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 short indicator note introduces William Blau’s double-smoothed stochastic, attributing it to a 1990 article. It identifies the calculation’s inputs as the current close, the lowest low and highest high over a lookback period, and exponential moving…
This beginner’s guide explains futures grid trading bots, which place long and short orders at preset price levels around a contract price. The approach aims to capture repeated movements within a range by systematically buying and selling, rather than…
The document describes Temporal Routing Adaptor (TRA), a way to extend a stock prediction model so it can learn from different patterns in market data. It notes that momentum and reversal behavior may coexist, which challenges the assumption that…
The document answers how to allocate weights across strategies in a multi-strategy backtest. Its proposed workflow is to extract each strategy’s daily return series and use an optimization package to find portfolio weights. This frames the task as portfolio…
Qlib separates forecasting signals from portfolio construction. A strategy turns prediction scores into trading decisions, while a weight-based base class lets users specify target holdings and delegates order generation to the framework. The documented…
This Chinese-market stock screen combines three conditions: turnover between 3% and 12%, an opening price within 5% of the 10-day average closing price, and more than two limit-up days during the past 10 days. It is aimed at finding active stocks whose…
This post proposes screening stocks that have at least two limit-up sessions within 500 days and five moving averages described as overlapping. It interprets the moving-average condition as a possible sign of nearby support and resistance, and repeated…
This post describes a screen for Chinese A-share stocks in the metaverse industry that appeared on the previous day’s trading leaderboard. It adds a moving-average condition using five periods: 5, 10, 20, 30, and 60 days. The example formula checks whether…
This Chinese-language post outlines an equity screening rule that combines MACD above zero with a candlestick-pattern condition and a company characteristic. It presents the combination as a way to identify stocks with upward trend potential, while warning…
The article explains how leveraged perpetual futures positions can be liquidated when traders fail to meet maintenance margin requirements. It treats liquidation data as forced buy or sell order flow that may reveal short-term market pressure, and describes…
The document introduces a color-histogram implementation of William Blau’s Q-period Stochastic Index, an indicator described in his book on momentum, direction, and divergence. It identifies the indicator’s general form and points to a smoothing-algorithm…
This expert advisor monitors open positions across symbols and magic numbers. After a position has been open for a configurable number of seconds, it checks whether profit has reached a configured threshold in points. If the threshold is met, the advisor…
The document explains a trend indicator attributed to Andrew Abraham’s 1998 article. It defines trend direction using a trailing level built from a weighted average of true range. True range is the largest of the current high-low range and the gaps from the…
The expert advisor combines MACD divergence with stochastic confirmation and Bollinger Band trade exits. For buys, the stochastic main line must be above its signal line and remain within the configured oversold range for a specified candle period. The sell…
This short listing describes XWAMI_HTF, a version of the XWAMI indicator with a selectable chart timeframe in its input settings. The example default is a four-hour period, indicating that users can choose the timeframe on which the indicator operates. It…
This article outlines factors to assess before depositing token pairs into a decentralized exchange liquidity pool. Liquidity providers receive a share of swap fees, generally represented by redeemable pool tokens, and some pools may also distribute…
This example describes a concentrated long-only stock portfolio built through a sequence of AI agents. A research agent ranks companies for understandable businesses, cash generation, and attractive prices. A second agent challenges each idea by examining…
This proposed A-share stock screen combines market activity, company size, profitability, and recent price action. It selects stocks with turnover between 3% and 12%, market capitalization below 10 billion yuan, positive income, and at least one limit-up…
This code excerpt implements three filters intended to support spread trading and risk adjustment. The correlation filter calculates rolling correlation between the first two series, rescales it to a zero-to-one range, and uses changes in that measure to…
This Chinese course listing outlines a study of A-share stocks that reach their daily upper price limit. Its stated sequence is to explain the limit-up mechanism, classify limit-up events, examine subsequent stock returns, and then apply a support vector…
This document describes a chart indicator that displays trend direction and trade signals derived from the UltraWPR indicator on a selected bar. It uses a colored background: pale shades mark trend continuation, while brighter shades distinguish buy and sell…
This proposed stock screen combines amplitude above 1, institutional participation, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and at most 100%. The final criteria specify institutional participation above…
This post proposes screening A-share stocks for turnover between 3% and 12%, market value below 10 billion yuan, scale above 200 million yuan, and no losses. It presents the screen as a way to combine trading activity, company size, and profitability, then…
This document outlines a proposed position-sizing engine for algorithmic trading. It combines Kelly sizing, which uses estimated win rate and payoff ratio, with volatility adjustment based on Average True Range and tick value. The stated goal is to reduce…