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 beginner tutorial explains why a live trading system may need to collect its own candlestick history. Some exchanges provide candle data directly, while others may not. The author distinguishes live use from testing: the platform supplies historical…
This podcast recap discusses Rated’s work on Ethereum proof-of-stake infrastructure data. Validator assessment uses real-time and historical measures such as uptime, efficiency, and protocol adherence to give operators context for improving performance. The…
The document describes a modified Aroon oscillator intended to react more quickly to trend changes while smoothing noise. It starts from the difference between Aroon Up and Aroon Down, applies an exponential moving average, and tests a range of gain values…
The document presents a Chinese equity screen combining daily price movement, a nonempty outstanding convertible-bond name, and a sequence of seven declining sessions. It frames the amplitude condition as a measure of volatility, the bond field as a…
This post describes a basic A-share momentum screen that excludes Beijing-listed stocks and selects for daily amplitude above 1% and a closing price at the two-day high. It frames amplitude and market location as filters and the recent price high as a…
This stock screen looks for daily amplitude above 1%, a current high matching the highest high over two sessions, and an intraday low that is 4% to 5% below the previous close. The post interprets the combination as selecting volatile stocks that have…
This post presents a daily, end-of-session A-share selection rule: retain stocks with MACD above zero and turnover between 3% and 12%, then rank them by market heat. It describes positive MACD as a trend filter and heat as a way to identify stocks attracting…
This document describes a short-term A-share screen combining turnover, recent price declines, and limit-up activity. It selects stocks with turnover between 3% and 12%, three consecutive falling sessions, and more than two limit-up days within the prior ten…
The document critiques trend lines built from DeMark pivot points or Bill Williams fractals when key points are identified using only a minimum-bar rule. It proposes removing that minimum and defining a point's dimension as the smallest count of bars on…
The article proposes screening stocks for a daily price range above 1%, no limit-up close on the previous day, and a positive gain over the preceding ten days below 35%. It presents the range as a way to find more active shares and treats the prior-day…
This stock-selection screen combines turnover, order-book balance, and share price. It selects listed mainland Chinese stocks with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and a latest price below 12 yuan. The…
The document describes an indicator that compares recent volatility with a longer-term volatility baseline. It calculates standard deviations of close-to-close momentum over short and long lookback periods, then divides the short-period value by the…
This brief platform support exchange addresses why a historical-data call for the CSI 300 index is not recognized. The response says the newer backtest engine retrieves data through SQL and suggests using the platform’s data interface to obtain index data…
The essay cautions against treating a single factor as a reliable cause of an investment outcome. It uses stock reactions to restructuring announcements to show that the same news can be welcomed in a bull market and ignored or sold in a weak market. It also…
This document outlines a Chinese-equity screen requiring a stock to belong to the metaverse theme, have positive net buying attributed to major participants during the auction, and show a KDJ K value below 20. The post interprets the KDJ threshold as a weak…
This document describes an intraday screen for Chinese equities. Its stated filters are turnover between 3% and 12%, at least one limit-up event in the previous 25 days, and exclusion of special-treatment stocks. It aims to identify candidates before 10 a.m.…
This screen looks for metaverse-related stocks whose turnover is between 3% and 12% and whose candles have closed down for seven consecutive sessions. The document describes the setup as a way to find companies in the metaverse theme after a sustained…
The proposed screen selects stocks with turnover between 3% and 12%, a positive product of the daily price change and net volume attributed to very large orders, and a close above the Bollinger upper band. Its stated rationale is to combine active trading…
This system combines the direction of an X-day average of closing prices with price comparisons over two lookback intervals. A buy setup requires the average to be higher than it was Y days earlier, while the latest close is below its level Y days earlier…
This stock screen targets companies classified in the metaverse industry. It selects shares where the KDJ indicator has just crossed upward and turnover is between 2% and 9%, with eligible securities checked before 10 a.m. for that day's trading. The…
This note proposes screening Chinese stocks for prior-day trading-list appearances with buy amounts greater than sell amounts, an amplitude threshold, and membership in a beverage or alcohol-related industry. It presents the combination as a way to capture…
This note describes a short-term Chinese stock screen using three conditions: amplitude above a stated threshold, a rising-bottom pattern, and more than two limit-up days within a ten-day window. Its stated rationale is to find shares with strong recent…
This Chinese stock-screening note combines a 14-period RSI threshold below 65 with a recent candle pattern, then ranks qualifying shares by auction value and selects the top five. The stated rationale is to pair a technical condition described as oversold…
This article outlines a process for developing equity selection rules, from finding market examples and forming a hypothesis to implementing factors, running an initial backtest, reviewing losses, and deciding whether to adjust the logic. It proposes several…