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.
16,761 documents
This proposed screen combines a market-cap limit below 10 billion yuan, turnover between 2% and 9%, and convergence among the 5-, 10-, 20-, 30-, and 60-day moving averages. It also describes selecting stocks without losses, though the meaning of that…
This stock-selection method looks for a positive return over ten days that remains below 35%, a weekly MACD above its zero line, and an RSI below 65. The post frames the return filter as an additional screen alongside a longer-horizon trend condition and a…
This stock-selection method filters for shares with turnover between 3% and 12%, a reversal-style candlestick condition, and a weekly five-period moving average crossing above the ten-period average. The article presents the combination as a way to pair…
The document describes an expert advisor that opens trades after identifying candlestick patterns associated with bullish reversals. It reports that the system was tested on daily charts, but gives no details about the patterns, entry or exit rules, test…
This Expert Advisor builds several price patterns at different historical depths from tick movements. It encodes each pattern as a binary sequence according to whether each sampled price rose or fell, then tracks virtual trades for pattern configurations and…
The document describes an Expert Advisor that trades signals from a BullsBears semaphore trend indicator. It opens a trade when a bar closes and the indicator reverses, marked by a color change. The indicator’s compiled file must be available in the…
This stock screen looks for at least five overlapping moving averages, turnover between 2% and 9%, and a positive ten-day return below 35%. The article interprets the combined filters as a way to find shares with aligned short- and medium-term trends,…
This foreign-exchange Expert Advisor is described as using an EMA_RSI_VA indicator. It opens a buy signal when the fast line crosses upward and a sell signal when that line crosses downward. An optional position-size scaling feature increases lot size…
This note outlines a Chinese equity selection approach using three signals: RSI below 65, the latest high matching the highest high over the previous two days, and strong performance during 2021. The proposed combination uses RSI as a momentum condition, a…
This Chinese stock selection example combines a 14-period RSI below 65, prior-day auction turnover above 0.26, and a 20-day moving average above the 120-day average. Stocks meeting all three conditions are ranked by individual stock popularity. The…
The Session Reality Auditor compares a broker’s declared quote and trade sessions with observed one-minute bars over a configurable history window. For each weekday and minute, it measures how often bars appear, then reports effective sessions, declared…
This post presents a Chinese stock screen built around price amplitude above 1, MACD below zero two days earlier, and more than two limit-up sessions within ten days. It frames the combination as a short-term technical and market-sentiment filter. The final…
This document describes an Expert Advisor that trades breakouts of a channel formed by two TMA moving averages. The upper and lower trigger levels are offsets from a TMA average, set by user inputs; a trade signal occurs when a bar closes beyond the relevant…
This trading system uses a smoothed parabolic indicator whose input series is derived from X2MA moving-average values. It generates a trade signal when a large colored point appears at a bar’s close. The description indicates that an Expert Advisor…
This stock-screening proposal targets Shenzhen main-board equities with at least five moving averages converging, a price-to-earnings ratio within the stated range, a price-to-book ratio within its stated range, and a 2019 dividend ratio above the specified…
This Expert Advisor combines several moving averages across three timeframes with AC indicator readings across two timeframes. It assigns signal strength from the indicators’ states and can be configured to act on all generated signals or only on stronger…
This brief description outlines an automated trading system that uses three instances of the Parabolic SAR indicator. A trade signal is generated when the third indicator's bar closes, provided that the direction is confirmed by the trend signals from the…
This document describes an Expert Advisor that trades changes in direction identified by the VininI_Trend indicator. It offers two signal modes: entering when the indicator crosses its upper or lower levels, or entering when the indicator changes direction.…
This post proposes screening Chinese stocks with market capitalization below 10 billion yuan and at least five moving averages converging at the same time. It names the 5-, 10-, 20-, 50-, and 200-day averages, treating their alignment as a possible sign that…
The document describes a class for calculating trading statistics from trade history, including while a strategy is running or outside the strategy tester. It presents this as a way to access statistics without relying on the tester-only statistics function.…
This document describes an Expert Advisor that combines JBrainTrend1Sig signals with the cloud color from UltraRSI. In its simultaneous-filtering mode, a trade signal can form at bar close when JBrainTrend1Sig produces a signal and UltraRSI’s cloud color…
This Chinese-language post describes a stock screen combining three conditions: at least five overlapping moving averages, a named morning-star reversal pattern, and a positive but capped ten-day price gain. The pattern description calls for a bullish candle…
This rule-based swing system uses Monday’s first session open as the weekly reference. It places a limit buy one percent below that level and, after entry, sets a one percent profit target beginning on the next day. If price falls half a percent below entry,…
This document explains a market-regime indicator built on Bag-of-SFA-Symbols (BOSS). It converts normalized price windows into symbolic words using a low-pass Fourier representation and data-learned bins, then compares stretches of market history as…