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.
22,592 documents
This note outlines a Chinese stock selection screen that combines a reported daily increase in buying participation above five percent, Shenzhen main-board membership, specified price-to-earnings and price-to-book ranges, and a short moving average above a…
This note describes a Chinese equity screen combining a metaverse industry classification, a stock code beginning with 60, and an opening price near the 10-day moving average. Its indicator example expresses the condition through crossings between the open,…
This brief description presents a histogram version of the classical Relative Vigor Index (RVI). Color changes identify when the oscillator enters overbought or oversold areas, while a colored cloud between the oscillator and its signal line highlights their…
This post proposes screening Chinese A-share stocks with three conditions: RSI below 65, an external-to-internal volume ratio above 1.3, and turnover between 3% and 12%. It supplies example indicator formulas and a Python-style workflow that retrieves market…
This Chinese-language post outlines an A-share stock screen focused on companies classified in the metaverse industry. Its stated selection logic combines total assets above 200 million with an opening price near the 10-day moving average. The post also…
This stock screen selects Chinese A shares using a turnover range of 3% to 12%, excludes Beijing-listed shares, requires current volume above 10,000 lots, and includes an opening-price shape condition. The article describes the target as relatively active…
This Chinese equities screen looks for stocks with daily amplitude above one, circulating market capitalization above 10 billion yuan, and an outside-to-inside trading ratio above 1.3. The post describes amplitude as a proxy for trading activity, company…
This Chinese equities screening idea combines stocks with an amplitude above one, evidence described as main-force control on the prior day, and an engulfing or reversal pattern. The post frames these conditions as a way to find actively traded stocks…
The document introduces Williams %R as a momentum oscillator that locates the closing price within the recent high-low range over a chosen lookback period. Its scale runs from −100, where the close matches the period low, to 0, where it matches the period…
This student submission translates a Chinese “dragon returning” trading approach into a factor-based stock strategy. It first identifies strong sectors with sector momentum, then selects leading stocks within them using stock momentum and price-volume…
The document demonstrates how to adapt a simple Chinese equity strategy from the JoinQuant platform to Tonghuashun SuperMind. The example uses a five-day average: it buys a stock when the latest price exceeds the average by one percent and available cash is…
The document summarizes a study of dividend-focused Smart Beta strategies in Chinese equities. It argues that dividend factors show a consistent ranking pattern across the CSI 300, CSI 500, and broader market universe, with higher-dividend portfolios…
The document surveys a Chinese securities research team’s work on applying artificial intelligence to quantitative investing. It organizes that research around model evaluation, factor discovery, overfitting controls, synthetic data, and methods intended to…
The document proposes a short-term stock screen using four conditions: an amplitude threshold, a specified share price of 18.5 yuan, current volume of at least 10,000 lots, and a higher open. It describes the intended candidates as active stocks with notable…
The example shows how to use Pyfolio to create a returns tear sheet for a single stock. It retrieves daily returns for Facebook through a Pyfolio utility, then passes that return series to a tear-sheet function with a live-start date. The stated output is a…
The document describes a Chinese equity screen requiring daily price amplitude of at least 1%, circulating market value above 10 billion yuan, and a company name containing a metaverse keyword. The post frames these conditions as a mix of trading activity,…
This document summarizes a securities research report on constructing factors from high-frequency data, with a focus on combining intraday and day-level information. It frames the choice of calculation method around whether price and volume signals retain…
This essay applies ideas from philosophy of science to judging trading strategies. It contrasts testable claims, which make predictions that evidence could disprove, with claims that cannot be meaningfully tested. For strategies whose edge is inferred from…
This Chinese-language post discusses connecting BigQuant research with Guojin Securities’ QMT platform for automated live trading. Its concrete example is a stock strategy that first processes daily data to select a watchlist, then monitors those names and…
The document proposes a Chinese stock screen combining three conditions: at least five moving averages converge, the stock had a limit-up event within the prior 25 days, and the company has a market capitalization below 10 billion yuan with no reported…
This post presents a China-market stock-selection screen for the metaverse theme. It starts with stocks whose prior-day turnover exceeds 8% and whose price is above the five-day moving average. The proposed refinement also requires a MACD crossover, with…
This Chinese-language post describes a stock screen for the metaverse theme. Its initial conditions select shares with previous-day turnover above 8% and price above the five-day moving average. It then refines the screen by adding a MACD crossover…
This post presents a stock screen combining daily price amplitude, a positive weekly MACD signal, and a minimum total market capitalization. Its rationale is to look for volatile stocks with an upward weekly signal while retaining companies above a size…
This post describes a China A-share screening idea that combines a daily turnover-rate band, a beverage and alcohol industry filter, and a rising-bottom condition intended to favor stocks with improving price structure. The listed screening logic is…