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Books: https://nitter.gq/t.co/VH9p5RkhFQ Newsletter: https://nitter.gq/t.co/nrBv4yVmWa Platforms: https://nitter.gq/t.co/6nk8SdQ6Nw | https://nitter.gq/t.co/6eOukprKLO

Joined July 2019
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Hey guys! I’ve just released a refined, compact edition of one of my newsletter series on the foundations of quantitative trading. It is a theoretical introduction designed for aspiring quants who are beginning to explore the field. The focus is on first principles, method, and the conceptual framework behind quantitative trading. Link in the comments. I hope you enjoy it.
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The paper defines a separator as information that makes asset returns mutually conditionally independent. It then says that the maximum absolute conditional correlation is zero when the information is a separator. But that equivalence is false without additional distributional assumptions.
One thing is a portfolio that performed well historically and another to demonstrate that the portfolio-selection process will work out of sample.
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🟥For this one and more papers with code: quantbeckman.com
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For something so absurdly simple, it is so beautiful.
Previously, this was called an agent in trading
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Evaluate the severity of the original breakdown, verify remediation through several quarters of clean filings, and confirm that restatement risk is resolved. The sweet spot is finding a solid core business whose governance discount is lifting. The setup occurs when a multi-quarter control discount disappears while operating fundamentals remain intact. Enter only after the market begins repricing the lower reporting-risk state.
🎙️[PODCAST] Why I’m leaving QuantX🎙️
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One thing is a portfolio that performed well historically and another to demonstrate that the portfolio-selection process will work out of sample.
The problem is that the additional reward depends on price changes and sentiment, not on how much of each asset the agent actually holds or trades.
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🟥For this one and more papers with code: quantbeckman.com
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Previously, this was called an agent in trading
Market mechanics > Fitting parameters
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🎙️[PODCAST] Why I’m leaving QuantX🎙️
The problem is that the additional reward depends on price changes and sentiment, not on how much of each asset the agent actually holds or trades.
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The problem is that the additional reward depends on price changes and sentiment, not on how much of each asset the agent actually holds or trades.
The authors acknowledge in Section 3.1 that the dynamic program uses the entire realized order-flow path of the evaluation day, including information that becomes available after each trading decision 😬 in other words, look-ahead bias
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🟥For this one and more papers with code: quantbeckman.com
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Market mechanics > Fitting parameters
The jackknife method systematically evaluates the impact of each observation by recalculating the median after its removal <3
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There’s only one reason I haven’t told X to fuck off. 🤣
Auditor resignations are another data source because it can reflect governance and risks. Indeed, his job can be assessed as any other event. Here, the bearish setup carries high conviction when a resignation intersects with deteriorating liquidity.
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Auditor resignations are another data source because it can reflect governance and risks. Indeed, his job can be assessed as any other event. Here, the bearish setup carries high conviction when a resignation intersects with deteriorating liquidity.
Resolved filing delays create opportunities when the 10-Q or 10-K report numbers that match expectations. The long thesis strengthens once accounting issues are clear, and the stock begins recovering the NT drop. Here the entry triggers after the filing posts.
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The authors acknowledge in Section 3.1 that the dynamic program uses the entire realized order-flow path of the evaluation day, including information that becomes available after each trading decision 😬 in other words, look-ahead bias
Interesting interpretation for the Sunday morning. I only have to say that learning a representation of market microstructure is not equivalent to learning a predictive, economically useful, or causally accurate model of financial markets.
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🟥For this one and more papers with code: quantbeckman.com
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The jackknife method systematically evaluates the impact of each observation by recalculating the median after its removal <3
These are the 3 reasons why you dont have an edge
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Systematic macro hedge funds outperformed discretionary macro strategies in Q3 2026. But only by 5.7%... nothing impresive
Nobody is talking about the broadest synchronized hedge fund losses since the pandemic, but anyone can have one bad day right!?
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