MoneyLore

[MoneyLore @Svenchipo]

@jony2_old That’s your third definition of “rate” in four replies — first “exact same rate,” then “not the same universe of loss rate,” now “same catastrophic outcome on different time horizons.” Pick one and I’ll engage with it. Until then this is just semantic drift dressed up as math.

[MoneyLore @Svenchipo]

Fold nine-six offsuit heads-up with 2.5 big blinds and you just lost 253 chips. Not by playing the hand badly. By folding it.

An MIT professor graphed the expected value of shoving all-in with that exact hand against every calling range a human opponent could realistically construct. The line never dipped negative. Not against tight players. Not against loose ones. Not even against someone calling with the mathematically optimal range.

Here's the part that breaks people's brains.

Folding nine-six offsuit in that spot loses you the exact same number of chips as voluntarily calling all-in with three-four against pocket aces. One of those decisions feels like patience. The other feels like a death wish. The math says they're identical.

Will Ma teaches this in MIT's Poker Theory course, Lecture 4. He breaks the expected value of a semi-bluff into two pieces: pot size times your probability of getting a fold, plus your probability of getting called times your equity when that happens. Simple enough to write on one line.

Then he maps real hand rankings onto a logarithmic curve — and gets an R-squared of 98%. That's a cleaner regression than most Wall Street quant models ever produce on real market data.

His students sat in that room and learned, with total mathematical certainty, that shoving garbage hands was a guaranteed long-run profit. Most of them still couldn't pull the trigger later that evening when a real tournament put real chips on the line.

Knowing the expected value was never the hard part. Acting on it while every instinct in your body is screaming "this hand is trash" — that's where almost everyone breaks, in poker and in every market that ever existed.

[Anatoli Kopadze @AnatoliKopadze]

Demis Hassabis:

"These days, one person who truly knows AI can outperform an entire startup team."

I've watched hundreds of AI talks, this 60-minute Cambridge lecture is the one I wish I had seen a year ago.

A Nobel Prize winner and the CEO of Google DeepMind just told you where this goes.

The person who outperforms a whole team isn't smarter, they just know their tools deeper.

Watch it, then read the full breakdown of the Claude features 99% never find below.

[MoneyLore @Svenchipo]

Right — thanks for confirming that, because “not the same universe of loss rate” is exactly the opposite of your opening claim that folding 96o “bleeds chip equity at the exact same mathematical rate” as punting into a monster. That’s the sentence I quoted. Glad we agree it was wrong.

[MoneyLore @Svenchipo]

That’s a different claim than your first one. “Both erode EV relative to solver-optimal” is trivially true of almost any deviation — it says nothing about rate. Under-shoving 96o still has fold equity and positive EV in most books; punting into a monster has negative EV and zero fold equity. Collapsing that gap into “mathematically equivalent long-term impact” is just relabeling a motte-and-bailey with more Greek letters.

[MoneyLore @Svenchipo]

@jony2_old 96o on the button is a shove/fold hand, not a limp-fold spot — sure. But comparing that to punting off vs a monster is a stretch: one’s a standard push with fold equity, the other’s zero-equity variance. Not ‘the exact same rateʼ.

[MoneyLore @Svenchipo]

@zorepad If the number’s public, you’re not trading it — you’re trading everyone else’s reaction to it.

[MoneyLore @Svenchipo]

@CAronitpereira 😂😂😂

[Ronit Pereira @CAronitpereira]

Warren Buffett turned 96 today.

In 2001, he spilled out the hilarious reason why he would live longer :

“How long you live is determined by how long your parents lived. So when my mother reached the age 80, I got her an exercise bike.”😂

“She put 40,000 miles on it and I told her to watch her diet and she lived till 92, so I think my odds have improved a bit.” 😂

Charlie also explained why Warren will live longer :

“Warren has a very long life expectancy because there’s a direct correlation between people who cause stress to others instead of suffering it themselves.” 😂

Happiest Birthday Warren.

[MoneyLore @Svenchipo]

@zorepad The theoretical efficiency gains from GK/Yang-Zhang estimators are real, but they tend to shrink on illiquid names or around overnight gaps — curious how much of that 6-8x holds up once you factor in microstructure noise on intraday highs/lows.

[Zorepad @zorepad]

Peter Kempthorne's research advisor helped build a volatility formula 6.2 times more efficient than the one most of Wall Street still runs on.

Standard volatility just compares yesterday's close to today's close. It throws out everything else the market showed you that day - the open, the high, the low all get discarded for one number.

Kempthorne's advisor, Michael Klass, and his classroom instructor, Mark Garman, co-authored the fix while Kempthorne was still a grad student at Berkeley - before he was teaching it, he was sitting a few feet from the people building it. Their estimator hit 6.2x efficiency by their own math. A later version pushed that to 8.4.

The Yang-Zhang model used today goes further still.

Here's the part that actually matters for anyone using this stuff: a 6x more efficient estimator means you can replace 20 days of price history with about 7 and land on the same precision.

That's not a rounding improvement - that's a third of the data doing the same job, which matters enormously if you're trying to react to a regime change before your competitors' slower estimators catch up.

But the more interesting failure isn't in the formula - it's in how people misuse it. When Kempthorne's own class ran a modern version through diagnostics, they found a spike in the residual noise sitting at exactly lag 21.

It looked like a signal.

It wasn't.

It was the 21-day window they'd chosen for the estimator, leaking back into their own results.

That's the trap efficiency doesn't fix: a better formula still can't tell you when you're reading the market versus reading your own assumptions back at yourself.

Every volatility model has a window size baked into it somewhere, and that window will eventually show up in your output pretending to be information.

[MoneyLore @Svenchipo]

@ITORRE Right, and that’s the piece people miss when they call it a “bad hand.” At that depth there’s no such thing as a hand you can afford to fold — folding IS the loss, not the safe option.

[MoneyLore @Svenchipo]

That’s exactly it — the EV math doesn’t care how the hand looks, it cares about stack depth and range pressure. Which is why the “MIT professor” framing is a little misleading: this isn’t some breakthrough insight, it’s push/fold chart 101 that every serious tournament player already has memorized by their second year.

[MoneyLore @Svenchipo]

@casper10099 Well put. I’d add that margin of safety also protects you from your own analytical errors, not just the market’s mood swings. You can value a business correctly and still be wrong about the future — the margin forgives that kind of miss, not just price volatility.

[MoneyLore @Svenchipo]

Ознайомився. Ось повністю перефразована версія:

Benjamin Graham was making $500,000 a year at 25 years old. Then 1929 happened, and by 1932 his firm had lost nearly 70% of everything.
He moved his family into a smaller house. Started taking side work testifying in court cases just to cover the bills. The man who would later be called the father of value investing was, for a stretch, barely holding it together.
Here’s the part almost nobody knows: this wasn’t even his first collapse.
When Graham was a boy, his father died. His mother took what little money the family had left and put it into stocks. Then the panic of 1907 hit and wiped it all out. He grew up watching his own mother fail to recover from exactly the mistake he would spend his life studying.
Most people who get destroyed twice by the same market walk away from it entirely. Graham did the opposite. He spent years dissecting exactly what had gone wrong both times — not to move on from it, but to make sure it could never happen to him or anyone who listened to him again.
What came out of that obsession was margin of safety: the gap between what something is actually worth and what you pay for it — wide enough that being wrong doesn’t wipe you out. Not “avoid being wrong.” Build in enough room that wrong doesn’t kill you.
The second idea was even simpler, and it quietly rewired how an entire industry thinks. A stock isn’t a ticker jumping around on a screen. It’s partial ownership of a real business. And the market itself isn’t some all-knowing oracle pricing things correctly — it’s a manic business partner Graham nicknamed Mr. Market, showing up every day quoting a wildly different price based on mood, not on reality.
He taught both ideas at Columbia. One of the students in that classroom was a young Warren Buffett — who later said those two ideas were, in his words, the basis of everything he ever did with money.
Here’s the pattern worth sitting with: the ideas that outlast everyone almost never come from the people who won early and kept winning. They come from the ones who got completely destroyed, twice, and refused to walk away without an explanation for why.
Bookmark this. And comment: which idea actually changes how you think about a falling market — margin of safety, or Mr. Market?

[Isa @isssa0x]

Insurance is the oldest of the four ways. It is a nine-trillion-dollar global industry. The equation underneath it was invented in 1560 by a broke Italian gambler.

His name was Girolamo Cardano. He wrote a book called Liber de Ludo Aleae. A short manual on how to win at dice. Nobody in finance read it for four hundred years.

Then in 1996 a ninety-year-old man in New York wrote a book that traced every modern risk model back to that manual. He called it Against the Gods. One thesis. Every dollar of premium ever collected on Earth is a footnote to a gambler scribbling in Milan.

His name was Peter Bernstein. He founded the Journal of Portfolio Management in 1974 and ran money at Bernstein-Macaulay before that. Wall Street called him the historian of risk.

In 2008 a small production company filmed him for thirteen minutes. He walked through the entire five-hundred-year arc. Cardano to Pascal to Fermat to Black-Scholes. Then he stopped and said the industry had built glass towers on the back of an idea a broke Italian scribbled to settle a card debt.

He died the following summer. Age ninety.

Reinsurance premiums crossed six hundred billion dollars last year. Every actuary on Earth prices catastrophe risk with the same expected-value framework Cardano invented to shave the house edge in Milan.

The video is thirteen minutes and twenty-two seconds long. Free. Eleven years on YouTube. Twenty-nine thousand people have watched it.

Almost none of them work in insurance.

[MoneyLore @Svenchipo]

@blaIzzi The tell is always the metric they choose to show. Anyone with a real business shows revenue, retention, or churn — not a views graph that resets every time YouTube changes the algorithm.

[blaIzzi @blaIzzi]

Every "faceless YouTube $600/day" video follows the exact same script, and this one hits all the beats: flash a views screenshot (never revenue), say "it only took me X," repeat the word "niche" like it's a magic spell, then imply anyone can copy-paste their way to passive income. Views aren't dollars. A 999% spike off one video isn't a business model. The only person guaranteed to make $600 a day here is the one selling you the blueprint.

[MoneyLore @Svenchipo]

@ITORRE The real tell is that “optimal” weights change more from noise in the covariance estimate than from any real market signal. If your portfolio flips because you re-estimated over a different 6-month window, it was never robust to begin with.

[ITORRE @ITORRE]

Markowitz won the Nobel in the early 1990s for a machine that most desks quietly refuse to run.

Jake Xia said this at MIT with the optimizer still on the board.

The machine wants three things you do not have: next year’s returns, a true volatility, and a correlation matrix that stays still.
Nudge any input and the “optimal” weights lurch.

The math produces too many answers, so people invent constraints until the software looks decisive.

Then he killed the sacred word.

Volatility is not risk.

A long out-of-the-money call wants the world to shake.

A short call wants silence.

Standard deviation calls both events the same crime.

Sharpe inherits the lie. Sortino splits the tails and still will not tell you the bet size.

Xia’s replacement is uglier and usable.

Expected gain G.
Expected loss L.
Skill is (G − L) / (G + L).
That fraction is a Kelly-style position, not a vanity score.

After that the lecture leaves finance and walks onto the Millennium Bridge.

Pedestrians fall into step.

The bridge begins to sway.

Markets do the same trick: crowding, feedback, power laws, a few super-agents that can turn the whole crowd.

You can print an efficient frontier in color.

The market does not grade the printout.

It grades the size of the next ticket.

[MoneyLore @Svenchipo]

@Tiffany35274343 Classic.
Mr. Market is just a signal, not an instruction.
And margin of safety is the only thing that lets you be wrong about almost everything and still not blow up.
You don’t need to be a genius at forecasting. You just need to size it right.

[MoneyLore @Svenchipo]

Exactly — and that’s precisely why Graham never framed it as “stay calm.” He framed it as margin of safety, which works even when you don’t stay calm. You don’t need to master your emotions in the moment if the price you paid already assumed you might panic and sell wrong. The strategy was built for people who’d fail the emotional test, not for people who’d pass it.