Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
19,452 documents
This market commentary examines Bitcoin and Ether options alongside spot prices, macro events, and regulatory news as of April 23, 2023. It discusses dealer gamma, implied volatility, volatility risk premium, term structure, and trading flows. The author…
Smart order routing can seek liquidity across eligible order books that share a base asset and use quote assets with a fixed one-to-one exchange rate. For a submitted symbol, the router scans configured books and takes available liquidity at the best prices.…
This guide describes a workflow for exploring crypto investments: select a themed basket, compare available strategies, review each strategy's stated idea, and inspect its historical profit chart. Baskets group cryptocurrencies by a shared theme or…
This Chinese-language guide compares three configurations for a trading bot called “Wind Following”: a classic two-sided mode, a custom-multiple long-only mode, and a fast-entry, fast-exit long-only mode. It gives suggested account sizes, per-coin…
This article explains how derivatives can hedge existing crypto holdings or express views on future prices, and how market data can inform those decisions. It describes monitoring open interest and trading volume for clues about liquidity and changes in…
This brief documentation note explains a self-trade prevention rule: when orders from the same address would trade with each other, the resting order is canceled instead of being filled. The cancellation incurs no fee and does not appear in the trade feed.…
This article outlines an architecture for crypto trading agents that separates market research from order execution. A read-only market data MCP supplies prices, order books, candles, and context for an agent's analysis; a REST trading API carries out orders…
This market snapshot discusses legal and regulatory developments alongside trading conditions across centralized exchanges, decentralized exchanges, lending protocols, and blockchain networks. It describes a court ruling in Grayscale’s challenge to the SEC…
This teaching example ports a close-based trend strategy into JavaScript and extends it across multiple cryptocurrency futures symbols. It calculates an exponential moving average of typical price as a midline, computes ATR, and places upper and lower bands…
The study applies machine learning to estimate an optimal rebalancing frequency for pairs trading. It uses minute-level prices for 50 large cryptocurrencies from Binance during 2022 and 2023. For each asset pair, a simulated pairs-trading algorithm…
The support note explains liquidation in terms of account equity and maintenance margin. When positions move against a trader and account equity falls below the required maintenance level, a liquidation event occurs. This links trading losses to the…
This article explains how on-chain monitoring can help liquidity providers and DeFi teams detect contract risks and unusual pool activity. It outlines reentrancy, code flaws, and front-running as common vulnerabilities, then recommends tracking liquidity,…
This weekly digital asset review combines regulatory and product news with market indicators for Bitcoin, Ethereum, and Solana. It discusses ETF holdings and weekly flows, futures open interest across exchanges, long-short ratios, and funding rates. The…
This installment explains two parts of a spot-market strategy. Its account routine estimates total account value using available and frozen balances, marks coin holdings at the best bid, and tracks the coin share of portfolio value. If that share moves…
The document outlines a framework for monitoring stablecoin risk through price deviation from the peg, trading volume, liquidity, and transfer velocity. It explains that there is no single universal price threshold for declaring a depeg, and recommends…
The document compares crypto-backed borrowing options using custody model, borrowing rate, maximum loan-to-value, eligible collateral, borrow currency, liquidation terms, and security history. It distinguishes custodial services from non-custodial protocols,…
This market commentary links Federal Reserve expectations and geopolitical events with moves in bonds, gold, equities, and crypto. It reports that markets were pricing a greater chance of the Federal Reserve holding rates, while gold continued rising amid…
The document explains how DeFi borrowers pledge collateral worth more than their loans, creating a buffer against falling crypto prices. It discusses how lending platforms set overcollateralization ratios according to collateral risk, market conditions, and…
The article outlines buy-and-hold, day-trading, and swing-trading approaches for volatile altcoins, and describes stablecoins mainly as trading-pair assets, temporary havens, or inputs to yield farming. It distinguishes fundamental research, such as…
The document explains funding payments for Hyperliquid crypto perpetual contracts, which transfer value between longs and shorts to help keep contract prices aligned with spot. The payment direction depends on the premium of the contract relative to an…
This market recap reviews BTC and ETH options conditions around a period of rising crypto prices and an approaching halving. It compares realized and implied volatility, term structures, call and put skew, options activity, and dealer gamma. The commentary…
This midweek market recap summarizes changes in Bitcoin options conditions, with brief coverage of volatility, term structure, skew, option flows, and gamma positioning. It reports that realized volatility continued to rise, implied volatility farther out on…
This guide surveys data services that researchers and developers might use for market quotes and historical bars. It discusses Google Finance, Finnhub, iTick, and Bloomberg, describing their stated coverage across assets such as stocks, currencies, indices,…
This report studies whether DeFi lending activity in USDC, USDT, and DAI is associated with Ethereum volatility. It estimates daily volatility with the Garman-Klass method, which uses open, high, low, and close prices, then applies Augmented Dickey-Fuller…