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.
29,558 documents
This stock screen selects companies in the metaverse theme whose institutional-flow measure is above zero and whose 14-period RSI is below 65. The stated rationale combines exposure to a popular sector with a positive institutional signal and a momentum…
This short-term stock screen targets A-share companies in the metaverse sector that appeared on the Dragon-Tiger trading list the previous day and had a volume ratio between 1.5 and 6. The document presents the conditions as a way to find stocks with…
This account describes applying the Campisi model to attribute pure bond fund returns using portfolio holdings and a benchmark. It separates total and excess returns into four effects: coupon income, government-bond yield changes, credit-spread changes, and…
This A-share stock screen combines a turnover band with two signals of institutional activity: appearance on the prior day’s top-ten trading list and reported institutional holdings or buying. The stated selection rule uses turnover from 3% to 12%, a…
This Chinese-market stock screen combines price movement, company profitability, market capitalization, and opening-auction buying activity. It selects shares with amplitude above 1, market capitalization within the stated 10-billion limit, positive net…
This stock-selection rule combines three filters: amplitude above 1, a daily maximum decline between 4% and 5%, and a daily MACD value above zero. The stated rationale is to look for shares with notable price movement that have also retained a positive…
This Chinese A-share screening idea combines membership in a metaverse-related category, a positive return, and a money-flow strength ranking. The article’s final version adds a positive market-capitalization condition. Its example formula compares a 21-day…
The proposed Chinese stock screen filters for daily turnover between 3% and 12%, excludes Beijing-listed A shares, and selects stocks described as being controlled by major holders on the previous day. The article discusses this holder-control signal as a…
The document outlines an expert-advisor strategy that looks for a new low during a downtrend alongside an oversold RSI reading to buy, and a new high with corresponding overbought conditions to sell. Users can set the lookback period for trend conditions, a…
The article argues that a complete trading system must define entries, exits, and capital allocation. It favors coherent rules and warns against unexplained indicators or assumptions that cannot be justified. Entry and exit decisions should follow a…
This stock selection recipe combines a daily price-range threshold, a minimum level of prior-day turnover, and a signal described as institutional buying. The article frames the range and turnover conditions as ways to find shares with activity and…
The document summarizes a macro-factor framework for strategic asset allocation, illustrated with portfolios for endowments, life insurers, and public pension plans. It lays out four stages: derive macro factors from principal components of monthly returns…
This stock screen combines technical conditions with a historical dividend measure. It selects equities with at least five overlapping moving averages, weekly MACD above zero, and a dividend payout ratio above 25% in 2019. The article interprets…
This stock-selection rule screens Chinese equities for companies in the metaverse industry with a tradable float no greater than 5.5 billion shares, then considers the highest prices across the latest two days. The article presents it as a short-term,…
This module implements the bivariate Nelsen 13 copula, a tool for modeling dependence between two uniform variables. It provides the copula cumulative distribution and density, a conditional distribution, random pair generation, and a parameter estimator…
This documentation explains how a trading bot builds the set of markets it can trade. Pairlist handlers can start from a static whitelist or dynamically select pairs by measures such as volume or percentage change; subsequent filters can remove or reorder…
The document presents a stock screen combining three conditions: price amplitude above 1, a 2019 dividend ratio above 25%, and the current low below the previous day's low. It supplies example indicator logic and Python-like pseudocode for applying these…
This document describes a utility library for working with floating-point numbers in trading software. Its functions cover approximate comparisons, rounding to decimal places or increments, normalization and range mapping, clamping, safe division, binary…
This document outlines an equity screen combining a daily price-range condition, a market-capitalization ceiling, positive profits, and a price pattern described as a rounded arc. Its proposed version requires a range above 1%, capitalization below 10…
This stock-selection rule combines a minimum daily price amplitude, a bounded turnover rate, and a positive daily MACD reading. The stated rationale is to use amplitude and turnover as measures of trading activity, then use MACD as a technical filter…
This document describes an Expert Advisor that runs grid trading in finite, restartable cycles. At each restart, it selects an anchor and grid, then closes the cycle when a profit target, drawdown limit, age limit, or weekend rule is reached. The design aims…
This article describes a daily stock screen combining RSI below 65, first-level bid volume greater than ask volume, and a MACD condition from an earlier session. Its code examples also include a daily price-gain filter above 2%, so the implemented screen has…
This API reference describes actions available to deployers of builder-deployed perpetual markets. It covers registering a DEX and assets, updating oracle inputs, setting funding parameters and margin tables, configuring open-interest caps, assigning fee…
This MetaTrader 5 example demonstrates an EMA crossover Expert Advisor designed to illustrate implementation practices rather than a trading edge. It evaluates signals on closed bars and acts on a new bar, closing an existing position and opening in the…