I built a systematic stock selection pipeline and would love to collect some insights. Here are the core informations:
Good morning everyone!
I am making progress on my NBA_IV project.
I am used to fully trusting AI to translate my narrative ideas into code. I take advantage of your expertise to help me move forward View full post
I am making progress on my NBA_IV project.
I am used to fully trusting AI to translate my narrative ideas into code. I take advantage of your expertise to help me move forward View full post
Bonjour à tous !
J'avance sur mon projet NBA_IV.
J'ai l'habitude de faire pleinement confiance à l'IA pour retranscrire en code mes idées narratives. Je profite de votre expertise pour m'aider à ava View full post
J'avance sur mon projet NBA_IV.
J'ai l'habitude de faire pleinement confiance à l'IA pour retranscrire en code mes idées narratives. Je profite de votre expertise pour m'aider à ava View full post
Translated from French
nate_the_great The random selection problem makes sense — you miss the dominant names and the sector weights break.
Taking the top by market cap within each sector isn't selection bias — size is str View full post
Taking the top by market cap within each sector isn't selection bias — size is str View full post
nate_the_great Funny enough I run into the same issue on the crypto side.
The equivalent of SPY is the Total Market Cap, and BTC + ETH alone already represent ~55-60% of it. Add SOL, BNB, XRP and yo View full post
The equivalent of SPY is the Total Market Cap, and BTC + ETH alone already represent ~55-60% of it. Add SOL, BNB, XRP and yo View full post
Regarding your question
"ownership/utility seeking investors who invest for another reason like brand, franchise quality, narrative, scarcity or reflexive price history.
This is where I need the inp View full post
"ownership/utility seeking investors who invest for another reason like brand, franchise quality, narrative, scarcity or reflexive price history.
This is where I need the inp View full post
nate_the_great Yeah the Kalman gain is basically that — it decides how much weight you give to the new price vs what the model already expects. If the price is super noisy it just ignores most of it,
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BTC Daily — $81,198 · May 13, 2026
For the tenth consecutive day in the $79,500—$82,500 range, the market digested without making a decision. The $80,500 GAP continues to exert central gravity — each View full post
For the tenth consecutive day in the $79,500—$82,500 range, the market digested without making a decision. The $80,500 GAP continues to exert central gravity — each View full post
BTC Daily — $81,198 · 13 Mai 2026
Dixième jour consécutif dans le range $79,500–$82,500, le marché digère sans trancher. Le GAP à $80,500 continue d'exercer une gravité centrale — chaque tentative de View full post
Dixième jour consécutif dans le range $79,500–$82,500, le marché digère sans trancher. Le GAP à $80,500 continue d'exercer une gravité centrale — chaque tentative de View full post
Translated from French
Roman puts it perfectly — smoother vs filter. The look-ahead bias is exactly that: estimating a past state using future realizations.
The natural fix is a Kalman filter or HMM in filter mode, where Δ View full post
The natural fix is a Kalman filter or HMM in filter mode, where Δ View full post
Trader
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I really like the notion of decomposing anything into more intuitive or structurally understood components, the entire purpose of many matrix decompositions is to observe structure. You are correct i
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The real fear and greed index.
Research indicates that many animals can detect human fear through scent, guinea pigs are very sensitive to the scents associated with human emotions, such as sweat pro View full post
Research indicates that many animals can detect human fear through scent, guinea pigs are very sensitive to the scents associated with human emotions, such as sweat pro View full post
