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 post proposes a Chinese equity screen combining recent reported capital accumulation above 5%, prior-day evidence of major-holder control, a market capitalization below 10 billion yuan, and a no-loss condition. It frames the combination as a way to find…
The document explains how an Expert Advisor or indicator can protect communications with a server using hybrid encryption. RSA with PKCS#1 v1.5 padding encrypts a randomly generated AES session key, while AES encrypts the larger request or response payload.…
This document describes an MT5 conversion of an earlier MT4 utility for managing trade exits. The expert advisor can apply stop loss and take profit levels, lock in profits, and trail stops using methods whose details are not explained. It also supports…
This page describes a configurable expert advisor presented for mean-reversion trading, with a stated preference for major forex pairs on daily charts. It lists settings for trade size, moving averages, fractal counts, stop loss, take profit, maximum trades,…
This post proposes screening Chinese stocks for amplitude above 1, a current control indicator above 21, and identifiers beginning with 60. It frames the first two filters as ways to find volatile stocks with greater market influence, while acknowledging…
This post describes a short-term Chinese equity screen requiring price amplitude above 1, prior-day indicators of large-player control, and prior-day turnover above 8%. It interprets amplitude as a measure of movement, the control indicator as a proxy for…
This Expert Advisor checks for signals only when a new bar begins and combines the Adaptive Moving Average with the Relative Strength Index. A buy setup uses a two-stage sequence: RSI must fall below the configured lower level, set to 30 in the example, and…
This note groups four risk-based portfolio approaches—global minimum variance, equal risk contribution, maximum diversification, and equal weight—within one optimization framework. The framework uses three adjustable parameters to represent the individual…
This note proposes screening Chinese main-board stocks associated with robotics. The listed conditions are an intraday range greater than 1%, circulating market value below 10 billion, and a daily gain greater than 1%. It describes these as a mix of…
This note presents a Chinese equity screen for stocks associated with the metaverse theme. It combines positive net buying attributed to major participants during the auction with a relative-volume filter: volume is described as greater than 1.5 and less…
This note describes a main-board Chinese equity screen using turnover between 3% and 12%, a reversal-pattern condition, and a seven-day decline condition. It presents the combination as a way to find stocks that have fallen persistently while retaining…
This article explains how to build an options strategy with VeighNa’s template-based OptionStrategy module and evaluate it with historical data. Its example sells one at-the-money call and one at-the-money put on the current month’s China Financial Futures…
This stock screen selects non-STAR-market main-board equities with a 14-period RSI below 65 and a daily gain above 1%, then ranks candidates by capital strength, defined in the note as circulating market value divided by turnover. The proposed rationale is…
This Chinese stock-screening note combines three conditions: the 20-day moving average is above the 120-day average, the prior session’s 9:15 matched price was at the limit down, and today’s increase in holdings exceeds 5%. It interprets the moving-average…
This document describes an expert advisor that combines an Elliott Wave concept, fractal-based trend lines, moving averages, and RSI thresholds. It frames the price pattern as five waves in the main direction followed by a three-wave correction, and says the…
This document outlines a screen for main-board Chinese stocks associated with robotics. It selects stocks with turnover between 3% and 12%, circulating market capitalization below 10 billion yuan, and a previous closing price above its 250-day moving…
The article surveys execution algorithms by their main objective: reducing market impact, controlling total trading costs, or adapting execution to favorable market conditions. It describes TWAP as time-based order slicing, VWAP as matching execution to…
This document describes a backtest reporting framework that computes metrics over a full record and, optionally, across daily, hourly, or monthly partitions. Metric classes can be instantiated with relevant supplied parameters, then receive the record and a…
This stock screen combines three filters: daily price range of at least 1 percent, free-float market capitalization above 10 billion yuan, and a MACD reading above zero. The article frames these as measures of trading activity, company scale, and technical…
This stock selection approach screens for companies associated with the metaverse theme, positive institutional flow, trading volume above 10,000 lots, and a higher opening price. The article provides a brief rationale for each filter: thematic exposure…
This A-share stock screen combines a positive MACD reading with a favorable company-type filter and a historical dividend payout ratio above 25% for 2019. The stated rationale is to pair a technical condition with business and dividend characteristics,…
This Chinese A-share screening rule starts with price amplitude above 1 and a current control indicator above 21, while excluding Beijing A-shares. Its final proposed version adds return on equity above 15%, year-over-year revenue growth above 20%, and a…
This stock-selection screen combines three technical conditions: a 14-period RSI below 65, a daily gain greater than 1%, and a closing price above the 250-day moving average. It limits the universe to main-board stocks. The accompanying rationale treats RSI…
This note presents a short-term equity screen based on daily high-low range and turnover. It combines a range threshold above one with turnover bounds: first greater than 2% and less than 9%, then greater than 3% and less than 12%. Because the latter…