Публикации
Исследования ИИ-агентов, бэктестинг и аудит рыночных прогнозов, а также архитектура платформы.
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The 20 biggest AI and chip stocks lost over $1 trillion in one week. Hedge funds dumped AI for five sessions straight while retail poured a record $3.9B into 3x chip ETFs.
5 мин чтения6 разделов
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MEV is one of the few places where machine learning has a defensible job, because the task is simulation and classification rather than price prediction. But private order flow makes every public-data study a lower bound of unknown tightness.
6 мин чтения6 разделов
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Most depegs that matter are plumbing wearing the costume of solvency. What machine learning can genuinely do with stablecoin data, why depeg prediction breaks on rare events, and how supply works as a regime descriptor rather than a signal.
6 мин чтения6 разделов
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Funding rates and open interest describe how levered a market is and what that position costs to hold. They forecast the size of coming moves, not the direction - and the data is full of traps that quietly wreck studies. What AI can honestly extract.
6 мин чтения6 разделов
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On-chain data is the only complete dataset in markets - no survivorship bias, no vendor filter. It is also built on unvalidated address labels and a handful of independent cycles. What AI can honestly do with a blockchain, and what it cannot.
7 мин чтения7 разделов
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Direction is the AI forecast everyone wants and a liquid market defeats. How far an asset can move is the one machine learning can make - and prove. Why sigma-root-t is wrong in both directions, and what coverage really tests.
7 мин чтения7 разделов
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Everyone chases AI that predicts price. The place machine learning genuinely earns its keep is risk management — volatility, position sizing, drawdown, liquidation. Measurable, unglamorous, honest.
9 мин чтения7 разделов
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Retail sees price and volume. Machine learning reads liquidity — depth, order-flow imbalance, market impact, hidden orders — the short-lived information beneath a single price. And its honest limit.
9 мин чтения7 разделов
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Measured over the full Binance history: the root-t band is 20% too wide at one day, converges by thirty, and crosses over for ETH. Plus the overlapping-window correction almost everyone skips.
7 мин чтения7 разделов
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Why Ethereum is a different forecasting problem from Bitcoin — staking queues, fee burn, rollup migration, and the beta trap that makes weak ETH models look skilful.
9 мин чтения7 разделов
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Where AI genuinely changes a crypto exchange: surveillance, risk engines, liquidity, AML, matching-engine ops — and where the label is mostly marketing.
9 мин чтения7 разделов
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What AI can honestly do for Bitcoin price prediction, what is theatre, and why a timestamped, hashed, publicly scored forecast is the only real evidence.
7 мин чтения6 разделов
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How AI detects crypto volatility regimes using realized volatility, clustering, and time-series models — and why the honest output is uncertainty, not price targets.
6 мин чтения7 разделов
