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.
31,205 documents
The indicator combines weighted averages of highs and lows to form channel levels, a Hull moving average for trend display, and relative volume to qualify breakouts. A bullish or bearish breakout is identified when price crosses a stored channel boundary in…
The Waddah Attar Explosion indicator combines the change in MACD with Bollinger Band width to represent directional momentum and volatility expansion. The MACD change is multiplied by a sensitivity coefficient and split into positive and negative histograms.…
This page describes a higher-timeframe variant of the UltraAbsolutelyNoLagLwma indicator. It adds a timeframe input so the user can select the chart period from which the indicator operates; the provided default is a four-hour period. This lets a trader view…
This Chinese-language post describes an equity screen using three conditions: price amplitude above 1%, a ten-day gain greater than zero but below 35%, and a positive institutional-flow measure. It explains these filters as seeking stocks with some recent…
This note proposes a short-term stock screen based on daily amplitude above 1, a condition described as main-force control on the prior day, and a 9:25 a.m. gain below 6%. It interprets the range as a sign of active price movement, the control measure as an…
This Chinese-language strategy note describes a stock screen combining RSI below 65, the product of price change and large-order net inflow, and bullish crossovers in three indicators, with MACD, KDJ, and DMA as examples. Its sample implementation also…
ASCTrend is a chart indicator that uses Williams Percent Range to generate buy and sell arrows. Its RISK setting controls the indicator period and shifts the thresholds used to identify signals. A signal is produced when the indicator moves from an…
This Chinese stock-screening note combines daily price movement, a morning-star style candlestick condition, and a ranking based on large-order net volume. Its example code also checks recent moving averages and requires the latest large-order net amount to…
This indicator note explains a short-term trading idea based on alternating periods of small and large price ranges. Range is treated as the distance traveled over a chosen interval, and a narrow range is described as a possible warning that a wider move may…
This stock-selection method filters for shares with turnover between 3% and 12%, a rising K value in the KDJ indicator, and a 2019 dividend measure above a stated threshold. The note presents the combination as a way to pair trading activity and improving…
V1N1 LONNY is described as a multi-symbol intraday Expert Advisor that trades breakouts during the London session. It treats the pre-London Asian range as a no-trade zone, placing buy stops above the range high and sell stops below its low. Entries use the…
This stock-selection recipe combines three conditions: amplitude above 1, a shortening negative MACD histogram on a 15-minute chart, and a prior-day 09:15 matching price described as limit-down. The author interprets high amplitude as a way to find volatile…
This Chinese-market stock screen combines a metaverse industry filter with Shenzhen main-board eligibility, valuation bounds, and a recent KDJ bullish crossover. It selects stocks with price-to-earnings ratios from 0 to 29.01 and price-to-book ratios from 0…
Adaptive Volatility Analysis (AVA) is an indicator intended to measure whether market volatility is increasing or easing. It compares a short-period exponential moving average of ATR with a longer-period exponential moving average, producing a relative…
This Chinese-language post proposes screening stocks with turnover from 3% to 12%, a rising DEA condition, and at least one limit-up session in the prior 25 trading days. It presents the approach as combining an upward technical signal with recent market…
This document outlines an automated trading strategy that compares a moving average with the Parabolic SAR indicator to generate trading signals. The expert advisor operates using the current, still-forming bar, allows only one open position at a time, and…
This Chinese-language post describes a stock selection rule using turnover and recent price weakness. It screens for shares with turnover between 3% and 12%, seven consecutive declining sessions, and a current maximum decline between 4% and 5%. The article…
This screening rule looks for stocks with an amplitude above one percent, a current high matching the highest high over two days, current volume above ten thousand lots, and an opening price equal to the high. The document frames the combination as a way to…
This indicator presents three RSI lines with different lookback periods, then smooths the first RSI line with a moving average and optionally applies a second moving average to that result. Crosses between the smoothed RSI and its second average can serve as…
This A-share screening rule combines three conditions: RSI below 65, tradable market capitalization between 5 and 10 billion yuan, and a ten-day price gain above zero but below 35 percent. The accompanying Python example calculates a 14-period RSI and…
This A-share stock screen selects names whose prior trading range exceeds a stated threshold, whose opening price is within five percent of the ten-day moving average, and whose registered province is not Beijing. The document provides example formulas and…
The document describes an indicator that combines ZigZag and Parabolic SAR values and displays the resulting points as fractal labels. It notes that the labels repaint in a way similar to the extreme points of a standard ZigZag, so displayed turning points…
This proposed Chinese equity screen uses turnover, recent price movement, and prior-day actual turnover to identify candidates. Its headline criteria specify a turnover rate between 3% and 12%, a 10-day gain above zero but below 35%, and prior-day actual…
This proposed Chinese equity screen combines a positive MACD reading, positive price-to-earnings ratio, and evidence of institutional net buying. The described filter further requires net institutional purchases to be positive and recent net-buy volume to…