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.
12,140 documents
This platform update describes additions to an expression engine for quantitative analysis. The new rolling functions calculate sums, means, standard deviations, variances, skewness, and kurtosis over a specified lookback while handling missing values. It…
This short indicator description proposes calculating a stochastic oscillator from an adaptive, averaged price series instead of raw prices. The filtering step is intended to suppress some price noise before the stochastic calculation, with the adaptive…
This stock screen selects shares with turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and prior-day actual turnover within a stated range of 3 to 28. The document frames these filters as a way to combine market activity and…
This stock-screening idea combines metaverse-sector membership, an arc-shaped price pattern, and daily MACD above zero. The document then expands the proposed conditions with Bollinger Band width below three and a 20-day volatility measure below ten. Its…
The document describes a Chinese equity screen requiring a relative strength index below 65, a daily gain above 1%, main-board listing, a robotics concept classification, and circulating market value below 10 billion yuan. It combines a momentum condition…
This document describes an Expert Advisor built around a momentum entry signal. For a buy, it scans a series of MACD readings for a transition from negative to positive, then checks that the close of a selected bar is above its moving average by a…
The study examines timing the basis between Chinese equity indices and their futures, motivated by persistent futures discounts and uncertainty for market-neutral funds. To reduce the influence of carry components such as rates, dividends, and time to…
The Alf Winner oscillator combines a price measure based on close, high, and low with volume. It normalizes that volume-weighted price against its recent range and applies two weighted moving average smoothing steps, whose periods can be adjusted. The…
The document describes a Chinese equity screen for Shenzhen Main Board stocks. It selects stocks with amplitude above 1, price-to-earnings ratios from 0 to 29.01, price-to-book ratios from 0 to 3.11, and 10-day returns above 0 but below 35. The author frames…
This stock-selection rule screens for turnover between 3% and 12%, a rising K value from the KDJ indicator, and a daily price change bounded around the previous close. The article describes these as technical and market-activity filters intended to identify…
This stock screen selects companies in the metaverse theme whose institutional-flow measure is above zero and whose 14-period RSI is below 65. The stated rationale combines exposure to a popular sector with a positive institutional signal and a momentum…
This research note studies whether stocks featured on China’s daily price-change leaderboards attract investor attention and how that attention relates to later returns. Using Sogou search index data as an attention proxy, it reports a U-shaped relationship…
This Chinese A-share screening proposal looks for stocks with daily MACD above zero and weekly MACD above zero, then ranks eligible names by a market-attention measure. The selection is intended to run after the weekly close. Its accompanying example…
This A-share stock screen combines daily turnover, a rising DEA signal, and circulating market capitalization. It seeks stocks with turnover between 3% and 12%, capitalization between 5 billion and 10 billion yuan, and an upward-moving DEA measure. The…
This post proposes a Chinese stock screen combining membership in the metaverse theme, an upward-moving 30-day moving average, and a rounded price pattern. It presents the pattern as a way to describe recent price structure and includes sample indicator…
This stock-selection rule combines three filters: amplitude above 1, a daily maximum decline between 4% and 5%, and a daily MACD value above zero. The stated rationale is to look for shares with notable price movement that have also retained a positive…
This Chinese stock-screening proposal combines a minimum daily amplitude, three consecutive limit-up closes on the previous day, and evidence of a limit-up within the prior 25 trading days. The refined criteria raise the amplitude threshold to 1.5% and…
This stock-selection rule targets equities listed in 2021, with turnover between 3% and 12%, and a 20-day moving average above the 120-day moving average. The article explains the short-over-long moving-average relationship as a trend or buy-signal filter…
The document describes a Chinese stock screen requiring daily amplitude above 1, RSI below 65, and circulating market value between 5 billion and 10 billion yuan. It presents amplitude as a measure of price movement, RSI as an indicator of overbought…
This post proposes screening Chinese metaverse-related stocks for a morning gain below 6% and a possible start of an upward move. Its technical description looks for a short moving average that was below a longer moving average and has since crossed above…
This indicator identifies possible divergences between price and a 14-period relative strength index by comparing successive local turning points. A bullish setup occurs when price makes a lower low while RSI makes a higher low; a bearish setup occurs when…
This post describes a Chinese equity screen that selects stocks with daily amplitude above 1%, a positive but below 35% ten-day return, and a price under 12. It explains the intended rationale: seek active stocks that have risen without an extreme recent…
The document describes an oscillator adaptation of the Gann High-Low Activator, an indicator attributed to Robert Krausz and described in a 1998 issue of a technical analysis magazine. It characterizes the underlying calculation as a simple moving average of…
This meetup Q&A surveys quantitative research topics, including collecting and cleaning market data, creating features, training models, and evaluating strategies through backtests. It lists possible information sources beyond price and volume, such as…