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.
4,194 documents
This study compares time-series and cross-sectional standardization of price and volume factors in an A-share stock-selection setting. It uses a dataset spanning 2011–2022 with 98 daily factors and a five-day return label, and compares LightGBM and deep…
This Chinese stock-screening post proposes ranking shares by capital-flow strength and requiring the 9:25 opening gain to be below 6%. Its revised screening logic adds a top-100 capital-strength ranking, a price-to-earnings ratio below 20, a price-to-book…
This document proposes screening Chinese shares using turnover between 3% and 12%, a share code beginning with 60, a price-to-earnings ratio between zero and 29.01, and a price-to-book ratio no higher than 3.11. It presents the rules as a mix of trading…
This Chinese-language forum post addresses two data needs in quantitative stock research: constructing weekly bars from daily observations and obtaining historical quarterly financial measures such as return on equity. It outlines grouping daily data by…
This report summary describes a fund-selection approach that uses portfolio holdings to estimate managers’ stock-picking and market-timing abilities. Holdings provide information for attributing and forecasting performance that is not available from fund net…
This stock-screening strategy combines price movement, company size, profitability, and chart structure. It seeks stocks with daily range above 1%, market capitalization no greater than 10 billion yuan, positive net profit in each of the latest four…
The document presents a framework for testing stock-selection factors. It evaluates each trading day’s stock factor values against returns over subsequent holding periods, aiming to show how predictive information changes as the holding period grows. Daily…
This research summary examines where mutual fund excess returns may come from, separating security-selection skill from timing skill. Timing is framed as adjusting a fund's market beta, with stronger exposure during rising markets and reduced exposure during…
The document proposes screening A-share equities for turnover between 3% and 12%, circulating market capitalization below 10 billion yuan, no reported losses, and a share price below 12 yuan. It frames the rules as a way to identify lower-priced, smaller…
The post proposes a Chinese equity screen for companies classified in the metaverse industry. It combines a volume-ratio band above 1.5 and below 6 with a KDJ bullish crossover. The author then expands the proposed screen to favor stocks with forecast profit…
This strategy forms a long-short equity portfolio by ranking stocks on trailing returns, buying the strongest group and shorting the weakest. The ranking uses a twelve-month lookback while skipping the most recent month, a common way to reduce the influence…
This proposed stock screen combines a daily price-range threshold, consistently high return on equity over five years, and large or extra-large buy orders during the opening auction. Its stated logic requires the combined auction buy volume to exceed the…
The document reports a single-factor study of operating-efficiency and growth measures. For six operating factors, it says the analysis used grouped portfolio net values, long-short group returns, information coefficients, and Fama–MacBeth methods. Four…
This research overview presents a workflow for building stock-selection signals from daily price and volume data. Genetic programming generates candidate factors, using rank information coefficients to target linear relationships or mutual information to…
The study summary examines whether active stock selection that increases a mutual fund portfolio’s technological similarity predicts subsequent performance. Company patent distributions are compared using cosine similarity, and a fund’s active technological…
This Chinese-language forum post raises practical questions about what factor weights from a labeling or training process represent. It distinguishes possible interpretations, including neural-network parameters, regression coefficients, and tree-based…
This note outlines a screen for Shenzhen Main Board equities using price amplitude above 1, MACD crossing above zero, positive price-to-earnings below 29.01, and positive price-to-book below 3.11. The intended combination pairs a volatility filter and a…
This stock-selection screen combines a short-term technical condition with valuation and historical dividend filters. It selects Shenzhen Main Board shares with a 14-period RSI below 65, positive price-to-earnings and price-to-book ratios below stated upper…
This Chinese-language post describes a stock screen that combines recent buying activity with company and valuation filters. It seeks stocks with a positive daily accumulation measure, positive large-order net flow for several consecutive days, market…
This Chinese-language post proposes screening stocks by combining a minimum daily trading range, sustained return on equity, and an upward price trend. The stated rule calls for a range of at least one, ROE above 15% for five consecutive years, and a weekly…
This stock-selection concept combines a price-range condition with weekly MACD and valuation filters. It targets Shenzhen main-board shares with an amplitude above 1, a weekly MACD above zero, a price-to-earnings ratio from 0 to 29.01, and a price-to-book…
The article argues that quantitative trading depends on market understanding as well as technical implementation. It contrasts trend-following and mean-reversion approaches as examples of strategies grounded in different views of market behavior, and…
This Chinese stock-selection post describes a screen for main-board shares with turnover between 3% and 12%, a daily gain above 1%, and return on equity above 15% in each of the most recent five years. It combines recent market strength and trading activity…
This forum post presents a Chinese stock strategy that reportedly produced backtest trades but no live signals. Its example queries daily stock factors for non-ST, non-suspended companies outside specified listing sectors, then applies filters for minimum…