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 short description explains a chart operated tool for modifying protective exits on all open orders for the current instrument. The trader drags the script’s placement relative to the current market price: below the market it adjusts stop losses, and…
This overview explains how a crypto derivatives portfolio can combine instruments with positive and negative delta to keep net directional exposure near zero. Traders may then focus on changes in implied volatility, time decay, or other option effects rather…
This screen selects equities using three conditions: daily price range above a stated threshold, a 2019 dividend ratio above 25%, and a nonempty name for an outstanding convertible bond. The article presents the combination as a way to consider price…
This stock screen targets companies classified in the metaverse industry. It looks for a fresh KDJ bullish crossover and positive large-order net-flow readings over several consecutive days, then selects a small set of candidates. The post describes the idea…
The article compares eight forex expert advisers built around Martingale or grid trading. It describes their entry filters, position sizing, grid spacing, and exit methods. Examples include trend or oscillator filters for initial trades, ATR-based spacing,…
This stock-selection proposal focuses on companies classified in the metaverse theme. It filters for prior-day actual turnover between 3% and 28% and a circulating market value above 10 billion yuan. The article explains turnover as a sign of market activity…
This article describes a short-term stock screen using four conditions: daily amplitude above 1%, current volume above 10,000 lots, a higher open, and a bullish weekly bar. It presents these as signs of active trading and upward price movement. Its indicator…
This overview outlines a quantitative workflow: collect and clean data, develop a strategy, manage risk, backtest on historical data, and automate execution. It then sketches strategies for Chinese equities and futures, including Turtle-style breakouts,…
This document describes adapting several MT5 standard trading classes for use in MT4, with the goal of sharing an Expert Advisor codebase across both platforms. It sets two constraints: the program must avoid MT5-only classes unless they are also ported, and…
This post outlines an A-share screen that combines RSI below 65, parent-company net profit growth above 20% and no more than 100%, and three consecutive declining sessions. It presents the combination as a way to identify stocks with both technical weakness…
This post proposes an A-share stock screen combining a daily price range of at least one percent with a volume ratio between 1.5 and 6. It also applies two concentration-related filters based on circulating market value and total shares. The rationale is to…
This trading-tool description argues that viewing positions and risk as percentages can help traders manage emotions and apply a consistent plan. It illustrates how traders following the same plan may make different decisions, such as holding losing…
The article describes how historical crypto options data can support market research, algorithm development, and portfolio management. It identifies implied volatility, realized volatility, open interest, put/call ratios, price and volume records, and order…
This document describes a daily stock screen for companies classified in the metaverse industry. It selects stocks with a newly formed KDJ bullish crossover and a positive price-to-earnings ratio, then limits candidates to actively trading stocks identified…
This post outlines a Chinese equities screen that selects stocks with a stated amplitude above 1, a price below 20, and positive net buying attributed to major participants during the opening auction. It provides example indicator and Python-style…
This post describes a Chinese equities screening idea intended for use before 10 a.m. It combines a price ceiling below 20, a minimum amplitude threshold, exclusion of stocks marked ST, and a five-part limit-up method. The post also offers example formulas…
This introductory guide outlines a retail trader’s path into quantitative trading. It describes using market data and mathematical models to generate decisions, learning market concepts and a programming language, building models from historical data, and…
The article argues that a factor can be useful even when its strongest information lies in identifying poor-performing stocks. It describes ranking stocks into daily groups by factor value and interpreting unusually strong performance in the worst-ranked…
The Ulcer Index is presented as a measure of downside volatility, originally devised by Peter Martin for evaluating stock market funds. The document explains its use as a trend confirmation tool: a falling index alongside rising prices suggests downside…
This strategy uses hourly candles and technical indicators to identify directional momentum. It calculates ADX, positive and negative directional indicators, Parabolic SAR, and momentum. Long entries are signaled when ADX exceeds a threshold, momentum is…
This document describes a read-only dashboard for monitoring an account against configurable proprietary trading firm risk limits. It displays balance, equity, floating profit and loss, the day's profit and loss, the share of the daily loss limit used, the…
The document describes a MetaTrader 5 dashboard for separating the results of multiple expert advisors running in one account. Each robot’s trades carry a numeric magic number, allowing the dashboard to group activity by strategy instead of relying on…
This brief Q&A explains how to change the scoring function used during hyperparameter search. The question asks how to include annualized return, win rate, and maximum drawdown alongside a Sharpe-based score. The response says the score function can read…
Dollar cost averaging (DCA) invests a fixed amount at regular intervals regardless of the current price. Because each contribution is the same size, it buys more units when prices are lower and fewer when they are higher. The article presents this schedule…