Adam Luba

[Adam Luba @adamluba1]

@blitzlink_ - Trey McBride just went 9/75 on 11 targets against ARI……wut?

[Ying Hua @huaxying]

On the buy side, I was lucky to have access to some of the best tools in the industry. The strange part was that each one made a piece of the job faster, but the research process as a whole still felt fragmented.

That experience shaped our vision for Implied. We saw AI as a chance to rethink the research process from scratch. We wanted to build one platform that could stay with you throughout the entire research day. One that understands your work, can help with every part of the process, and knows when to bring something important to your attention.

It’s the platform I wish I’d had on the buy side. This is a day on Implied.

[Implied @impliedinsights]

Ever feel like you’re already behind before the market even opens?

What if you could wake up knowing what changed, arrive with the research already underway, and follow your curiosity all the way to conviction?

See what a day on Implied looks like.

[Adam Luba @adamluba1]

Clarity when the market gets chaotic.

[Implied @impliedinsights]

We’re in the thick of earnings season. It doesn’t have to be chaotic.

See what earnings can look like with Implied.

[Ethan Kho @ethanrkho]

Insurance stocks used to move 2–3% on earnings. Now they move 15–20% intraday. An ex-Balyasny PM explains why automation caused it — and why that's bullish for human analysts:

Ying Hua (@huaxying) — a decade covering insurance at Goldman and Citadel, then quantamental PM at Balyasny, now founder of Implied (@impliedinsights) — explains:

"When I started in 2010, a 2–3% move in insurance was huge. By the time I left, you'd see intraday 15–20% moves."

"The reason: everything predictable forces everyone onto the same side of the boat."

"AI is just another wave of quant — less on number data, more on word data. Next-token prediction is pattern matching."

"When that alpha collapses, everything that isn't pattern matching carries more weight."

"Look at credit card data. Hedge funds had a five-to-six-year lead of just easy money. Now people buy it not to generate alpha — just to know what everyone's expecting."

"The crazy moves around earnings are the things the data didn't predict. Everyone missed it, so everyone has to scramble to the right side."

"Automation collapses alpha in one area but expands opportunity in others. A differentiated view gets paid more — so this should mean more people doing the things only humans can do."

[Ethan Kho @ethanrkho]

Why pod shops can be right 70% of the time and still get crushed:

Ying Hua (@huaxying) — ex-Goldman, ex-Citadel, PM at Balyasny, now founder of Implied (@impliedinsights) — explains:

"Poker is extremely similar to investing when your time horizon is a few weeks to a few months — which is where most multi-manager hedge funds live."

"What matters in poker? Other people's perception of your hand, where they sit, and how much stack they have."

"In a sector with no new money coming in, the players at your table are just the other pod shops."

"Because you have a similar process and similar data, you more or less know what card everyone is trying to present. So everyone does the same thing."

"As a group, you're probably right 60–70% of the time."

"But when you're right, you don't get paid — because you need to sell to get paid, and everyone's selling."

"And the times you're wrong, you really get screwed. Everyone's getting out. Everyone has to go to the other side at once."

[Ethan Kho @ethanrkho]

Ex-Balyasny PM Ying Hua (@huaxying) on why automation will increase demand for hedge fund talent, the quant/fundamental convergence, & why quant is blackjack but fundamental is poker.

Ying Hua (PM @ Balyasny — built & led a quantamental team covering US insurance, capital markets & fintech | ~5 yrs @ Citadel running a long/short insurance book | Equity research @ Goldman Sachs | MS in Data Science @ UC Berkeley | Now founder & CEO of Implied @impliedinsights)

"One of the best-kept secrets: fundamental investors are not good at sizing. Quant funds are really good at sizing."

We cover:
- The only real line between quant and fundamental: historical pattern matching vs. "how is this time different" — and the alpha neither group is looking at
- Why she rebuilt her process so every model updated within 2 minutes of a print
- Scraping highway patrol data from 15 states to track auto insurance losses live, every single day
- The Malibu wildfire: mapping burned mansions from celebrity tweets to estimate losses before any industry consultant published a number
- Her automation math: data gathering ~100% automatable, processing ~80%, judgment still 100% human
- AI is quant for words — next-token prediction is pattern matching, which makes this just the next automation wave after quant and indexing
- The proof differentiated views pay more: insurance stocks moved 2-3% on earnings in 2010; by the time she left, 15-20% intraday
- Why "hook Claude Code up to data and let it rip" fails: BloombergGPT losing to a smaller open-source model, & why horizontal models are college grads
- Quant is blackjack with card counting; multi-manager investing is poker — your hand, others' perception of it, your seat, everyone's stack
- Most PMs are playing the wrong game: the positioning game hiding inside "fundamental" sectors with no new money coming in
- Her hiring bar at BAM: every fundamental analyst learns Python — and the one skill she says can't be trained
- The only two truly meritocratic jobs: hedge fund PM & sales

Highlights:
(00:00) Intro
(00:40) How a quantamental PM actually puts on a position
(02:05) The only real line between quant and fundamental
(04:45) Why quantamental lowers the burden on your brain
(06:40) Scraping 15 states of highway patrol data to nowcast insurance losses
(09:25) The Malibu wildfire: estimating losses from celebrity tweets
(11:55) How much of fundamental investing can be automated
(13:45) Quantifying intuition: when a CFO's filler words jump 8% to 20%
(16:25) The contrarian case: automation expands demand for talent
(18:15) Earnings vol exploded — differentiated views pay more
(20:25) Why Claude Code can't run your book
(23:40) Horizontal models are college grads with no domain knowledge
(30:50) Why chat is the wrong interface for investors
(36:20) Will AI make markets more or less efficient?
(39:10) Two things every fundamental PM should do today
(41:50) The moat that expands: talent, redefined
(45:50) Sometimes the game is positioning, not fundamentals
(48:25) Blackjack vs. poker vs. surfing: matching the game to your horizon
(52:00) Should young analysts chase the hottest sector?
(57:55) Munger vs. Musk: two philosophies of wealth
(1:01:05) Self-awareness in investing is bimodal
(1:07:05) The only two truly meritocratic jobs: hedge funds & sales
(1:08:50) The one skill for every regime: reconstruct the narrative

[Adam Luba @adamluba1]

Ken Griffin says “short-term alpha from calling the quarter with alt data is dying.”

But average earnings-day volatility has climbed from under 3% to over 5%. The opportunity may not be disappearing. The tools for capturing it may simply be changing.

We’re testing whether AI can be the next great earnings predictor.

[Implied @impliedinsights]

https://t.co/SJVZ51SMD4

[Adam Luba @adamluba1]

We never wanted to build just another chat bot. The possibilities for an AI native fund are so much greater than that. Excited to share more about what we've been working tirelessly on building for the last two years.

[Implied @impliedinsights]

Every fund has a chatbot. Most investors tell us their process doesn't feel much faster. The time AI saves on search gets spent stitching everything else together across an already fragmented stack.

The mistake is treating AI as one more tool. We believe it's the first real opportunity to rethink the research process from scratch, and we've spent the last two and a half years building exactly that: one system for the entire workflow, run by an agent that knows your names, learns from live information, and works ahead of you.

There's a lot to build, and a race to build it. The first funds to get there lock in a multi-year lead. So what does it take? Not to deploy a chatbot, but to actually build an AI-native research platform? We just published our first post on exactly that. Link in the reply.

[Implied @impliedinsights]

Every fund has a chatbot. Most investors tell us their process doesn't feel much faster. The time AI saves on search gets spent stitching everything else together across an already fragmented stack.

The mistake is treating AI as one more tool. We believe it's the first real opportunity to rethink the research process from scratch, and we've spent the last two and a half years building exactly that: one system for the entire workflow, run by an agent that knows your names, learns from live information, and works ahead of you.

There's a lot to build, and a race to build it. The first funds to get there lock in a multi-year lead. So what does it take? Not to deploy a chatbot, but to actually build an AI-native research platform? We just published our first post on exactly that. Link in the reply.

[Adam Luba @adamluba1]

@lincoln3_ @aleabitoreddit @vancegson The shares convert. You don't have to do anything.

[Adam Luba @adamluba1]

New 2026 uniform unveil

[Peter Anthony Cowan @living_energy]

Low-frequency electromagnetic fields can degrade collagen, weaken tendons, and cause soft-tissue damage at levels regulators call "safe."

We have a real world case study proving this:

An NFL team whose practice facility sits next to a massive electrical substation.

THREAD 🧵

https://t.co/4AFRlmqgZv

[Adam Luba @adamluba1]

@josemorgado Fed/Nadal ‘09 AO is the best match and highest quality of tennis I’ve ever seen.

[Adam Luba @adamluba1]

@thorfinnur @tequieremos @josemorgado 09 was better.

[Adam Luba @adamluba1]

@StockSavvyShay Snowflake has little to no useful application in the AI ecosystem. Your cursory technical understanding of how AI workflows are built is misleading your followers.

[Adam Luba @adamluba1]

@_willcompton Welcome to a real man’s sport, Will

[Adam Luba @adamluba1]

@austinabbott Justin Fields or Caleb Williams?

[Adam Luba @adamluba1]

@ramit When you buy a house it is highly leveraged without the same risk to the downside. Then when you sell it you get many tax advantages like no cap gains on the first 500k in appreciation. So investing the difference from rent is a tragically worse investment

[Adam Luba @adamluba1]

@stoolpresidente 24,272

[Adam Luba @adamluba1]

@stoolpresidente He was a junior champion downhill skier. He’s got some of the strongest legs, best balance, and fitness on tour.