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founder of finance academy ||| explaining complex finance world in simple terms
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A dead MIT professor accidentally destroyed the $20 billion executive coaching industry with one hour of lecture, and ten million people have already watched him do it.
He filmed it once in January 2018 and died eighteen months later.
Executive coaches charge fifteen thousand dollars a session to teach a third of what he covered in that one hour for free.
His name was Patrick Winston. He ran the MIT Artificial Intelligence Laboratory from 1972 to 1997 and wrote the AI textbook every computer science major in the world read for thirty years.
Every January for four decades, he gave a lecture called "How to Speak."
His entire framework fits on a napkin.
Do not read. Be in the image. Keep images simple. Eliminate clutter. Start with an empathetic connection. End with a punch line the audience can repeat over dinner. Never open with a joke. Never end with "thank you."
That last rule alone has probably cost the executive coaching industry a hundred million dollars.
"Your success in life will be determined largely by your ability to speak, your ability to write, and the quality of your ideas. In that order."
That is the actual opening line of the lecture. Winston believed it strongly enough to spend fifty years teaching computer scientists how to talk.
Founders spend $80,000 on an MBA and then hire a communications coach to teach them the same material Winston filmed once for free. Engineers write brilliant code and lose promotions to teammates who watched this lecture on the train.
The lecture is free on MIT OpenCourseWare. The textbook is free on his page.
Winston died in 2019. Almost none of the ten million viewers have actually implemented the four rules on the napkin.
The napkin is free. The willingness to actually use it in your next meeting is the entire edge.
you can play the same two cards perfectly twice and be wrong both times, your stack decided the answer.
kevin desmond teaches this at mit sloan, course 15.s50, free on mit ocw.
the m-ratio is your stack divided by one round of blinds and antes, a chip count turned into a countdown of rounds you can survive.
then the impossible part: above an m of 20 you play any style, below 10 hands you'd normally fold become forced all-ins, the correct play flips, cards unchanged.
then the collapse: below an m of 1, harrington calls it dead, the blinds already decided for you, the move is shove.
then the transfer: whatever stack he's sitting on puts him in one of these zones, and the zone decides which hands are worth playing before his cards.
watch the moment he shows the same cards, a fold in one zone, a shove in another.
after this, a stack size is a countdown, not a number on the screen.
The week Lehman Brothers collapsed, an MIT professor walked into class and put its 2007 annual report on the screen.
$19 billion in revenue. $4 billion in profit. $145 billion in capital. 28,500 employees.
Nine months later, it was gone.
His explanation didn't start with Wall Street. It started with his own house.
In 1988 he bought his first home with just 5% down, which is 20-to-1 leverage. "I beat Lehman Brothers." (Lehman ran at about 16 to 1.)
Here's the math that sinks them both:
- Put 20% down and prices fall 10%: half your money is gone
- Put 5% down and prices fall 10%: all of it is gone, and you still owe more
Leverage isn't dangerous on its own. It becomes dangerous when prices stop moving smoothly. For years housing only went up, so nobody felt the risk. Then volatility arrived.
The lesson: before you borrow, don't ask how much prices usually move. Ask how much they could.
A $100 bet on red in American roulette has an expected value of -$5.26. Bet it every night for a year and your expected loss is about $1,920. Yet the casino has almost zero chance of losing. Here's the math that makes gambling a business and not a game
An American wheel has 38 pockets: 18 red, 18 black, 2 green.
Bet $100 on red:
- Win $100 with probability 18/38 (47.4%)
- Lose $100 with probability 20/38 (52.6%)
Expected value = (18/38 x $100) - (20/38 x $100) = -$5.26 per spin.
Those two green pockets are the entire business model.
Now look at it from both sides of the table.
You, one spin a night for a year (365 spins):
Expected loss: $1,920
Typical swing: about +-$1,900
So you still have about a 1 in 6 chance of finishing the year ahead. Your luck is still bigger than the edge against you.
The casino, 1 million spins a year:
Expected profit: $5.26 million
Typical swing: about +-$100,000
The edge is 50 times bigger than the noise, so the casino's chance of a losing year is effectively zero.
Same bet, same odds. The difference is volume.
That's the law of large numbers: randomness averages out, and the edge doesn't. The more times you repeat a bet, the more the result converges to its expected value.
The lesson isn't "never gamble." It's this:
Always ask which side of the edge you're on.
If the edge is against you, repetition guarantees you lose.
If the edge is for you, like owning a diversified slice of the economy for decades, repetition makes you the casino.
This MIT lecture covers the math behind it: random variables, distributions, and the Central Limit Theorem 🎥
A stock that goes up 50% then down 50% leaves you with 75 dollars out of every 100. The average return is 0%. You lost 25%.
This isn't a trick. It's how compounding works, and it quietly eats returns in every portfolio.
Gains and losses don't cancel out, because each one is applied to a different starting amount. The 50% gain is on 100 dollars. The 50% loss is on 150 dollars.
That's why losses need bigger gains to recover:
- Lose 20%, you need +25% to get back
- Lose 33%, you need +50%
- Lose 50%, you need +100%
Now take two portfolios, both averaging 10% a year:
A gains 10% every year. After 10 years, 100 dollars becomes 259.
B alternates +30% and -10%. Same 10% average. After 10 years, 100 dollars becomes 219.
Same average, 40 dollars less. B's real compounded return is about 8.2% a year, not 10%.
There's a simple rule of thumb for the gap:
compounded return ≈ average return − (volatility² ÷ 2)
B swings 20% around its average. 20% squared is 4%, half of that is 2%. So 10% becomes roughly 8%. The math checks out.
The average return tells you what a typical year looks like. The compounded return tells you how much money you actually end up with. Most return charts show you the first one.
This is also why leveraged ETFs bleed in choppy markets. If an index goes +10% then -10%, it's down 1%. A 3x fund goes +30% then -30% and is down 9%.
The takeaway: two investments with the same average return are not the same investment. Lower the swings without lowering the average, and you end up with more money. That's the whole case for diversification.
A 2 dollar lottery ticket with a 1 in 300 million chance of a 500 million dollar payout has an expected value of negative 33 cents. A 30 thousand dollar car insured against theft in a neighborhood where 1 in 200 cars is stolen a year is worth positive 150 dollars in expected value.
The math to compute either one takes 4 seconds. Almost no one runs it.
Andrew Lo has been teaching Session 1 of MIT 15.401 since 2003. The Fall 2008 recording sits free on MIT OpenCourseWare. Every decision his students will ever make, from a stock trade to a job offer to which route to drive home, reduces to the same 4-second calculation. Expected value equals probability times payoff.
Institutional desks run it before every trade. Retail investors run it before none. The gap between them has a name and it is not luck.
The math is free. The willingness to run it before you sign is the entire fortune.
Claude Shannon ran his personal stock account at 28% a year for 30 years. He's also the man who mathematically proved the ceiling above every filter the thread above is selling.
Both facts have been sitting in the same library since 1948.
Shannon didn't beat the market with a smarter moving average. He didn't beat it with a swarm, a neural net, or the sharpest filter of his generation, and he could have built any of them in an afternoon. He beat it because he understood the one thing the industry has been quietly ignoring for 78 years: no filter, no matter how clever, can pull more signal from a channel than the channel actually holds.
The market channel is almost pure noise by design. Every real edge gets arbitraged toward zero the moment enough people find it. A better filter doesn't create signal that wasn't there - it rounds noise into a shape that fools you into betting on it.
Shannon compounded like that because he was ruthless about which channels still had signal left, and disciplined about how much to bet when they did. The filter came last. It always comes last.
Build the filter. It's a fine tool. Just remember there's a ceiling above it no engineering can lift, and the part that finds signal before it decays - that part, you still have to bring yourself.
Shannon wrote it down in 1948. It's still free. The lesson has been sitting there for 78 years.
Harvard needs 8% return every year just to keep the lights on. 5% spending plus 3% inflation. Miss that number and buildings stop, professors leave, research dies. 40% of the operating budget comes from one portfolio.
Not tuition.Not grants. One fund. Jake Xia manages that fund's public markets. He also teaches the math behind it at MIT for free.
One of the top five most-watched courses on OpenCourseWare. Millions of views. Almost nobody changed how they invest. Every year he hands students a blank page. Build a portfolio.
No rules.Someone writes 100% Apple. Someone writes rare coins. Confident picks. Same blind spot, every time. Not one student asks the only question that matters: how much goes in each position.
They all pick what to buy. Nobody sizes it. Sizing is the entire job. The answer won the Nobel Prize. It's called the efficient frontier. Xia draws it on the board in under a minute.
Five equations sit underneath it. Compound growth. Present value. The geometric mean. The Rule of 72. Real return. All older than any bank on earth. All fit on a napkin. None behind a paywall.
A "guaranteed 5% bond" during 4% inflation is a 1% return. The industry doesn't hide this. It just hopes you never run the equation yourself. The lecture is free. The napkin is free.
The only thing that costs anything is not knowing The answer is in this video.
This man teaches at a community college in California.
His salary: around $800,000 a year.
The engineers who passed calculus because of him: $1,800,000 to start.
He has more calculus students than Harvard, MIT, and Stanford combined.
This is Professor Leonard's Calculus 2, Lecture 6.2. Free on YouTube.
Professor Leonard has taught calculus on YouTube for over a decade. His channel has millions of subscribers across 150 countries. Every major university has students who watch him the night before their exam.
Then the concept.
An inverse function is a machine that undoes another machine. If a function takes 2 and gives you 8, the inverse takes 8 and gives you back 2. Finding an inverse means switching every x and y in the equation and solving for y again. The graph flips across the line y = x like a mirror.
Then the problem.
Sometimes it is easy to find the inverse. Sometimes it is impossible to write it explicitly. A function like 3π sin x + sin x cannot be solved for x with algebra. You have to think. What angle makes the whole thing equal to 1? You work backwards through the unit circle until the answer appears.
Then the shortcut.
If you want the derivative of an inverse at a point, you do not need the inverse itself. You only need the derivative of the original function. The formula: the derivative of the inverse at a point equals 1 divided by the derivative of the original function evaluated at the switched point. The inverse flips the coordinates, so you flip where you plug in.
Watch the moment he shows why G prime of 8 equals 1/12 without ever writing the inverse function.
Every engineering student memorizes the derivative rules. Professor Leonard's lecture is the one that shows why the inverse derivative formula is just those same rules run backwards.
A software engineer at a semiconductor company in Austin said Professor Leonard's channel is the reason she passed Calculus 2 on her second attempt. She graduated, joined the company, and now makes $165,000 a year.
Bookmark this and watch later - after this lecture every inverse problem on your exam will feel like a question you already answered.
WARREN BUFFETT PUT $13 MILLION INTO A COMPANY ACCUSED OF FRAUD, NOW WORTH $50 BILLION
and wall street was already dumping the stock when he decided to buy.
in 1964 american express admitted a subsidiary had been caught in a fraud so large nobody could say yet what it would cost. the stock fell from $60 to $35 in months.
warren buffett put $13 million into it anyway, close to 40% of his partnership's capital, while most of wall street would not touch the name.
he drove around omaha himself, checking diners and gas stations to see whether people were still handing over their american express cards. they were.
[[QUOTE PENDING FOOTAGE CONFIRMATION, SEE VIDEO BLOCK]]
the position kept compounding for decades inside berkshire hathaway. that stake alone is worth roughly $50 billion today.
most people sell the moment a stock is in the news for the wrong reason. the $13 million he refused to sell is worth more than most people will ever earn.
MICHAEL BURRY MADE $725 MILLION SHORTING HOUSING WHILE HIS OWN INVESTORS TRIED TO PULL OUT
some threatened to sue him, and he refused to close the position before it paid off.
by 2005 he had moved his fund into a bet that the housing market would collapse, years before anyone agreed with him.
his own investors turned on him first. by december 2006 he was closing his hong kong office and cutting staff while an angry crowd of them demanded their money back and threatened lawsuits.
he considered liquidating the fund at what he called the worst possible moment, with the crash still more than a year away.
he held the position anyway. by the end of 2007 the fund had made $725 million, by his own count.
"we were threatened with lawsuits, and i had to consider liquidation of the fund, at the worst possible time."
everyone says they would hold a position under that kind of pressure. most people fold the moment their own investors turn against them.
George Soros made a 1 billion dollars in a trade against the bank of england in 1992, five years after his fund gave back a 60% gain in a single week during the 1987 crash.
soros calls this reflexivity, laid out in a filmed lecture at central european university.
a widely believed story can change behavior enough to briefly make itself true, whether or not it was ever accurate.
the theory behind his billion dollar trade also explains his 1987 losses, because reflexivity describes how a story moves a market, never whether it's true, and he sat on both sides five years apart.
the last time a story convinced you a market had to move, how did you know it wasn't your own conviction talking?
Michael Saylor turned $250 million into 21,454 bitcoin in one announcement on august 11, 2020, a bet no other public company was willing to make.
he didn't stop there. four months later he raised $650 million in debt and bought 29,646 more bitcoin with it, then kept doing that for years, borrowing and selling new stock to buy even more, again and again.
the part people copy is buy bitcoin and hold forever. what built the fortune is a public company's power to borrow against a rising asset and sell stock to buy more, a machine not sitting in the account of whoever's watching the interview.
if you'd bought his bitcoin with your own cash, could you have kept adding every time it dropped?
Sam Zell bought distressed real estate for a dollar down after the 1973 crash, then sold what he built for 39 billion dollars.
he offered banks holding busted buildings a deal, take the losses for equity. nobody else could touch it, nobody else had a banker willing to lend. that became equity office properties, sold to blackstone in 2007.
buy when everyone else is broke is real advice, and it is being given by one of the only people who actually had a banker willing to lend when credit vanished. almost nobody repeating it today has that part, the actual ability to act on it.
next time credit disappears and everything is cheap, will you actually have the cash, or just the quote?
paul tudor jones made $100 million in a single day during the 1987 crash, after predicting the exact kind of decline on camera before it hit.
pbs aired it once in 1987, then he spent decades keeping it out of sight.
"there will be some type of a decline, without a question, in the next 10, 20 months. it will be earth-shaking."
"don't ever feel that you are very good. the second you do, you are dead."
he never says how long that fear lasted.
The man who wrote rich dad poor dad in 1997 just said he is 1.2 billion dollars in debt, and he says that was the plan.
robert kiyosaki built most of it inside llcs with partners across about 1,500 apartment units, not on his personal balance sheet, and he hasn't said how much he personally guaranteed. he says borrowing against real estate lets him skip income tax on the cash he pulls out.
his good debt rule gets repeated like a fact anyone can use safely, and it isn't. it was written by a man who can let one llc fail without touching the rest of his life, and most readers repeating it back cannot.
if the entity holding your good debt failed tomorrow, what would you still personally owe?
The man who is estimated to have saved ordinary investors over $1 trillion in fees died with a fortune estimated at $80 million.
vanguard is owned by its own funds, owned by the people invested in them, not by bogle, so no parent company skims a margin off the expense ratio.
"i'm an ordinary guy just trying to do my best for investors and who gave a damn about investors."
the story gets told as a saint choosing to give it away, but he made one legal choice, decades ago, that took the choice out of his own hands for good, and that is rarer and less flattering than ongoing generosity.
if the structure had let you keep every dollar you saved other people, would you have built it this way.
a friend who works in adtech sent me a lecture last week and said it's the reason every ad auction online looks the way it does.
stanford, cs364a, algorithmic game theory, taught by tim roughgarden, free on youtube since 2013.
about a third of the way through, he walks through the vickrey auction, the winner pays not what they bid, but the second-highest bid in the room. bidders end up with no reason to lie about what something is actually worth to them, so honesty becomes the easiest strategy.
google runs a version of exactly this on every search result page, and it pulled in $294.69 billion in ad revenue in 2025 alone.
In 1986 a guy got kicked out of every casino in Vegas for counting cards. So he flew to Hong Kong with $180,000 and started betting on horses instead. He walked away with almost $900 million.
It's Bill Benter. He figured horse racing was just another counting problem. Same math, more moving parts.
He and a partner showed up with $180k and a computer. Benter spent years teaching that computer to guess one thing, the real chance each horse had to win. If his number was better than the odds the bookies gave, he bet. If not, he skipped it.
That's the whole trick. Expected value.
EV = p · b − (1 − p)
Only bet when your win chance p, at odds b, is worth more than your chance of losing.
This recording was never meant to be some hidden gem. Nobody expected Professor Tsitsiklis to hand the whole foundation away in 45 minutes, but that's exactly what happens on the board. Students in that room pay over $80,000 a year to sit through it. It's free right here.
It's free right here. Every quant, every professional bettor, every hedge fund analyst started with this exact hour. Benter just watched it and actually did the homework.
Almost nobody knows this lecture even exists. Watch it before it gets taken down.
The answer is in this video.
