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.
28 documents
This article describes an AI-assisted crypto trading workflow that combines scheduled market analysis with human approval before routine purchases. Its demonstration strategy is dollar-cost averaging: a base amount is adjusted between zero and twice that…
This platform guide describes a visual, node-based workflow for connecting market data, external information, analysis, decision logic, and trade execution. It outlines node categories for AI analysis and agents, data transformation, flow control, custom…
This beginner guide surveys six crypto approaches: long-term holding, intraday trading, scalping, swing trading, RSI-based trading, and avoiding pump-and-dump groups. It presents dollar-cost averaging as a way to spread purchases over time, and describes…
The article presents a dashboard approach to assessing Bitcoin and broader crypto market conditions. It groups indicators into macro supply and market capitalization, capital flows, exchange balances, derivatives positioning, and on-chain or miner measures.…
The article outlines a crypto investing assistant that combines periodic market-data collection, AI-generated analysis, human approval, and exchange execution. Its example applies dollar-cost averaging to spot purchases, adjusting the baseline contribution…
The article presents a single-instrument trading system that cycles through market perception, decision, execution, trade review, and playbook updates. It structures technical indicators covering trend, momentum, volatility, and volume, and combines that…
The document describes a two-sided BTC grid strategy managed by a workflow that checks market volatility before initialization and runs the grid on a recurring candle trigger. When configured position or price conditions suggest the market has moved beyond…
The article outlines an automated workflow for trading tokenized US stock contracts through a crypto platform. A scheduled process gathers account positions, news sentiment, and daily stock candles; calculates MACD, RSI, ATR, and OBV; asks a language model…
The article presents a two-part workflow for newly listed crypto perpetual contracts. A slower analysis process detects exchange announcements, tracks candidate tokens, and gathers basic token metrics, news, and derivatives data such as prices, funding…
This article describes a workflow intended to interrupt impulsive crypto trades by requiring a trader to state a reason before acting. It combines the trade idea with position information, news-based sentiment, and technical indicators such as MACD, RSI,…
The document develops the Psychological Line (PSY), an indicator that measures the share of rising bars over a lookback period, into a directional strength measure. The basic count treats every up or down bar equally, so it misses the size of price moves.…
This essay proposes assigning deterministic trading tasks to explicit rules and reserving AI for decisions that require interpretation of unstructured information. Moving-average signals, position limits, and stop-losses are presented as rule-based tasks,…
The document describes a proposed workflow intended to slow impulsive cryptocurrency trades. Before acting, a trader records the asset, direction, size, and rationale. The system combines that input with current position data, news sentiment, and technical…
This essay argues that traders can undermine their results through gambling-like behavior, uncritical trust in prominent commentators, and decisions driven by intuition without a defined plan. It explains how confident predictions can appear successful…
This article outlines a system that turns an analyst’s posts on X into potential trades in US equity perpetual futures. It proposes collecting posts through an RSS feed, asking a language model to identify explicitly named tickers and classify direction and…
The document presents a framework for assessing Bitcoin’s market cycle by combining macroeconomic measures, capital flows, exchange activity, derivatives positioning, and on-chain indicators. Examples include central-bank money supply, Bitcoin ETF and…
The document describes a pipeline that turns a financial influencer’s posts into trading signals for Binance stock perpetual contracts. It proposes collecting posts through an RSS feed, asking an LLM to identify explicitly named tickers, direction,…
The document outlines an automated crypto trading workflow split between an AI agent and a trading platform. The AI gathers price, volume, and news data, classifies sentiment, and emits a structured buy, sell, or hold signal. An executor receives that signal…
The document describes a workflow for trading newly listed crypto perpetual futures. It separates slower analysis from rapid launch monitoring: an analysis process tracks exchange announcements, gathers token fundamentals, news, and cross-exchange market…
The document outlines an automated workflow for combining cryptocurrency market data and news into recurring trading reports. It collects candlesticks across 15-minute, hourly, and daily intervals, standardizes and merges them, and retrieves recent articles…
This experimental crypto strategy combines short- and long-period exponential moving average crossovers with sentiment analysis of recent RSS news. It filters headlines to a recent time window, packages news, crossover direction, and current position…
This article presents an automated strategy for binary event contracts on Polymarket. A scheduled workflow first filters markets by liquidity, activity, spread, and price range, then examines hourly candles for patterns such as gradual price advances, rising…
This guide describes a proposed spot crypto trading workflow in which an AI agent gathers price, volume, and news data, forms a buy, sell, or hold decision, and sends a structured signal to a separate execution platform. The execution service listens for…
The document introduces FMZ’s visual workflow system as a way to connect market data, analysis, signal generation, risk controls, and order execution. It describes a modular approach in which users combine prebuilt nodes, external data requests, AI analysis,…