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.
8,851 documents
This article recommends using AI to study existing trading strategies instead of asking it to generate a complete system from a natural-language prompt. The proposed workflow is to select a strategy, ask AI to explain its overall logic and components, probe…
This article explains box theory as a breakout method built around a recent trading range. The upper boundary represents resistance and the lower boundary support; a move above or below a boundary is treated as a possible transition into a higher or lower…
This article describes a crypto futures framework that periodically selects liquid contracts and tunes a double moving average crossover strategy for each one. It first ranks USDT contracts by dollar trading volume, then backtests multiple fast and slow…
The document presents a trading strategy as a complete set of rules covering what to trade, how much to allocate, when to enter and exit, how to place orders, and how to respond to unusual conditions. It surveys broad strategy families and recommends trend…
This tutorial translates a closing-price trend strategy into a multi-contract crypto futures implementation. It calculates Average True Range (ATR), smooths each bar’s typical price with an exponential moving average, and forms upper and lower bands by…
This article describes a daily trend indicator that classifies a bull trend when both highs and lows rise consecutively, and a bear trend when both fall. It uses completed daily bars to avoid decisions based on unfinished data and requires at least three…
This document describes a waterfall-style trend strategy built from three lines, each formed by averaging three exponential moving averages at progressively longer lengths. It proposes going long when price is above all three lines and they are ordered…
This document presents a trend-following strategy based on Ease of Movement (EMV), an indicator combining changes in price range and trading volume. It describes EMV as a measure of price movement relative to volume: readings above zero indicate a stronger…
The document introduces relative strength as a momentum approach: compare an asset’s performance with a benchmark or similar assets, favor stronger performers, and exit holdings that weaken. It says this approach is most useful in markets with clear trends…
The document walks through a Python implementation of a Donchian channel strategy for a futures market. It defines the channel from the highest high and lowest low over a lookback period, with the midpoint between them. A close above the upper boundary opens…
The document walks through turning a trading idea into an FMZ strategy: gather closing prices, calculate short and long moving averages, define entry and exit conditions, and send orders. Its example uses a 10-period average for shorter-term direction and a…
This experimental strategy combines a short- and long-period EMA crossover with sentiment analysis of recent cryptocurrency news. It collects RSS items from multiple sources, filters and orders them by recency, and sends the technical signal, news, and…
This article introduces wavelet transforms as localized, multi-scale filters for financial price series. It explains how wavelet basis functions and their coefficients can separate low-frequency movement from faster fluctuations, then describes a simplified…
The document describes a Python framework for a futures trend strategy, organized as a class with separate modules for market decisions, order handling, account calculations, risk controls, and persistent data. Its trend signal uses price relative to an EMA…
The document introduces wavelets as localized, multi-scale filters for separating slower price movement from faster fluctuations. It demonstrates a simplified approach that applies selected coefficient sets as weighted smoothing filters, varies the sampling…
This article explains the Directional Movement Index (DMI), describing it as a way to compare directional buying and selling pressure and assess trend strength. It outlines how to derive the positive and negative directional indicators from high, low, and…
This tutorial introduces FMZ’s M language as a compact, indicator-oriented way to express trading rules. It builds a moving-average example: long entries require price and the short average to be above the long average while that average rises; short entries…
The document explains Parabolic SAR as a trend-following indicator whose stop level advances toward an extreme price using an acceleration factor. It outlines rising and falling calculations, including the initial factor, its increments when new extremes…
The article defines PBX as a set of averaged exponential moving averages and uses their relative order to identify directional conditions. Its example builds three PBX lines, each averaging EMAs at progressively longer periods. It opens a long when price is…
The article links Bitcoin’s value to adoption and investor confidence, arguing that rising prices can attract participants and strengthen the conditions supporting further gains. The same feedback can work in reverse, producing sharp swings. It suggests that…
In this podcast discussion, a crypto trader describes adapting from traditional finance habits toward crypto’s momentum and trend-following behavior. The conversation covers his path into the market, moving from spot exposure to perpetual futures, and…
This introductory article explains how trading bots apply user-defined rules to monitor markets and place trades. It outlines why the author considers crypto suitable for algorithmic trading, citing volatility, continuous market access, and the market’s…
The document describes a bearish Bitcoin options trade based on reported spot ETF outflows, a technical downtrend, and economic uncertainty. Its proposed bear call spread sells a call at a lower strike and buys a call at a higher strike with the same expiry.…
The report examines how Bitcoin’s 200-week and 50-week moving averages have behaved during bear markets. It defines qualifying bear periods as drawdowns of at least 50% lasting more than 90 days, then compares price closes, lows, and moving-average crossings…