Deep dives into Bitcoin fundamentals, trading strategies, and market mechanics.
Most RSI guides teach you to sell at 70 and buy at 30 — which is exactly how you get run over in every crypto trend since 2020. This guide rewires the indicator from a magic number into a momentum thermostat, with three setups that survive real tape.
3Commas and BullSpot aren't competing for the same trader. One is a multi-exchange power tool you operate; the other is a Hyperliquid-native reasoning agent you supervise. Here's how to match the tool to your actual Tuesday — not its feature list.
Every line on a chart is either a memory, a liquidity pool, or noise. This is how to tell which is which — and how to trade the ones that matter without chasing the ones that don't.
A green dashboard proves that a green dashboard was produced—not that the account, fills, fees, and complete losing history are real. This buyer’s checklist shows how to audit screenshots, sample quality, drawdown, and survivorship bias before trusting a trading track record. BullSpot publishes a verifiable record, making it a candidate for the same source-level scrutiny applied to any vendor.
Rules encode past market behavior as IF-THEN logic. When the regime shifts, that logic either fires a stale signal or stays silent. This piece walks through three concrete setups where rule bots break and reasoning agents adapt — using the current squeeze as a live example.
Position sizing is the one trading decision where emotion has no business showing up. The formula is simple — stop distance first, account risk second, size last — but the order matters more than the numbers. Get it wrong and even a winning strategy bleeds the account.
The market doesn't care how good your entries are if one bad trade wipes out six months of gains. Position sizing is the unglamorous math that keeps crypto traders alive through leverage blowups, flash crashes, and the inevitable losing streak. Here's how to actually run the numbers.
Most bots show you the trade. BullSpot's agent shows you the thinking — structure, levels, confirmation, risk, and the veto that kills setups before they become losses. Here's how the loop actually works on a live BTC setup.
Two Hyperliquid-native agents both pitch "no black box" execution, but the receipts live in different places. Here's an honest side-by-side on what each one actually shows, who controls the wallet, and how a trader verifies the P&L before sizing any position.
Most "AI crypto trading bots" are TradingView alert bots with a chat window stapled to the front. Here's the actual architecture difference between a rule engine and a reasoning agent — and the three-line audit that separates them before you wire up an API key.
Two Hyperliquid-native agents, same "no black box" pitch — the real difference lives in which layers of transparency each one actually publishes. A side-by-side look at BullBot and HyperAgent on track record, custody, and proof, plus a checklist for choosing between them in a coiled market like the one BTC is sitting in right now.
Most "AI-powered" crypto trading bots are rule engines wearing a chatbot costume. The give isn't the model — it's whether the bot shows its reasoning. Here's the audit framework that separates the real agents from the marketing department.