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
The article argues that greater differences among stocks can improve the opportunity set for systematic equity strategies. When company returns, sectors, and factors diverge, models can rank securities using valuation, momentum, quality, earnings revisions,…
This article describes a Chinese stock-selection screen combining turnover between 3% and 12%, a reversal or engulfing-style price condition, and a holder-concentration threshold. Its example calculations use the day’s high and low relative to the previous…
The article outlines a Chinese equity screening rule that selects stocks whose codes begin with 60, have turnover between 3% and 12%, and did not hit the daily price limit on the previous session. It frames the turnover range as a liquidity filter and the…
The document explains stop losses as planned exits for positions that move against a trader. Long positions generally place them below the entry price and short positions above it. A stop level can follow the trading strategy, such as a level near a recent…
This is a long-only reversal strategy described for the DAX or GER30 on an hourly chart. It calculates a lower band from a 100-period moving average minus one 10-period standard deviation. A position is opened when price falls below 97.5% of that band, RSI…
This document is a QuantStats tear sheet comparing an AI trading strategy with SPY over a brief January 2026 backtest, using Yahoo data. It reports a 1% total return for each, with the strategy showing a higher annualized return estimate but also a larger…
This Chinese-language post describes a stock screen combining three signals: ranking stocks by large-order net volume and capital strength, and looking for a shortening green MACD histogram on a 15-minute chart. The author presents these filters as a way to…
This post outlines a Chinese equity screen combining amplitude above 1%, a morning-star-style price pattern, and valuation constraints: price-to-earnings between 0 and 29.01 and price-to-book between 0 and 3.11. It describes applying these filters to…
This post describes a Chinese equity screen combining a relative strength index (RSI) below 65 with circulating market value between 5 billion and 10 billion yuan. Eligible stocks are ordered by a stock-heat measure, presented as a ranking based on trading…
This Chinese-language post outlines an equity screen for stocks with daily amplitude above 1%, a robotics concept classification, and circulating market value below 10 billion yuan. Among qualifying names, it ranks the product of price change and net volume…
This paper summary describes a reinforcement-learning approach to continuous-time mean-variance portfolio selection. It frames the problem as entropy-regularized relaxed stochastic control, aiming to balance theoretical tractability with practical…
The document describes a Double Smoothed Stochastic derived from work on market cycles and presents it as an oscillator for identifying overbought and oversold areas. Its calculation first normalizes the close within a recent high-low range, smooths that…
The document presents a Chinese equity screening idea that combines a 14-period RSI below 65, a multi-candle price pattern, and indicators intended to represent institutional buying. Its stated concept is to use a technical filter alongside research or…
This market commentary argues that quiet spot trading, low realized volatility, and a steep options term structure favor a near-term short-volatility bias in Bitcoin and Ether. It notes that scheduled inflation releases and a potential Bitcoin spot ETF…
This checklist identifies conditions to inspect when an MQL4 Expert Advisor is not ready to trade or needs a basic operational review. It covers whether a symbol is available in Market Watch, whether trading is permitted for the program and terminal, and…
This Chinese-language stock-screening post combines three criteria: at least five moving averages converge, the stock was described as under major-player control on the prior day, and its dividend payout ratio exceeded 25% in 2019. The post interprets…
This Python module provides diagnostics and configuration helpers for a systematic trading system. It compares each rule’s capped forecasts and each instrument’s combined forecasts with a target average forecast magnitude, ranking the largest discrepancies…
This guide explains how to run several OctoBot instances on one computer. Each instance needs its own copied working folder for separate configuration and logs, plus a unique web interface port. The setup involves stopping the current bot, duplicating its…
The document describes a trading-platform panel that estimates the largest lot size an account can place using its available margin. It is intended to handle market and pending orders on both sides of the market, including buy, sell, pending buy, and pending…
This Chinese stock-selection rule filters for turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and stock codes beginning with 60. It provides a formula and a Python example that groups price data by code and uses…
This Chinese equity screen selects stocks with turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and up to 100%, and revenue in 2021 more than 1.1 times its 2018 level. The document supplies…
This Chinese equity screen combines price activity, a moving-average condition, and recent limit-up behavior. It looks for stocks with daily amplitude above 1, a close crossing above a short moving average, and three consecutive limit-up sessions on the…
This guide advocates planning trade risk and profit targets as percentages of account equity rather than as fixed cash amounts or pip distances. Its example compares the same 10% risk allocation on accounts of different sizes to illustrate how the dollar…
This post proposes a stock screen to run after the close. It combines a daily amplitude threshold above 1, institutional participation above 30, and a rule that excludes stocks that hit a price limit the previous day. The author frames the filters as a way…