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.
79,386 documents
This Chinese stock-selection example combines a minimum daily price range with price action near short and medium moving averages, a recent high-price condition, and a regression-based measure involving the spread between short and longer moving averages. It…
This example assembles a futures trend-following system on hourly data and shows how to choose among vanilla accounting, simulated market orders, and simulated limit orders. The system combines raw data, trading rules, forecast scaling and combination,…
This short VeighNa forum exchange discusses running multiple strategies on the same instrument when one strategy places orders with position locking enabled. The question asks whether other strategies sharing the same PositionHolding object also need to use…
This note proposes screening Chinese stocks for amplitude above 1, a morning star candlestick pattern, and a close above the previous day's low. The author interprets amplitude as a measure of activity and volatility, the candlestick pattern as a possible…
This note describes a Chinese stock screen combining daily amplitude above 1, a rounded price pattern, and turnover between 2% and 9%. The author presents the range as a way to find active stocks, the shape as a sign of gentler price movement, and the…
This post proposes selecting Chinese metaverse-related stocks with no more than 5.5 billion shares in free float and a positive weekly candle, described as a red bar. It interprets the candle as a sign of strengthening buying pressure and suggests that…
This post describes a Chinese equity screen that selects stocks with turnover between 3% and 12%, stock codes beginning with 60, and a positive recent change in institutional ownership. Its stated rationale is that rising institutional holdings may indicate…
This Chinese-language post proposes screening listed Chinese stocks using price movement, the presence of an outstanding convertible bond name, and a minimum listing age. It explains the intended rationale as combining trading activity with indicators that…
This weekly market note reviews Bitcoin and Ether options conditions in early December 2022 alongside macroeconomic context. It describes falling realized volatility and implied volatility, a soft volatility backdrop, changing risk reversals, and steep Ether…
The document proposes a Chinese A-share stock screen that combines a daily range filter, a recent limit-up event, and an RSI-based condition intended to identify the start of a strong upward move. It gives indicator formulas and Python-style pseudocode for…
This overview explains Hummingbot executors as components that manage order lifecycles under conditions set by controllers using market data. It lists executor categories for positions, dollar-cost averaging, grids, arbitrage, time-weighted execution,…
This note describes a Swami-style stochastic indicator associated with John Ehlers’s discussion in a March 2012 issue of TASC. The indicator displays colored zones derived from stochastic calculations and adds a generic stochastic value, described as an…
This stock-screening method selects companies classified in the metaverse theme when their closing price is above the five-day moving average and a Morning Star candlestick signal is present. The article describes the pattern as a way to identify short-term…
This automated strategy combines MACD crossovers with a 200-period moving average filter and support or resistance conditions. A buy setup requires the MACD main line to cross above its signal line below zero, price to be above the moving average, and price…
This indicator compares the direction of the USDX line with the direction of the Slope Direction Line and displays a colored pointer in a separate chart window. It marks agreement when both lines point upward or both point downward, using distinct colors for…
This post describes a simple Chinese equity screen that selects stocks classified in the metaverse industry, with a positive return condition and a stock code beginning with 60. The return test is expressed as the latest close exceeding the previous close,…
This Chinese-language post outlines an equity screen for robot-concept stocks. It combines a daily high-low amplitude threshold, a circulating market capitalization below 10 billion yuan, and a condition described as the start of a strong upward move. The…
This indicator gathers values from up to ten combinations of symbols, timeframes, and signal variants, synchronizing them to the symbol on which the indicator is installed. Its original purpose is to provide normalized inputs to a neural network, though the…
This indicator applies the Relative Strength Index to values from Parabolic SAR rather than to market prices. The author presents it as another variation in the RSI family and says it can be used in the same general way as a conventional RSI. In this…
This convertible-bond research note describes a relative-value approach based on the embedded option. It first compares implied volatility with the underlying stock’s historical volatility: relatively low implied volatility is treated as evidence that the…
This Chinese stock-selection example filters for shares with turnover between 3% and 12%, membership in a beverage and alcohol import-export sector, and a 14-period RSI below 65. The article frames the sector condition as an industry constraint and the RSI…
ATLAS Mini is a compact indicator designed to flag unusually narrow Bollinger Bands as a warning that a sharp price move may follow. It measures band width relative to the upper band, applies a square-root scaling and multiplier, then compares the result…
FactorVAE is described as a probabilistic dynamic factor model that applies a variational autoencoder to noisy market data to forecast cross-sectional stock returns. In training, an encoder-decoder uses future returns to identify posterior factors that…
FactorVAE is presented as a probabilistic dynamic factor model that uses a variational autoencoder to extract latent factors from noisy market observations and forecast cross-sectional stock returns. During training, an encoder and decoder use realized…