Author
Michael Gu, Creator of Boxmining, stared in the Blockchain space as a Bitcoin miner in 2012. Something he immediately noticed was that accurate information is hard to come by in this space. He started Boxmining in 2017 mainly as a passion project, to educate people on digital assets and share his experiences. Being based in Asia, Michael also found a huge discrepancy between digital asset trends and knowledge gap in the West and China.
182 articles
SafePal says an order-tracking flaw exposed 39,798 buyers. Wallet keys were not leaked, but names, addresses and order details can fuel targeted scams.
Latency matters only relative to a strategy, venue and market event. Map the full path before paying to optimize the wrong bottleneck.
The symbol may look the same, but matching rules, products, fees, depth and account risk make each exchange a different market.
The signal is the visible tip. Production trading depends on market data, risk, execution, monitoring, capture, recovery and reconciliation.
A backtest, event replay and paper account answer different questions. Use each as a gate—and keep live capital outside the experiment.
A correct up-or-down call can still be a losing trade. Compare direction labels with fair value, expected return and decisions after costs and risk.
Sequence gaps, clock drift, revised candles and vanished assets can manufacture an edge. Here is how to build market data that can be audited.
Rebuild two classic microstructure teaching signals, then stress-test the assumptions that make an attractive formula fail in real crypto markets.
Market makers wait, takers demand immediacy and arbitrageurs connect prices. Here is what each role earns—and what each risks.
Learn how order events create bids, asks, spreads, depth and trades—and why the visible book is only a conditional snapshot of liquidity.
Follow one hypothetical crypto order from a live quote through market data, risk checks, matching, fills and account reconciliation.
A model should never hold unlimited signing authority. Learn how keys, scoped permissions, policy checks, approval, and revocation fit together.
A safe trading agent needs explicit reasons not to trade. These seven external gates turn vague caution into testable rejection rules.
AI agents, trading bots, and copy trading automate different decisions. Compare who creates the signal, who controls execution, and where the risks sit.
GameFi did not fail because digital ownership is useless. It failed because projects priced financial demand as if it were player love, then built economies that needed new buyers more than games that retained ordinary players.
An AI trading agent can research, propose, and sometimes execute trades. The important part is the control system between its idea and a signed order.
Harmony patched a cross-shard replay flaw after roughly 4 billion ONE appeared without authorization. The incident follows years of bridge losses, token inflation and failed recovery.
Crypto price charts and prediction-market odds can react to the same event while answering different questions. Here is how to compare them without forcing a false signal.
A correct prediction is not automatically a profitable trade. Learn how bid-ask spread, visible depth, fees, latency, queue uncertainty, and partial fills change the result.
A reproducible experiment for testing AI forecasts against Polymarket odds without leaking the answer, cherry-picking markets, or pretending paper fills were real.
Build a useful Polymarket AI agent without giving it a wallet: collect public data, make time-stamped forecasts, simulate realistic fills, and audit every decision.
Boxmining’s methodology template for evaluating AI trading agents across forecast calibration, drawdown, execution, refusals, safety rules and reproducibility—not headline profit alone.
A practical explanation of how automated market makers quote prediction markets, manage inventory and survive adverse selection—without pretending the order book reveals who runs an AI agent.
A defensive guide to keeping hostile headlines, webpages and tool output from turning an AI market analysis task into an unauthorized trade.
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