Itu Picaaang
84.3K posts
Itu Picaaang
@PAClearning
Stats/ML/Quant
semak-semak Tham gia Mart 2011
3.6K Đang theo dõi11.9K Người theo dõi
Baiknya...
Rumahkan setengah yang kurang produktif, dobelkan atau tripelkan THP yang produktif, serta moratorium rekrutmen selain tendik dan nakes.
kale@kalistohenituse
unpopular opinion tentang PNS/PPPK :
Indonesia
@Cheytax_1 Retail dikasih AI, bukannya makin pinter malah kepedean tapi salah.
Alhamdulilah
Indonesia
Alhamdulilah masih banyak orang seperti ini.
The Wheelie Investor@WheelieInvestor
MY OPENCLAW BACKTEST IS COMPLETE The results looks very promising This is how the bot would have performed in FY 2025 I'm ready to deploy this bot. I am confident First fully automated trade will commence soon. Stay Tuned!!!
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@danauhaikal @ChocomaltMacha Hayo gimana kira-kira kalkulasinya? 😁
Indonesia
@ChocomaltMacha @PAClearning kalo 1H trading pak? apakah tetep butuh 4yr period of time jg, atau dengan 300 sample backtest sudah cukup??
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What happens to your codebase when you stop reviewing your agents' output
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@catuaries Untungnya daru dumb money yang dikasih AI kaya gini memang
Indonesia
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FLASH SALE PAYDAY ⚡️
Program yang bikin skill meningkat dengan intensive mentoring dan diajarkan secara slow-paced yang meningkatkan keberhasilan sampai 10x lipat di Pacmann
Mulai dari 2,998 juta untuk 6 bulan.
Indonesia
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Pengen tahu lebih lanjut mengenai Strategi Investasi dengan metode hedge fund yang tahan banting?
Jangan lewatkan WEBINAR GRATIS PACMANN berikutnya!
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@majaw3634 @ChocomaltMacha Butuh 4 tahun dan trading per hari untuk buktikan forward test Sharpe benar atau valid.
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@ChocomaltMacha @PAClearning Tentu saja jawabannya 😂
Indonesia
@pedma7 @JoachimMo1985 @macrocephalopod Are you running a sector-neutral strategy by orthogonalizing your strategy against market and sector risks?
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@JoachimMo1985 @macrocephalopod @PAClearning you have a bunch of different sectors, but tbh, most are not relevant on their own from what I observe. the most risky one that usually puts on some massive runs are memecoins. its a nasty sector to be short at at reversals as they tend to all pump a lot together.
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@pedma7 @macrocephalopod Are you not afraid of a potential large drawdown with a 40% volatility target?
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40% vol target for the systematic portfolio and at least a sharpe of 1. but tbh, on sharpe, I am not too concerned about it, since im still running mostly trend stuff.
but here's my realized metrics:
new systematic port (since nov 2025): 25% vol and 0.95 sharpe
global port (from aug 2023): 156% vol and 1.48 sharpe (skewed by a few large long term bets ive made over these past few years)
the systematic port fell short of the vol I set because for a bit of time I was not factoring in correlations into the targeting formula which was naturally falling short of vol targets all the time.
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How to Build an Alpha Engine, PIMCO (2004)
people.duke.edu/~charvey/Teach… [pdf]
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@goldydharmawan @IraninIndonesia Padahal lucu kalau ngeledekin posisi Indonesia yang plin-plan. 😂
Indonesia
@PAClearning @IraninIndonesia Agak susah kayaknya, serius soalnya 😅
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Consider that the dumbest people you know are repeatedly being told "You're absolutely right!" by LLMs.
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In 2008 every stock on Earth was crashing
Hedge funds shorted Volkswagen expecting it to follow the rest of the market down
Then Porsche quietly revealed they had been secretly accumulating 74% of VW through options and nobody saw it coming
The free float was just 6% but short interest was 12%
There literally weren’t enough shares on the planet for short sellers to cover their positions
In a single week Volkswagen went from an ordinary automaker to the most valuable company on Earth passing ExxonMobil at over $370 billion
Short sellers lost over $30 billion and some funds were completely destroyed overnight
The greatest short squeeze in history didn’t happen during a boom
It happened during the worst financial crash in 80 years
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Yeah, right, until you realize that your searches overfit your data.
Han Xiao@hxiao
autoresearch basically starts the era of disposable model. AI labs that can't automate their own R&D pipeline will be outrun by those that can. The moat isn't talent anymore - it's the speed of your automated experimentation loop. - minimax 2.7 was built from an autoresearch-like pipeline - models designing models. - half-life of a frontier model is now down to a month in 2026 - at minimax & miromind, the model now decides who to hire. Not HR. Not hiring managers. The model evaluates market talent, identifies capability gaps, and recommends candidates. If your AI can build the next AI, it sure as hell can pick the humans it needs to assist the process.
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@PAClearning Mohon maaf lahir batin ya kaaak.
Ada versi mini
Indonesia
Selamat Idul Fitri, mohon maaf lahir dan batin teman-teman X semua.
Indonesia
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