Guides & essays

Agentic Trading

• Robinhood's Agentic Accounts Add Limited Margin
  Announced August 12: switch the agentic account from cash to limited margin and the agent trades with unsettled funds — no T+1 wait, no borrowing. What it fixes, and the pattern-day-trading question Robinhood hasn't answered yet.
• Why the Sentiment Gauges Disagree
  AAII, CNN Fear & Greed, the VIX and put/call ratios contradict each other because they measure different things on different clocks. What each one actually reads, and where sentiment belongs.
• We Tested Betting on the Decline. It Did Not Work.
  We pre-registered a grid of inverse-ETF hedges and measured every cell against cash and a defensive macro sleeve. All 36 failed. Here is the full result, published.
• Correction, Bear Market, Crash: The Thresholds Are Arbitrary
  Pullback, correction, bear market — what the thresholds actually are, who defines them, and why 19.8% and 20.2% are the same tape. The label is a reporting convention, not a decision boundary.
• Should You Turn Your Trading System Off During a Crash?
  A losing system and a broken system feel identical from inside a drawdown. The only way to tell them apart is with criteria you wrote down before it started.
• Market Weakness Is a Risk Input, Not a Veto
  We built the rule that stops buying when the market is down, measured it over 2,649 S&P sessions, and threw it out. Weakness predicted drawdown, not returns.
• Can an AI Agent Trade Crypto in 2026? Broker by Broker, Honestly
  Yes at Coinbase, announced at Robinhood. The broker-by-broker state of agentic crypto — and where a benchmarked signal read fits, losses included.
• Robinhood Is Opening Agentic Trading to Crypto
  What the July 10 announcement covers, what is still unknown — and, updated July 15: Coil's crypto board is now live as a read, losses published next to the record.
• Can an AI Agent Manage My Portfolio?
  Should an AI agent manage your portfolio? Why improvised trading fails, why rule execution is different, and the questions to ask any tool.
• MCP Explained for Traders
  What the Model Context Protocol is, what a broker MCP server exposes, why it beats screen-scraping and pasted API keys, and what agents still cannot do.
• Robinhood's 70,000 Agentic Accounts, in Context
  Robinhood says roughly 70,000 accounts have enabled agentic trading, well under 1 percent of its funded base. What that tells us about the era ahead.
• Scheduled AI Agents: Software on a Cadence
  Agent scheduling lets trading software run on a cadence inside your AI agent instead of a server you maintain. What it enables, and what to demand.
• What Is Agentic Trading? A Plain Explainer
  What agentic trading is, how it differs from robo-advisors and classic bots, and what a safe setup looks like. A plain explainer for 2026.

Agent Economy

• Can AI Agents Buy Software Yet?
  How AI agents find and buy software in 2026: llms.txt, machine-readable manifests, and the checkout step that still needs a human.
• Self-Custody Trading Software: Keep Your Keys
  What self-custody means for trading tools: why broker API keys should stay on your machine, the threat model of hosted platforms, and what to check first.
• The Agent Economy: When Software Buys Software
  AI agents are starting to discover, compare, and buy on our behalf. What that changes for builders and buyers, and where a $12/mo board fits.
• What Makes Software Agent-Native
  Agent-native software ships machine-readable docs, manifests, deterministic CLIs, and verifiable claims. Here is what that looks like in practice.

Method

• Crypto Trend Following vs Buy-and-Hold: 10 Years of BTC/ETH, Honestly
  Ten years of BTC/ETH through a gated trend rule: 59.6% vs 74.9% CAGR — it does not beat holding — in exchange for smaller crashes. The full table, ugly rows included.
• Will Automation Give You Better Returns Than Trading Manually?
  The honest answer: automation does not add returns, it subtracts mistakes. What retail traders actually lose to, what a bot fixes, what it cannot, and how to judge any automated strategy.
• Buy Pullbacks, Not Breakouts
  Why disciplined systems buy leaders on pullbacks to real support instead of chasing breakouts. Entry price defines risk and structure gives a close stop.
• Cash Is a Position
  Cash is an allocation, not the absence of an opinion. Why systems that must always be invested degrade, and why long-only ones need permission to sit out.
• How to Read a Backtest Before You Trust It
  A vetting guide for backtests: survivorship bias, fill assumptions, cost modeling, inflated t-stats, and the exact questions to ask any vendor.
• Leadership Rotation, Explained
  Market leadership rotates. Why last cycle's winners go stale, how relative strength ranks the new leaders, and why cash is a valid answer.
• Regime Concentration: Where Edge Actually Lives
  Most strategies earn their edge in specific regimes and roughly match markets elsewhere. Why vendors hide this and how to ask when a system fails.
• Relative Strength vs Momentum: The Real Difference
  Momentum measures a stock's own trend. Relative strength ranks it against every peer. Why the difference matters and how a scanner uses both.
• Sector Rotation: A Practical Guide
  How money rotates between sectors, how it shows up in relative strength before headlines, and why rotation informs entries but never dictates them.
• Structural Stops vs ATR Stops, Explained
  Why stops placed at the price where the thesis fails beat volatility-multiple stops, how wide stops interact with sizing, and why no stop is a guarantee.
• Survivorship Bias in Backtests, Explained
  Testing today's index members backward quietly deletes every stock that died. How survivorship bias inflates backtests and how to fix it.
• Why Long-Only Is a Feature, Not a Limitation
  Shorting doubles the ways to be wrong and inverse ETFs decay on multi-day holds. Why Coil trades long-only, and what that choice honestly costs.

Leverage

• Leverage as an Accelerant, Not a Default
  Leverage works as a deliberate accelerant on high-conviction setups at reduced size, not a standing default. How Coil treats leveraged ETFs.
• Leveraged ETF Gap Risk: When Stops Don't Fire
  Overnight gaps skip stop losses. A 3x fund turns an index gap into roughly triple the damage at the open. How to score gap risk before entry, not after.
• NVDL vs NVDA: What 2x Daily Really Means
  NVDL targets 2x NVDA's daily return, not 2x the stock. How daily reset and compounding drift change multi-day holds, and when a system uses 2x.
• Single-Stock Leveraged ETFs: A 2026 Field Guide
  A 2026 guide to single-stock leveraged ETFs: how they differ from index leveraged funds, why decay and gap risk bite harder, and who they suit.
• TQQQ vs QQQ: The Long-Term Math
  TQQQ promises 3x the Nasdaq-100 per day, not per year. Plain-words math on daily resets, volatility decay in chop, gap risk, and holding-period honesty.

Future

• AI Job Displacement and Market Leadership
  Automation waves reshape market leadership. Where earnings power migrates when AI changes work, and how rotation frameworks track it without forecasts.
• AI Trading Scams: 9 Red Flags to Check First
  Nine red flags to check before paying for any AI trading product: guaranteed returns, income promises, hidden risk, unverifiable track records and more.
• The Trading Bot Passive Income Myth
  Why passive income from a trading bot is a myth: adversarial markets, regime-dependent edges, overnight drawdowns, taxes, and what a bot honestly is.
• UBI and AI in 2026: Where the Debate Stands
  The UBI debate as AI displaces work: arguments for and against, what pilots suggest, and why people reach for ownership while policy stalls.