,939,943,950,953,957,960,992,999,1003,1006,1017,1021,1024,1034,1040,1043,1047,1050,1074,1077,1081,1084,1094,1103,1105,1107,1110,1113,1115,1117],[12,910,912],{"className":911},[15,16,17,18,19,20],[22,913],{"alt":914,"className":915,"src":916},"An economic moat shown as a defended core with above-sector returns",[26,27],"\u002Fblog\u002Fog-moat.svg",[30,918,919,920,923],{},"Warren Buffett popularised one of the most useful images in investing. Picture a great business as a castle, and its profits as the treasure inside. Every profitable castle attracts attackers, competitors who want a share of that treasure. What protects it over time is the ",[34,921,922],{},"moat",": a structural advantage that makes the castle genuinely hard to attack.",[30,925,926,927,930],{},"A company without a moat can earn high returns for a while, but competition eventually arrives, undercuts its prices, and grinds those returns back down to ordinary. A company ",[795,928,929],{},"with"," a moat can defend its profits for years, sometimes decades. For a long-term investor, almost nothing matters more, and almost nothing is harder to measure honestly.",[12,932,934],{"className":933},[15,16,41,42,43,19,44,45,46,47,48],[30,935,936,938],{},[34,937,750],{}," This article is educational. It explains a concept used in fundamentals analysis, it is not a recommendation to buy or sell any security. Full disclosures at the end of this article.",[56,940,942],{"id":941},"what-an-economic-moat-actually-is","What an economic moat actually is",[30,944,945,946,949],{},"An economic moat is a ",[795,947,948],{},"durable"," competitive advantage, the operative word being durable. It is the reason a business can keep earning returns on its capital that are well above the cost of that capital, without competition immediately competing those returns away.",[30,951,952],{},"That phrase, returns above the cost of capital, is the whole game. Any company can grow by pouring in more money. The question that separates a great business from a merely large one is whether each dollar it invests comes back as meaningfully more than a dollar, year after year, even when rivals are trying to take its lunch. A moat is the structural reason the answer stays yes.",[56,954,956],{"id":955},"the-main-types-of-moat","The main types of moat",[30,958,959],{},"Moats come in a handful of recognisable shapes:",[64,961,962,968,974,980,986],{},[67,963,964,967],{},[34,965,966],{},"Network effects."," The product gets more valuable as more people use it. A marketplace or a payments network is worth more to each user precisely because everyone else is already there, which makes it extremely hard for a newcomer to break in.",[67,969,970,973],{},[34,971,972],{},"Switching costs."," Once a customer is embedded, leaving is painful, expensive, or risky. Enterprise software that a whole company runs on is a classic example, the cost is not the subscription, it is the migration.",[67,975,976,979],{},[34,977,978],{},"Cost advantage."," The business can produce the same thing more cheaply than anyone else, through scale, location, or a unique process, and can therefore undercut rivals and still profit.",[67,981,982,985],{},[34,983,984],{},"Intangible assets."," Brands that let a company charge a premium, patents that lock out imitation, or regulatory licences that competitors cannot easily obtain.",[67,987,988,991],{},[34,989,990],{},"Efficient scale."," A market just big enough for one or two players to serve profitably, where a third entrant would make the economics bad for everyone, so none arrive.",[30,993,994,995,998],{},"The names matter less than the test they all have to pass: does this advantage ",[795,996,997],{},"persist"," when a well-funded competitor attacks it? A trendy product is not a moat. A patent that expires next year is a shrinking one.",[56,1000,1002],{"id":1001},"the-measurement-problem","The measurement problem",[30,1004,1005],{},"Here is the hard part. The descriptions above are qualitative, you can only really confirm a network effect or a switching cost by understanding the business deeply, reading its filings, and watching how it behaves over years. You cannot do that, by hand, across thousands of companies. So how does an automated process judge something this subtle?",[30,1007,1008,1009,1012,1013,1016],{},"The answer is to stop trying to read the moat directly and instead look for the ",[34,1010,1011],{},"fingerprint it leaves in the financial statements."," A real, durable advantage is not just a story, it shows up in the numbers, because a business that can defend its profits ",[795,1014,1015],{},"actually keeps earning them."," That is something you can measure.",[56,1018,1020],{"id":1019},"the-financial-fingerprint-of-a-moat","The financial fingerprint of a moat",[30,1022,1023],{},"Two signals do most of the work.",[30,1025,1026,1029,1030,1033],{},[34,1027,1028],{},"High and persistent return on invested capital (ROIC)."," A single great year of ROIC proves nothing, anyone can get lucky once. What a moat produces is ROIC that stays well above the sector average ",[795,1031,1032],{},"year after year after year",". The persistence is the signal. A business that earns far more on its capital than its peers, and keeps doing so across an entire cycle, is almost certainly being protected by something structural, even if you cannot name it from the outside. So we look not just at the level of ROIC but at how many of the recent years cleared the sector bar.",[30,1035,1036,1039],{},[34,1037,1038],{},"Premium gross margins."," Pricing power, the ability to charge more than rivals without losing customers, is the most visible symptom of a moat. It shows up as a gross margin meaningfully above the sector. A company with no advantage has to compete on price, which compresses margins toward the industry average. A company that holds a premium margin for years is telling you customers are paying up for something they cannot easily get elsewhere.",[30,1041,1042],{},"Combine the two and you get a defensible, repeatable classification, which is exactly how Ploutos AI grades it.",[56,1044,1046],{"id":1045},"wide-narrow-or-none","Wide, narrow, or none",[30,1048,1049],{},"The classification lands in three buckets:",[64,1051,1052,1062,1068],{},[67,1053,1054,1057,1058,1061],{},[34,1055,1056],{},"Wide moat."," ROIC has been far above the sector, with consistency across most of the observed years, ",[795,1059,1060],{},"and"," gross margins carry a clear premium. This is the rare, durable-advantage profile.",[67,1063,1064,1067],{},[34,1065,1066],{},"Narrow moat."," A real but more modest edge, returns above the sector with decent consistency, or clear pricing power with respectable returns. An advantage, but one a determined competitor could erode.",[67,1069,1070,1073],{},[34,1071,1072],{},"None."," The financial fingerprint of commodity-like economics: returns near or below the cost of capital, no margin premium. The business may still be a fine investment at the right price, but you should not pay up expecting a durable advantage that the numbers do not support.",[30,1075,1076],{},"No single year and no single metric earns a \"wide\" label. It takes a pattern that holds up over time, which is the point, a moat that only existed last quarter was never a moat.",[56,1078,1080],{"id":1079},"why-a-moat-changes-how-much-margin-of-safety-you-need","Why a moat changes how much margin of safety you need",[30,1082,1083],{},"This is where the concept becomes practical. A moat does not just describe a business, it should change the price you are willing to pay for it.",[30,1085,1086,1087,1090,1091,1093],{},"A wide-moat company can reinvest its profits at high returns for years, which means its intrinsic value tends to ",[795,1088,1089],{},"grow"," over time. That durability justifies accepting a smaller discount to fair value, a smaller ",[123,1092,357],{"href":342},", because time is working for you. A no-moat business is the opposite: its advantage, if any, is fragile, its returns are more likely to fade, so you should demand a larger discount to compensate for that fragility before the price looks attractive.",[30,1095,1096,1097,1099,1100,344],{},"In other words, quality and price are not separate questions, they are the same question. A moat is one of the cleanest ways to ask it rigorously. If you want to see a moat classification produced alongside a full valuation and the rest of the research, you can ",[123,1098,668],{"href":214},", or read how moat, valuation, and the other signals come together in the ",[123,1101,1102],{"href":663},"full pipeline",[225,1104],{},[56,1106,851],{"id":850},[30,1108,1109],{},"This article is for general educational and informational purposes only. It is not investment advice and does not take into account your personal circumstances, objectives, or financial situation.",[30,1111,1112],{},"Any classification or quantitative output generated by Ploutos AI, including moat ratings, fair-value estimates, and margin-of-safety metrics, is produced by an automated system at a point in time and may become outdated as market conditions, company fundamentals, or news change. These are analytical reference points produced by a model, not price targets or instructions to transact.",[30,1114,860],{},[30,1116,863],{},[30,1118,866,1119,694],{},[123,1120,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":1122},[1123,1124,1125,1126,1127,1128,1129],{"id":941,"depth":250,"text":942},{"id":955,"depth":250,"text":956},{"id":1001,"depth":250,"text":1002},{"id":1019,"depth":250,"text":1020},{"id":1045,"depth":250,"text":1046},{"id":1079,"depth":250,"text":1080},{"id":850,"depth":250,"text":851},"An economic moat is a durable competitive advantage. Here is what one looks like, the main types, and how to measure it from a company's financial fingerprint.",[1132,1135,1138,1141],{"q":1133,"a":1134},"What is an economic moat?","The durable competitive advantage that protects a company's profits from competitors, like a moat around a castle.",{"q":1136,"a":1137},"What types of moat are there?","The main ones: network effects, switching costs, intangibles (brand, patents), cost advantage, and efficient scale.",{"q":1139,"a":1140},"How do you measure a moat in practice?","From durable high margins and ROIC over time, and from how hard it is for someone to copy the business.",{"q":1142,"a":1143},"Why does a moat matter to an investor?","A wide moat means more predictable and durable profits, which support a valuation over the long run.",{},{"title":906,"description":1130},"blog\u002Fen\u002Fwhat-is-an-economic-moat",[285,286],"what-is-an-economic-moat","bqkN4q5eLrP9pTQwRgwGxBnb09TRE6zq2fIrj7glooE",{"id":1151,"title":1152,"author":7,"body":1153,"date":878,"description":1352,"extension":259,"faq":1353,"featured":276,"mentionsTickers":276,"meta":1366,"metaTitle":1367,"navigation":279,"ogImage":1162,"path":342,"readMinutes":281,"seo":1368,"stem":1369,"tags":1370,"translationKey":1371,"__hash__":1372},"blogEn\u002Fblog\u002Fen\u002Fwhat-is-dcf-valuation.md","What is DCF valuation, and why analyst price targets are often wrong",{"type":9,"value":1154,"toc":1343},[1155,1163,1170,1173,1181,1185,1192,1199,1203,1209,1219,1229,1232,1236,1239,1242,1246,1253,1283,1297,1301,1304,1307,1311,1317,1325,1327,1329,1332,1335,1337,1339],[12,1156,1158],{"className":1157},[15,16,17,18,19,20],[22,1159],{"alt":1160,"className":1161,"src":1162},"Future cash flows discounted back to a present value",[26,27],"\u002Fblog\u002Fog-dcf.svg",[30,1164,1165,1166,1169],{},"The price of a stock is what the market is asking for it today. The ",[795,1167,1168],{},"value"," of a stock is a separate question: what is the underlying business actually worth? Those two numbers are often very different, and the entire discipline of value investing lives in the gap between them.",[30,1171,1172],{},"Discounted cash flow, or DCF, is the most fundamental tool for answering the second question. It is also one of the most misused. This article explains what a DCF really does, why a single DCF can be dangerously fragile, and why a careful process leans on it without trusting it alone.",[12,1174,1176],{"className":1175},[15,16,41,42,43,19,44,45,46,47,48],[30,1177,1178,1180],{},[34,1179,750],{}," This article is educational. It explains a valuation method, it is not a recommendation to buy or sell any security, and the example figures below are illustrative only. Full disclosures at the end of this article.",[56,1182,1184],{"id":1183},"the-one-idea-behind-dcf-time-has-a-price","The one idea behind DCF: time has a price",[30,1186,1187,1188,1191],{},"Imagine someone offers you 1,000 euros. Would you rather have it today or in five years? Today, obviously, and not only because of impatience. Money today can be invested, it carries no risk of never arriving, and inflation erodes the value of money you receive later. So a euro in the future is worth ",[795,1189,1190],{},"less"," than a euro now, and the further away it is, the less it is worth.",[30,1193,1194,1195,1198],{},"DCF takes that intuition and turns it into arithmetic. A business is, in the end, a machine for producing cash over time. If you can estimate the cash it will generate in the years ahead, and you can put a price on waiting, then you can translate all that future cash into a single number: what it is worth ",[795,1196,1197],{},"today",". That number is the company's intrinsic value, and dividing it by the share count gives you a value per share to compare against the market price.",[56,1200,1202],{"id":1201},"how-a-dcf-actually-works-in-three-steps","How a DCF actually works, in three steps",[30,1204,1205,1208],{},[34,1206,1207],{},"Step 1: Project the cash flows."," Start from the company's free cash flow, the cash left over after it pays to run and maintain the business, and project it forward, usually about ten years, using a growth rate. A mature, stable business might be assumed to grow that cash flow at a low single-digit rate, a faster-growing company at something higher, typically tapering toward a modest long-term rate as it matures.",[30,1210,1211,1214,1215,1218],{},[34,1212,1213],{},"Step 2: Discount each year back to today."," This is the \"discounted\" part. Each future year's cash flow is divided by a ",[795,1216,1217],{},"discount rate"," that reflects risk and the time value of money. A common shorthand: at a 10% discount rate, 1,000 euros a year from now is worth about 909 euros today, and 1,000 euros ten years out is worth only about 386. Riskier businesses get a higher discount rate, which shrinks their future cash more aggressively.",[30,1220,1221,1224,1225,1228],{},[34,1222,1223],{},"Step 3: Add a terminal value."," A company does not stop existing in year ten. To capture everything after the explicit forecast, you add a ",[795,1226,1227],{},"terminal value",", an estimate of all the cash beyond the projection, assuming a slow, steady long-term growth rate. This is then discounted back like everything else.",[30,1230,1231],{},"Add up all the discounted yearly cash flows and the discounted terminal value, and you have the estimated intrinsic value of the whole business today.",[56,1233,1235],{"id":1234},"why-a-single-dcf-is-dangerously-fragile","Why a single DCF is dangerously fragile",[30,1237,1238],{},"Here is the catch that humbles everyone who builds one: a DCF is exquisitely sensitive to its inputs. Nudge the growth rate up by two points and lower the discount rate by one, and the \"fair value\" can swing 40% or more. The model produces a precise-looking number, but that precision is an illusion, it inherits all the uncertainty of the assumptions you fed it. Garbage in, confidently-formatted garbage out.",[30,1240,1241],{},"This is why a DCF in the wrong hands becomes a way to justify a conclusion you already had. Want the stock to look cheap? Bump the growth rate. Want it to look expensive? Raise the discount rate. The math is honest, but it will faithfully launder a biased assumption into an authoritative-looking target.",[56,1243,1245],{"id":1244},"why-we-use-four-methods-not-one","Why we use four methods, not one",[30,1247,1248,1249,1252],{},"The defence against that fragility is not a better single model, it is refusing to rely on any single model. Ploutos AI estimates fair value with an ",[34,1250,1251],{},"ensemble of four independent methods",", each with different blind spots:",[64,1254,1255,1261,1267,1277],{},[67,1256,1257,1260],{},[34,1258,1259],{},"DCF",", the growth-aware estimate described above.",[67,1262,1263,1266],{},[34,1264,1265],{},"Sector multiples",", what comparable companies trade at on earnings, sales, and operating profit, adjusted for quality.",[67,1268,1269,1272,1273,1276],{},[34,1270,1271],{},"Earnings Power Value (EPV)",", a conservative anchor that assumes ",[795,1274,1275],{},"zero"," growth and asks what the business is worth purely on its current earning power. If a DCF says a company is cheap but EPV strongly disagrees, that tension is itself a signal.",[67,1278,1279,1282],{},[34,1280,1281],{},"The Graham Number",", a classic book-value-and-earnings benchmark from Benjamin Graham.",[30,1284,1285,1286,1289,1290,1293,1294,1296],{},"These are blended with weights that depend on the sector, because book value matters more for a bank than for a software company, and the result comes with a ",[795,1287,1288],{},"confidence level"," and a fair-value ",[795,1291,1292],{},"range",", not a single false-precision point. When the four methods agree, confidence is high. When they scatter widely, that disagreement is reported rather than hidden. Quality also bends the inputs: a business with a durable ",[123,1295,386],{"href":385}," earns a lower discount rate and a richer multiple, because its advantage is more likely to persist.",[56,1298,1300],{"id":1299},"why-analyst-price-targets-are-often-unreliable","Why analyst price targets are often unreliable",[30,1302,1303],{},"Sell-side analyst price targets are familiar, widely quoted, and structurally compromised. They are produced inside institutions with business relationships to the companies they cover, they cluster tightly around each other because being wrong alone is more career-threatening than being wrong together, and they usually carry a short, twelve-month horizon that has more to do with momentum than with intrinsic worth. The result is a number that often tracks the recent stock price rather than leading it.",[30,1305,1306],{},"A transparent, assumption-explicit valuation has the opposite character. You can see every input, you can change the ones you disagree with, and the conservative anchors keep optimism in check. It will not be right every time, no valuation method is, but it is honest about its uncertainty, which is more than a single confident price target ever offers.",[56,1308,1310],{"id":1309},"what-a-fair-value-is-and-is-not","What a fair value is, and is not",[30,1312,1313,1314,1316],{},"A fair-value estimate is a reference point, not a prophecy. It says \"based on these assumptions, here is roughly what the business is worth today, and here is how far the market price sits from that.\" The distance between price and value is the ",[34,1315,357],{},", the cushion that protects you when, not if, some of your assumptions turn out to be wrong.",[30,1318,1319,1320,1322,1323,344],{},"It does not tell you what the stock will do next quarter, and it is not a target you should expect the price to obediently reach. It is one disciplined input into your own judgement. If you want to see the four-method valuation run on a real company alongside the rest of the research, you can ",[123,1321,668],{"href":214},", or read how it fits into the ",[123,1324,1102],{"href":663},[225,1326],{},[56,1328,851],{"id":850},[30,1330,1331],{},"This article is for general educational and informational purposes only. It is not investment advice and does not take into account your personal circumstances, objectives, or financial situation. The example figures are illustrative and do not describe any specific security.",[30,1333,1334],{},"Valuation outputs generated by Ploutos AI, including fair-value estimates and margin-of-safety metrics, are produced by an automated system at a point in time and may become outdated as market conditions, company fundamentals, or news change. They are analytical reference points produced by a model, not price targets or instructions to transact.",[30,1336,860],{},[30,1338,863],{},[30,1340,866,1341,694],{},[123,1342,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":1344},[1345,1346,1347,1348,1349,1350,1351],{"id":1183,"depth":250,"text":1184},{"id":1201,"depth":250,"text":1202},{"id":1234,"depth":250,"text":1235},{"id":1244,"depth":250,"text":1245},{"id":1299,"depth":250,"text":1300},{"id":1309,"depth":250,"text":1310},{"id":850,"depth":250,"text":851},"Discounted cash flow, explained simply: valuing a company by its future cash, why a single DCF is fragile, and why analyst price targets are often unreliable.",[1354,1357,1360,1363],{"q":1355,"a":1356},"What is a DCF valuation?","DCF stands for Discounted Cash Flow: you estimate a company's future cash flows and discount them back to today to derive a fair value per share.",{"q":1358,"a":1359},"What is the discount rate (WACC)?","The rate that reflects the company's risk and cost of capital. Small changes in it move the valuation dramatically, which makes it one of the most sensitive assumptions.",{"q":1361,"a":1362},"Why do analyst price targets so often miss?","Because they depend on assumptions (growth, margins, discount rate, terminal value) that may not play out. A small change in an assumption moves the target a lot.",{"q":1364,"a":1365},"Is a DCF reliable?","It's a useful framework, not an exact number. It's only as good as its assumptions, which is why it's always paired with a margin of safety.",{},"What is DCF valuation?",{"title":1152,"description":1352},"blog\u002Fen\u002Fwhat-is-dcf-valuation",[504,286],"what-is-dcf-valuation","VSLMFGTzkLj1oYiLc18PXZCWUdowZT-HZLGR6g2LYGA",{"id":1374,"title":1375,"author":7,"body":1376,"date":878,"description":1573,"extension":259,"faq":1574,"featured":276,"mentionsTickers":276,"meta":1587,"metaTitle":1588,"navigation":279,"ogImage":1385,"path":206,"readMinutes":500,"seo":1589,"stem":1590,"tags":1591,"translationKey":1592,"__hash__":1593},"blogEn\u002Fblog\u002Fen\u002Fwhy-ai-stock-tools-hallucinate.md","Why AI stock tools hallucinate, and how we stop it",{"type":9,"value":1377,"toc":1564},[1378,1386,1389,1392,1400,1404,1407,1435,1438,1442,1449,1460,1463,1477,1481,1488,1494,1500,1504,1511,1518,1521,1525,1528,1531,1533,1539,1548,1550,1552,1554,1556,1558,1560],[12,1379,1381],{"className":1380},[15,16,17,18,19,20],[22,1382],{"alt":1383,"className":1384,"src":1385},"An ungrounded language-model answer next to a data-grounded pipeline",[26,27],"\u002Fblog\u002Fog-hallucinate.svg",[30,1387,1388],{},"Paste a ticker into a general-purpose chatbot and ask for an analysis, and you will get something that reads beautifully: a tidy P\u002FE ratio, a confident note about insiders buying last quarter, a clean paragraph on how the sector is rotating. The prose is fluent, the structure is professional, the tone is certain.",[30,1390,1391],{},"A lot of it may also be false. Not because the model is broken, but because it is doing exactly what it was built to do, and that job is not \"report facts.\"",[12,1393,1395],{"className":1394},[15,16,41,42,43,19,44,45,46,47,48],[30,1396,1397,1399],{},[34,1398,750],{}," Ploutos AI is an automated research tool. The analyses it produces are not personalised investment advice, do not consider your individual circumstances, and are not instructions to transact. You are solely responsible for any investment decision you make. Full disclosures at the end of this article.",[56,1401,1403],{"id":1402},"what-a-hallucination-looks-like-in-stock-analysis","What a hallucination looks like in stock analysis",[30,1405,1406],{},"In AI, a \"hallucination\" is a confident, fluent, plausible statement that simply is not true. In finance the failure is especially dangerous, because the output is full of exactly the specifics that make it look trustworthy:",[64,1408,1409,1416,1423,1429],{},[67,1410,1411,1412,1415],{},"A ",[34,1413,1414],{},"valuation multiple"," that is close to reality but quietly wrong, last year's P\u002FE, or a forward figure presented as trailing.",[67,1417,1418,1419,1422],{},"An ",[34,1420,1421],{},"insider transaction"," that never happened, or a real one with the direction flipped.",[67,1424,1411,1425,1428],{},[34,1426,1427],{},"catalyst"," lifted from an article that is two years old, described as if it were this week.",[67,1430,1411,1431,1434],{},[34,1432,1433],{},"cited source"," that does not exist, a report, a filing, an analyst note, fabricated wholesale because the sentence needed a citation to sound complete.",[30,1436,1437],{},"The unifying problem is that none of these are flagged as guesses. They sit in the same confident paragraph as the genuinely correct statements, and nothing in the text tells you which is which.",[56,1439,1441],{"id":1440},"why-it-happens-the-model-predicts-words-not-facts","Why it happens: the model predicts words, not facts",[30,1443,1444,1445,1448],{},"A large language model is, at its core, a very sophisticated next-word predictor. It has read an enormous amount of text and learned what ",[795,1446,1447],{},"tends to come next",". When you ask it for a company's free cash flow, it does not look up the number. It generates the most statistically plausible continuation of your question, and a specific-looking number is more plausible than \"I am not sure.\"",[30,1450,1451,1452,1455,1456,1459],{},"That is the whole trap. The model is optimised to be ",[795,1453,1454],{},"fluent",", and fluency rewards confident specifics. \"Its return on capital is around 14%\" reads better than \"I would need to check.\" So when the real figure is not reliably encoded in its training, the model does not stop, it produces a number that ",[795,1457,1458],{},"fits the shape"," of an answer. For casual writing that is fine. For an investment decision it is a landmine.",[30,1461,1462],{},"Two structural weaknesses make it worse:",[96,1464,1465,1471],{},[67,1466,1467,1470],{},[34,1468,1469],{},"Training data is frozen and fuzzy."," A model trained months ago has no idea what a company reported last week, and even older figures are blended across everything it ever read, not stored as a clean ledger.",[67,1472,1473,1476],{},[34,1474,1475],{},"The model wants to agree with itself."," Once it has written \"the bull case is strong\" in the opening, the rest of the answer tends to confirm that, not challenge it. This is confirmation bias, baked in.",[56,1478,1480],{"id":1479},"the-fix-part-one-do-not-ask-the-model-to-remember-make-it-fetch","The fix, part one: do not ask the model to remember, make it fetch",[30,1482,1483,1484,1487],{},"The single most important design decision in Ploutos AI is that ",[34,1485,1486],{},"the language model is never the source of a number."," Every figure that enters an analysis is fetched live, at the moment you run it, from a real source: fundamentals and prices, filings from SEC EDGAR for insider transactions and material events, news and sentiment feeds, and so on.",[30,1489,1490,1491,344],{},"The model's job is reframed from \"recall the facts\" to \"reason over facts I am handing you right now.\" That is a job language models are genuinely good at, weighing a return-on-capital figure against a sector average, noticing that free cash flow diverges from reported earnings, connecting an 8-K filing to a stated risk. The numbers are not its opinion, they are inputs it is not allowed to invent. And when the data simply is not there, we ",[123,1492,1493],{"href":813},"stop rather than fill the gap with a guess",[30,1495,1496,1497,344],{},"This is also why the work is split into stages rather than one giant prompt. Each stage has a narrow job grounded in specific data, which leaves far less room for the model to drift into invention. The full sequence is described in our ",[123,1498,1499],{"href":663},"walkthrough of the analysis pipeline",[56,1501,1503],{"id":1502},"the-fix-part-two-make-the-model-argue-against-itself","The fix, part two: make the model argue against itself",[30,1505,1506,1507,1510],{},"Grounding kills invented ",[795,1508,1509],{},"facts",". It does not, on its own, kill the second problem, the model talking itself into its own conclusion. For that we add a deliberately adversarial step.",[30,1512,1513,1514,1517],{},"After a verdict is formed, a separate and more capable model pass receives the picks with a single instruction: ",[34,1515,1516],{},"find what we got wrong."," It is told to behave like a hostile short-seller. For each idea it has to produce the weakest assumption in the thesis, a risk the first pass did not flag, a concrete bear case, and the specific observable event that would prove the thesis wrong.",[30,1519,1520],{},"This matters most exactly where confirmation bias is most dangerous: on the ideas that scored well. A tool that only ever tells you why an idea is good is not doing research, it is doing marketing. Forcing a structured rebuttal is the antidote.",[56,1522,1524],{"id":1523},"why-just-cite-your-sources-is-not-enough","Why \"just cite your sources\" is not enough",[30,1526,1527],{},"A common half-measure is to ask the model to cite sources. It helps with appearances and almost nothing else, because a model that will invent a P\u002FE will just as happily invent the citation next to it. A fabricated footnote is not a safeguard, it is a second hallucination wearing a suit.",[30,1529,1530],{},"The only reliable fix is architectural: the facts must come from outside the model and be verifiable, and the reasoning must be stress-tested by something whose job is to disagree. Citations are a presentation layer. Grounding is a plumbing layer. They are not substitutes.",[56,1532,220],{"id":219},[30,1534,1535,1536],{},"When you read an AI stock analysis, the right question is not \"does this sound smart?\" Fluency is free, and it is exactly what a hallucination is made of. The right questions are: ",[795,1537,1538],{},"where did each number come from, and what tried to prove this wrong?",[30,1540,1541,1542,1544,1545,344],{},"That is the bar we hold ourselves to. Numbers are fetched, not remembered. Conclusions are challenged, not just stated. And when the data is too thin to do either honestly, we say so. If you want to see the grounded pipeline produce a full analysis, you can ",[123,1543,215],{"href":214},", or read how the ",[123,1546,1547],{"href":663},"five stages fit together",[225,1549],{},[56,1551,851],{"id":850},[30,1553,854],{},[30,1555,857],{},[30,1557,860],{},[30,1559,863],{},[30,1561,866,1562,694],{},[123,1563,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":1565},[1566,1567,1568,1569,1570,1571,1572],{"id":1402,"depth":250,"text":1403},{"id":1440,"depth":250,"text":1441},{"id":1479,"depth":250,"text":1480},{"id":1502,"depth":250,"text":1503},{"id":1523,"depth":250,"text":1524},{"id":219,"depth":250,"text":220},{"id":850,"depth":250,"text":851},"A language model will happily invent a P\u002FE ratio or an insider trade that never happened. Here is why it happens, and how Ploutos AI prevents it.",[1575,1578,1581,1584],{"q":1576,"a":1577},"Why do AI stock tools invent figures?","A language model predicts the most likely next word, not the fact. When it doesn't reliably 'remember' a number, it produces one that looks right instead of saying 'I don't know'.",{"q":1579,"a":1580},"How is it prevented?","Numbers are fetched live from the official filings (grounding), not from the model's memory, and a separate pass challenges the conclusion.",{"q":1582,"a":1583},"Isn't it enough to 'cite sources'?","No. A model that will invent a P\u002FE will just as happily invent the citation next to it. Grounding has to be architectural, not cosmetic.",{"q":1585,"a":1586},"How do I know if an AI analysis is trustworthy?","Ask: where did each number come from, and what tried to prove it wrong? If the numbers have no verifiable source, treat them with caution.",{},"Why AI stock tools hallucinate",{"title":1375,"description":1573},"blog\u002Fen\u002Fwhy-ai-stock-tools-hallucinate",[900,901],"why-ai-stock-tools-hallucinate","OSgvQko9onLDKmYT3W43SiI7oRfW9cVxHwiVT3hS-DU",{"id":1595,"title":1596,"author":7,"body":1597,"date":878,"description":1773,"extension":259,"faq":1774,"featured":276,"mentionsTickers":276,"meta":1784,"metaTitle":1785,"navigation":279,"ogImage":1606,"path":813,"readMinutes":896,"seo":1786,"stem":1787,"tags":1788,"translationKey":1789,"__hash__":1790},"blogEn\u002Fblog\u002Fen\u002Fwhy-we-refuse-to-analyze-a-stock.md","Why we sometimes refuse to analyze a stock (and tell you instead)",{"type":9,"value":1598,"toc":1764},[1599,1607,1610,1613,1620,1624,1627,1634,1641,1648,1652,1658,1664,1670,1674,1677,1684,1691,1706,1710,1717,1720,1724,1727,1731,1738,1748,1750,1752,1754,1756,1758,1760],[12,1600,1602],{"className":1601},[15,16,17,18,19,20],[22,1603],{"alt":1604,"className":1605,"src":1606},"Three data-coverage tiers: full, partial, and insufficient",[26,27],"\u002Fblog\u002Fog-data-coverage.svg",[30,1608,1609],{},"There is a failure mode that almost every \"AI stock analyzer\" shares, and almost none of them admit to: when the underlying data is thin, they answer anyway.",[30,1611,1612],{},"Ask one of these tools about a tiny micro-cap, a freshly-listed company, or a foreign listing with sparse filings, and you will still get a confident verdict, a fair value, a score out of ten. It looks exactly like the verdict you would get for a household-name large cap. The difference is that one is built on real fundamentals and the other is built on blanks. You cannot tell which from the output, and that is the problem.",[12,1614,1616],{"className":1615},[15,16,41,42,43,19,44,45,46,47,48],[30,1617,1618,1399],{},[34,1619,750],{},[56,1621,1623],{"id":1622},"a-low-score-and-no-data-look-identical-but-they-are-not","A low score and \"no data\" look identical, but they are not",[30,1625,1626],{},"Our quality score rates a company against ten value-investing criteria: valuation versus its sector, revenue growth, gross margin, return on invested capital, free cash flow, balance-sheet strength, and so on. Each criterion either passes or fails, and the failures drag the score down.",[30,1628,1629,1630,1633],{},"Here is the subtle trap. If a company genuinely has a weak return on invested capital, that criterion fails and the score drops. But if we simply ",[795,1631,1632],{},"do not have"," the return-on-invested-capital figure, the most naive thing a scoring system can do is treat the missing value as a fail and drop the score in exactly the same way.",[30,1635,1636,1637,1640],{},"The result is a stock that ",[795,1638,1639],{},"looks"," like a mediocre business when the honest description is \"we do not have enough information to judge this business at all.\" A genuinely bad company and a company we know nothing about end up with the same low number. For a tool whose entire job is to help you tell good businesses from bad ones, that is not a small bug. It is a credibility problem.",[30,1642,1643,1644,1647],{},"So before anything else runs, we measure how much of the data we would need is actually present. We call this ",[34,1645,1646],{},"data coverage",", and it sorts every ticker you submit into one of three tiers.",[56,1649,1651],{"id":1650},"the-three-tiers-of-data-coverage","The three tiers of data coverage",[30,1653,1654,1657],{},[34,1655,1656],{},"Full."," We have the company's price, its share count, and most of the core fundamentals a valuation needs: earnings, margins, return on capital, cash flow, revenue, and a usable balance sheet. This is the normal case for established, well-covered companies. We proceed silently, exactly as you would expect.",[30,1659,1660,1663],{},[34,1661,1662],{},"Partial."," The essentials are there, but several core fundamentals are missing or the company is not yet in a state where a valuation model can produce a meaningful number, for example a business that is not yet profitable and has no positive free cash flow to discount. We can still run the analysis, but the verdict will rest on less. So we tell you that, show you the trade-offs, and let you decide whether to spend an analysis on it.",[30,1665,1666,1669],{},[34,1667,1668],{},"Insufficient."," The data is too thin to support a fundamentals verdict at all: no usable price or share count, a feed error, or only a handful of the core metrics present. This is the tier where most tools would quietly produce a number anyway. We do not. We stop and tell you what we found.",[56,1671,1673],{"id":1672},"what-enough-data-actually-means","What \"enough data\" actually means",[30,1675,1676],{},"Coverage is not a vague feeling, it is a count. We look for two things.",[30,1678,1679,1680,1683],{},"First, the ",[34,1681,1682],{},"critical inputs",": a current price and a share count. Without these, almost nothing downstream works, you cannot compute a per-share value or a margin of safety, so a verdict would be meaningless.",[30,1685,1686,1687,1690],{},"Second, the ",[34,1688,1689],{},"core fundamentals",", the eight figures that actually drive a value verdict: trailing earnings, gross margin, return on invested capital, free cash flow, revenue and its growth, the balance sheet, and the price-to-earnings ratio. The more of these are missing, the less any verdict can be trusted. We also check whether at least one valuation method can run at all, which needs either positive earnings or positive free cash flow to work with.",[30,1692,1693,1694,1697,1698,1701,1702,1705],{},"Importantly, this is a measurement of ",[795,1695,1696],{},"presence",", not a judgement of ",[795,1699,1700],{},"quality",". A company can have full coverage and still score poorly, that is a real, useful answer. What coverage protects against is the opposite case: a confident answer built on absence. If you want to see what the full pipeline does once the data clears this bar, we wrote a ",[123,1703,1704],{"href":663},"walkthrough of how Ploutos AI analyzes a stock"," end to end.",[56,1707,1709],{"id":1708},"why-we-check-this-before-charging-you-anything","Why we check this before charging you anything",[30,1711,1712,1713,1716],{},"The coverage check runs ",[795,1714,1715],{},"before"," an analysis is counted against your plan, and that ordering is deliberate. If a ticker is too thin to analyze honestly, we would rather spend zero of your searches on it than hand you a hollow report and quietly tick the counter down.",[30,1718,1719],{},"There is a cost on our side too, every analysis runs a multi-stage pipeline that calls a language model and a stack of data services, and burning that on a ticker we cannot do justice to is wasteful for everyone. But the user-facing reason is the one that matters: a search you spend should buy you something worth having.",[56,1721,1723],{"id":1722},"what-happens-when-a-ticker-is-flagged","What happens when a ticker is flagged",[30,1725,1726],{},"When coverage comes back partial or insufficient, you get a short, honest prompt instead of a redirect into a misleading report. It tells you what we actually have, weighs the upside of proceeding against the downside, and gives you three choices: run it anyway with your eyes open, drop the thin tickers and analyze only the ones with enough data, or step back and pick a different name. If you do proceed on partial data, the resulting analysis carries that warning forward, so the verdict is never dressed up as more certain than it is.",[56,1728,1730],{"id":1729},"why-this-is-a-feature-not-a-limitation","Why this is a feature, not a limitation",[30,1732,1733,1734,1737],{},"It is tempting to think that a tool which always has an answer is more powerful than one that sometimes says \"not enough to go on.\" The opposite is true. The willingness to say ",[795,1735,1736],{},"I do not know"," is exactly what separates a research process from a guessing machine. Value investing runs on the same principle, Warren Buffett's \"circle of competence\" is just a disciplined way of refusing to act where you lack the information to act well.",[30,1739,1740,1741,1744,1745,1747],{},"A verdict you can trust on the companies where the data is real is worth far more than a verdict on everything, because the second kind teaches you to ignore the warning labels. When Ploutos AI does give you a full analysis, you can know that it cleared this bar first. When it declines, that is information too. You can read about what we do with a full, clean dataset in our ",[123,1742,1743],{"href":663},"breakdown of how the analysis pipeline works",", or ",[123,1746,668],{"href":214}," and see the coverage check in action.",[225,1749],{},[56,1751,851],{"id":850},[30,1753,854],{},[30,1755,857],{},[30,1757,860],{},[30,1759,863],{},[30,1761,866,1762,694],{},[123,1763,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":1765},[1766,1767,1768,1769,1770,1771,1772],{"id":1622,"depth":250,"text":1623},{"id":1650,"depth":250,"text":1651},{"id":1672,"depth":250,"text":1673},{"id":1708,"depth":250,"text":1709},{"id":1722,"depth":250,"text":1723},{"id":1729,"depth":250,"text":1730},{"id":850,"depth":250,"text":851},"Incomplete data produces a confident but misleading verdict. Here is how Ploutos AI checks data coverage before spending your analysis, and when it stops.",[1775,1778,1781],{"q":1776,"a":1777},"Why does it sometimes refuse to analyze a stock?","When the available data is too thin for a reliable analysis, we stop rather than fill the gap with guesswork.",{"q":1779,"a":1780},"What counts as 'thin data'?","For example incomplete filings, a very recent IPO, or a ticker outside our coverage.",{"q":1782,"a":1783},"Isn't it better to always give an answer?","No. A confident answer built on missing data is worse and more dangerous than an honest 'there isn't enough information'.",{},"Why we refuse to analyze a stock",{"title":1596,"description":1773},"blog\u002Fen\u002Fwhy-we-refuse-to-analyze-a-stock",[900,901],"why-we-refuse-to-analyze-a-stock","1O1dM_dqeusYa6roV8eMgGDLwNku4Jswqpu4BnNH9so",{"id":1792,"title":1793,"author":7,"body":1794,"date":2222,"description":2223,"extension":259,"faq":2224,"featured":279,"mentionsTickers":276,"meta":2237,"metaTitle":2238,"navigation":279,"ogImage":1803,"path":663,"readMinutes":500,"seo":2239,"stem":2240,"tags":2241,"translationKey":2243,"__hash__":2244},"blogEn\u002Fblog\u002Fen\u002Fhow-ploutos-analyzes-a-stock.md","How Ploutos AI analyzes a stock in 4 stages (and one Devil's Advocate)",{"type":9,"value":1795,"toc":2211},[1796,1804,1807,1810,1817,1821,1824,1838,1841,1845,1848,1862,1962,1965,1969,1972,1983,1986,1990,1997,2041,2044,2048,2051,2083,2086,2090,2093,2100,2132,2135,2139,2142,2162,2166,2169,2186,2189,2191,2193,2195,2197,2199,2201,2207],[12,1797,1799],{"className":1798},[15,16,17,18,19,20],[22,1800],{"alt":1801,"className":1802,"src":1803},"Diagram of the Ploutos AI 5-stage analysis pipeline",[26,27],"\u002Fblog\u002Fog-pipeline.svg",[30,1805,1806],{},"Most tools that promise \"AI stock analysis\" do roughly the same thing. They paste your ticker into a large language model and hand you back whatever comes out. It looks smart. It reads like a research report. And often, when you look closely, the numbers are made up, the cited sources don't exist, and the conclusion contradicts a sentence written three paragraphs earlier.",[30,1808,1809],{},"Ploutos AI is built around the opposite assumption: a language model alone is not a research analyst. It needs structure, real data, and (most importantly) something to push back against its own conclusion. That is why every analysis you run goes through the same five stages, in the same order, with the same discipline. This article walks through what is happening behind the spinner.",[12,1811,1813],{"className":1812},[15,16,41,42,43,19,44,45,46,47,48],[30,1814,1815,1399],{},[34,1816,750],{},[56,1818,1820],{"id":1819},"why-a-pipeline-instead-of-one-big-prompt","Why a pipeline instead of one big prompt",[30,1822,1823],{},"A single LLM call has two failure modes that are hard to fix from inside the prompt:",[96,1825,1826,1832],{},[67,1827,1828,1831],{},[34,1829,1830],{},"It hallucinates specifics",": a P\u002FE ratio that does not match reality, an insider transaction that never happened, a sector rotation that ended last quarter.",[67,1833,1834,1837],{},[34,1835,1836],{},"It confirms its own thesis",": once it has written \"the case for buy\" in paragraph one, paragraph four will rarely call it wrong.",[30,1839,1840],{},"Splitting the work into stages, with each stage given a narrow job and each grounded in actual data fetched live from the public-domain stack we ship today (SEC EDGAR XBRL for fundamentals, FRED for macro and FX, FINRA for short interest, Marketaux for news), addresses the first problem. A separate, hostile critique pass at the end addresses the second. Below are the five stages in order.",[56,1842,1844],{"id":1843},"stage-1-screen-macro-regime-fundamentals","Stage 1: Screen (macro regime + fundamentals)",[30,1846,1847],{},"The first thing the agent does is fire two calls in parallel:",[64,1849,1850,1856],{},[67,1851,1852,1855],{},[34,1853,1854],{},"Macro regime check",": current VIX level, yield curve, market trend, central bank stance. This shapes how every later decision is weighted (a stock that scores well in a bull market scores differently in a stagflation regime).",[67,1857,1858,1861],{},[34,1859,1860],{},"Fundamentals pull",": for each ticker you submitted, the agent retrieves the data needed to score it against 10 sector-aware quality criteria:",[1863,1864,1865,1878],"table",{},[1866,1867,1868],"thead",{},[1869,1870,1871,1875],"tr",{},[1872,1873,1874],"th",{},"Criterion",[1872,1876,1877],{},"What it checks",[1879,1880,1881,1890,1898,1906,1914,1922,1930,1938,1946,1954],"tbody",{},[1869,1882,1883,1887],{},[1884,1885,1886],"td",{},"P\u002FE vs sector",[1884,1888,1889],{},"Is the valuation reasonable relative to peers?",[1869,1891,1892,1895],{},[1884,1893,1894],{},"Revenue growth (5y CAGR)",[1884,1896,1897],{},"Is the top line actually growing?",[1869,1899,1900,1903],{},[1884,1901,1902],{},"Gross margin vs sector",[1884,1904,1905],{},"Does the business have pricing power?",[1869,1907,1908,1911],{},[1884,1909,1910],{},"EPS positive and growing",[1884,1912,1913],{},"Profitability and trajectory",[1869,1915,1916,1919],{},[1884,1917,1918],{},"Assets\u002FLiabilities > 1",[1884,1920,1921],{},"Solvent balance sheet",[1869,1923,1924,1927],{},[1884,1925,1926],{},"ROIC vs sector",[1884,1928,1929],{},"Capital efficiency",[1869,1931,1932,1935],{},[1884,1933,1934],{},"Free cash flow trend",[1884,1936,1937],{},"Is real cash being generated?",[1869,1939,1940,1943],{},[1884,1941,1942],{},"Debt coverage over 10y",[1884,1944,1945],{},"Can it service its debt across cycles?",[1869,1947,1948,1951],{},[1884,1949,1950],{},"Buybacks (share count)",[1884,1952,1953],{},"Returning capital or diluting?",[1869,1955,1956,1959],{},[1884,1957,1958],{},"FCF\u002FDividend ratio",[1884,1960,1961],{},"Is the dividend covered?",[30,1963,1964],{},"Each criterion passed or failed contributes to a score from 0 to 10. This score is not a verdict; it is a filter. It tells the next stage which tickers are worth deep research and which are not.",[56,1966,1968],{"id":1967},"stage-2-context-sector-news-macro-overlay","Stage 2: Context (sector news + macro overlay)",[30,1970,1971],{},"A high fundamental score does not mean much if the sector is being repriced this week. Before any deep work, the agent uses a real-time web search to surface recent sector-wide events:",[64,1973,1974,1977,1980],{},[67,1975,1976],{},"Regulatory changes affecting the industry",[67,1978,1979],{},"Interest rate impacts on cyclicals vs defensives",[67,1981,1982],{},"Industry-specific macro trends (chip cycle, energy supply, retail spending)",[30,1984,1985],{},"If something material has shifted, the agent re-ranks the candidates from Stage 1. A perfectly-fundamented company in a sector that just lost its biggest customer is not the same opportunity it was last month.",[56,1987,1989],{"id":1988},"stage-3-deep-research-parallel-data-pull-per-ticker","Stage 3: Deep research (parallel data pull per ticker)",[30,1991,1992,1993,1996],{},"This is where the heavy lifting happens. For each ticker that made it through, the agent fires seven independent data calls ",[34,1994,1995],{},"in parallel",":",[96,1998,1999,2005,2011,2017,2023,2029,2035],{},[67,2000,2001,2004],{},[34,2002,2003],{},"Valuation models",": a 4-method ensemble, DCF, sector multiples, EPV (Earnings Power Value), and the Graham Number, with confidence ranges.",[67,2006,2007,2010],{},[34,2008,2009],{},"News sentiment",": bullish vs bearish tilt relative to the sector, plus buzz level.",[67,2012,2013,2016],{},[34,2014,2015],{},"Earnings surprises",": beats, misses, and revisions over the last four quarters (execution quality).",[67,2018,2019,2022],{},[34,2020,2021],{},"Insider transactions",": what executives are actually doing with their personal money over the last 6 months.",[67,2024,2025,2028],{},[34,2026,2027],{},"Recent SEC filings",": material events from 8-K filings (M&A, restatements, cyber incidents, executive changes).",[67,2030,2031,2034],{},[34,2032,2033],{},"Institutional holdings",": what tracked smart-money investors are accumulating or selling.",[67,2036,2037,2040],{},[34,2038,2039],{},"Short interest",": bear thesis check; high short interest with weak fundamentals is a red flag.",[30,2042,2043],{},"These come back, and the model synthesises a thesis covering: which fundamentals are working and which are not, where the price sits versus fair value, whether insiders and institutions agree with the thesis, and what material events might be coming.",[56,2045,2047],{"id":2046},"stage-4-synthesis-structured-output","Stage 4: Synthesis (structured output)",[30,2049,2050],{},"The synthesis becomes a structured output you would recognise as a PickCard in the app:",[64,2052,2053,2059,2065,2071,2077],{},[67,2054,1411,2055,2058],{},[34,2056,2057],{},"model rating",": one of six tiers from Strong Outperform to Strong Underperform. This is the relative language a sell-side analyst would use to describe a stock against its peer companies. It is the model's analytical view at a point in time, not a personal recommendation to buy or sell, and it does not take your circumstances into account.",[67,2060,2061,2064],{},[34,2062,2063],{},"Margin of Safety",": the percentage gap between the current market price and the midpoint of the model's fair-value range. A discipline metric showing how much room the price has before reaching the model's estimated fair value, not a price target.",[67,2066,2067,2070],{},[34,2068,2069],{},"Conditions to watch",": observable factors the model highlights, for example macroeconomic conditions that would strengthen the thesis or price ranges where its valuation models would give the position more headroom. These are reference points the user can monitor, not instructions to transact.",[67,2072,2073,2076],{},[34,2074,2075],{},"Key risk and catalyst",": what could invalidate the thesis, what could accelerate it.",[67,2078,2079,2082],{},[34,2080,2081],{},"Insider, institutional, and short-interest data points",": one-line summaries distilled from the underlying filings.",[30,2084,2085],{},"Every user-submitted ticker gets one entry in this output, even those that score poorly. The agent is not allowed to silently drop a ticker. If the model rating is \"Underperform\", that is what the model says.",[56,2087,2089],{"id":2088},"stage-5-devils-advocate-the-part-most-tools-skip","Stage 5: Devil's Advocate (the part most tools skip)",[30,2091,2092],{},"This is the stage that, in my opinion, makes the difference between research and recommendation.",[30,2094,2095,2096,2099],{},"After the verdict is formed, a separate model pass (a more capable one) gets the picks and one instruction: ",[34,2097,2098],{},"find what we got wrong",". For each pick it returns:",[64,2101,2102,2108,2114,2120,2126],{},[67,2103,2104,2107],{},[34,2105,2106],{},"Robustness score"," (1 to 10): how resilient is this thesis to challenge?",[67,2109,2110,2113],{},[34,2111,2112],{},"Weakest assumption",": the single assumption most likely to be wrong.",[67,2115,2116,2119],{},[34,2117,2118],{},"Overlooked risk",": a real risk the main analyst did NOT flag.",[67,2121,2122,2125],{},[34,2123,2124],{},"Bear case summary",": how does this thesis go to zero or underperform by 30%+?",[67,2127,2128,2131],{},[34,2129,2130],{},"Invalidates thesis if",": a concrete observable signal that would force exiting the position.",[30,2133,2134],{},"For positive verdicts this matters most; it is the structured antidote to AI confirmation bias. For negative verdicts the critique is collapsed by default in the UI, because piling more bad news onto an already-negative thesis is just noise.",[56,2136,2138],{"id":2137},"what-you-actually-see-at-the-end","What you actually see at the end",[30,2140,2141],{},"The whole pipeline takes about 30 to 50 seconds for a single ticker in a warm path. What lands on your screen is:",[64,2143,2144,2150,2156],{},[67,2145,1411,2146,2149],{},[34,2147,2148],{},"PickCard"," with the model rating, margin-of-safety metric, conditions to watch, all the data points, and (for positive ratings) an expanded Devil's Advocate critique.",[67,2151,1411,2152,2155],{},[34,2153,2154],{},"Top Picks tab"," summarising the ratings across all submitted tickers.",[67,2157,1411,2158,2161],{},[34,2159,2160],{},"Chat"," where you can ask the agent follow-up questions and it has the full pipeline output as context. \"What if rates stay above 5%?\" \"How does this compare to similar companies?\" \"What changed in their last earnings call?\"",[56,2163,2165],{"id":2164},"why-this-matters-for-value-investing","Why this matters for value investing",[30,2167,2168],{},"Value investing is not about predicting next quarter. It is about discipline: knowing what you own, knowing what could go wrong, refusing to confuse a story for a thesis. Every stage in the pipeline is built around that discipline:",[64,2170,2171,2174,2177,2180,2183],{},[67,2172,2173],{},"Stage 1 says: do not waste time on companies that fail the basic quality screen.",[67,2175,2176],{},"Stage 2 says: the present matters, do not analyse last year's company.",[67,2178,2179],{},"Stage 3 says: ground every claim in actual data.",[67,2181,2182],{},"Stage 4 says: be honest about what you see, even if the conclusion is uncomfortable.",[67,2184,2185],{},"Stage 5 says: assume you might be wrong, and look for the evidence that would prove it.",[30,2187,2188],{},"You still make the final decision. Ploutos AI is a research tool, not an advisor. It compresses what would take hours of manual data-gathering and cross-referencing into about a minute. Whether the model's view matches your own conviction is up to you.",[225,2190],{},[56,2192,851],{"id":850},[30,2194,854],{},[30,2196,857],{},[30,2198,860],{},[30,2200,863],{},[30,2202,2203,2206],{},[34,2204,2205],{},"Conflicts of interest",": Ploutos AI does not receive commissions, kickbacks, or inducements from brokers, exchanges, asset managers, or issuers in connection with the analyses it produces. Operators of Ploutos AI may, from time to time, hold positions in securities the system analyses. Where this is material to a given analysis, it is disclosed alongside the analysis.",[30,2208,866,2209,694],{},[123,2210,243],{"href":242},{"title":246,"searchDepth":247,"depth":247,"links":2212},[2213,2214,2215,2216,2217,2218,2219,2220,2221],{"id":1819,"depth":250,"text":1820},{"id":1843,"depth":250,"text":1844},{"id":1967,"depth":250,"text":1968},{"id":1988,"depth":250,"text":1989},{"id":2046,"depth":250,"text":2047},{"id":2088,"depth":250,"text":2089},{"id":2137,"depth":250,"text":2138},{"id":2164,"depth":250,"text":2165},{"id":850,"depth":250,"text":851},"2026-05-24","From screening to bear-case stress test, the full pipeline that runs every time you submit a ticker, explained without jargon.",[2225,2228,2231,2234],{"q":2226,"a":2227},"How does Ploutos AI analyze a stock?","In stages: screening, gathering data from filings, synthesising a structured thesis, and a separate Devil's Advocate pass that looks for what could go wrong.",{"q":2229,"a":2230},"Where does the data come from?","From official sources (SEC EDGAR filings, market data), with a source on every claim, not from a language model's 'memory'.",{"q":2232,"a":2233},"How long does an analysis take?","Usually a few minutes. The mechanical part (gathering and checking data) is automated.",{"q":2235,"a":2236},"Is it investment advice?","No. It's research and education, not personalised advice. You are solely responsible for your decisions.",{},"How Ploutos AI analyzes a stock",{"title":1793,"description":2223},"blog\u002Fen\u002Fhow-ploutos-analyzes-a-stock",[900,2242,901],"how-to","how-ploutos-analyzes-a-stock","ASM4-ZkvfUeCKR0vVlStjkZVNunyEdMec9IY0wZQiI0"]