sosa

Content creator | Market analyst | Alpha hunter
only chill vibe

[Zorepad @zorepad]

90 days from bankruptcy is where Tim Cook chose to build his career.

He's 37, running operations at Compaq - then the biggest PC seller on Earth. Apple just lost a billion dollars. Recruiters had tried to pull him there before. He'd said no every time.

Then he sat down with Steve Jobs.

By his own account, the meeting undid every rational argument he'd built for staying at Compaq. A mentor warned him he'd regret it. The spreadsheet said stay. He left anyway and called it a gut decision, not a math one.

What actually convinced him wasn't a turnaround plan - Apple didn't have one worth believing in yet. It was watching how Jobs made decisions in real time.

The rest of the industry had already concluded consumers weren't where the money was and pivoted hard toward enterprise clients. Jobs went the other direction, on purpose, while everyone else was walking away from regular buyers. The same instinct ran the internal org chart too - he kept the iPod and iPhone teams deliberately small, betting a handful of people could out-build entire divisions stacked with more headcount and more budget.

Here's the part I think gets missed when people retell this story as "Cook bet on a genius": Cook wasn't betting on Jobs's vision. He says outright the trait that mattered most was that Jobs could drop an idea he'd defended for years the second a better one showed up - no ego attached to being right.

That's a completely different kind of conviction than "believing in someone." It's betting that a person's process for changing their mind is more reliable than their current answer. Cook left a safe job at the market leader not because he was sure Apple would work, but because he was sure Jobs would notice fastest if it wasn't working - and change course without flinching.

Neither man ever protected his own idea once a stronger one showed up. That's the actual through-line, and it's a harder thing to hire for than talent

[sosa @IMundyk]

@zorepad @ITORRE People frame it as Cook having the courage to bet on Steve Jobs. But the real bet was on how Jobs thought

[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.

[sosa @IMundyk]

@zorepad @ITORRE This is the part people tend to miss. Better estimation doesn’t automatically mean better information

[sosa @IMundyk]

This is the part of portfolio theory people conveniently forget.

You can build the perfect model on paper, but if the inputs are garbage and the position sizing is wrong, the “optimal portfolio” means nothings

[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.

[ITORRE @ITORRE]

Sixteen geniuses with 350 years of combined experience still blew up Long-Term Capital Management.

Warren Buffett told the story to Florida MBA students in 1998, weeks after the rescue.

John Meriwether. Myron Scholes. A room of high IQs and leverage.

They risked what they needed for what they did not.

Buffett had bid $250 million for the net assets plus $3.75 billion of new capital.

He walked.

The fund still needed the New York Fed.

The same afternoon he explained the opposite machine.

See’s Candy cost $25 million in 1972.

By 1998 it was throwing off $60 million a year.

Price went up every year. Customers stayed.

Time is the friend of the wonderful business.

It is the enemy of the lousy one.

He told the room to buy businesses they understood, with honest managers and a moat, and to stop at about 6 of them.

The seventh best idea is how people stay average.

Coca-Cola went public in 1919 at $40.

It fell 50% in a year.

Reinvested, that share was worth about $5 million.

The lecture is free.
Almost nobody sits through the Q&A.

[Zorepad @zorepad]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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[sosa @IMundyk]

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