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.
28 documents
This research summary examines Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connect, comparing northbound and southbound trading and describing the traits associated with northbound holdings. It reports that flows did not reliably anticipate market…
This note proposes screening equities for intraday amplitude above 1, prior-day actual turnover between 3% and 28%, and positive net large-order flow during the afternoon. The combined filters aim to find shares showing both price movement and trading…
This market commentary connects Federal Reserve expectations and stablecoin policy news with volatility in crypto and crypto-linked equities. It focuses on Circle’s post-IPO shares, noting a sharp rise in implied volatility and short-dated call skew, then…
This strategy-sharing article describes an enhanced China Securities 150 equity approach that blends model-based stock ranking with technical timing. The universe is manually narrowed to roughly 100–300 large, liquid constituent-style stocks. An AI model…
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…
The article explains Active Fundamental Performance (AFP), a measure intended to identify mutual fund managers who select stocks well on fundamental information. For each fund, it computes the covariance between benchmark-adjusted portfolio weights, or…
This guide explains how to run a Python trading strategy backtest with LumiBot, choose a historical data provider, configure dates and sources, and review generated output. It describes ThetaData, Yahoo Finance, Polygon, custom Pandas data, and Polymarket…
This research roundup describes several quantitative finance studies. One classifies equity trades by their short-term co-occurrence with other trades and standardizes associated order imbalances into conditional order imbalance measures. These measures…
This note describes a two-stage ranking factor for equities. For each stock, it ranks the recent ten-day low-price observations through time, then ranks those values across stocks on the same date. The intended interpretation is that a larger final factor…
This podcast summary describes SOMA.finance’s plans to connect traditional finance with blockchain markets through token issuance, a decentralized exchange, and yield products. It says the platform aims to support tokenized securities and digital assets,…
This post outlines a Chinese equity screen that combines an amplitude threshold, a proxy for institutional buying, and a recent large daily gain. The intended logic is to find volatile stocks attracting institutional interest that have also shown a strong…
This document describes a Chinese A-share stock screen combining a technical condition, an earnings-growth filter, and price trend checks. The initial version selects stocks with RSI below 65, year-over-year growth in net profit attributable to…
The document describes a Chinese equities screening idea focused on stocks in the metaverse industry. It combines a price trend condition, expressed through a five-day moving average, with a condition that today’s increase in volume relative to share capital…
This weekly market note connects US inflation releases and speculation about Federal Reserve leadership to moves in gold, bonds, and crypto. It interprets mixed producer and consumer inflation readings, resilient employment, and possible political pressure…
This reference surveys machine-learning methods and relates them to investment research tasks. It covers linear and logistic regression, naive Bayes, nearest neighbors, support vector machines, decision trees and ensembles, neural networks, sequence models,…
This research summary compares high-frequency factors built from minute data in stocks and futures. It groups signals into return-distribution measures, intraday volume patterns, price-volume relationships, order-flow measures, and trend strength. Reported…
The post presents a Chinese equity screen combining daily price range, a ranking based on net large-order activity, and a minimum market-capitalization condition. Its stated rationale is to find stocks with notable volatility and trading activity while…
This podcast introduction describes a discussion with T3 Index founder Simon Ho about volatility indexes, options trading, and building an index business. It identifies Spike as an index derived from SPY options that competes with the Cboe VIX, and mentions…
The proposed daily stock screen combines three filters: price range, at least two limit-up moves within a 500-day lookback, and a selected company type. The accompanying discussion says company characteristics may relate to financial performance, while…
The article describes a short-term stock screen for companies classified in the metaverse theme. It selects stocks that appeared on the previous day’s trading leaderboard and had turnover between 2% and 9%. The stated rationale is to combine a current…
This Chinese stock-screening note combines a turnover-rate band of 3%–12%, three consecutive declining sessions, and a weekly moving-average condition involving the 30-week average. It presents the conditions as a way to find stocks with a longer-term upward…
The document summarizes an equity factor study on whether analyst attention predicts future company fundamentals and stock returns. It proposes adjusting a conventional analyst-coverage measure with a linear regression that removes effects associated with…
This research summary argues that factor returns can vary nonlinearly and across groups of stocks, so a single linear factor relationship may miss meaningful differences. It contrasts direct nonlinear transformations, which can be hard to justify…
The article proposes a Chinese equity screen combining amplitude above one, a ranking by net large-order volume, and at least two limit-up events within a 500-day window. It presents volatility as a source of short-term trading opportunities, large-order…