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 announcement outlines a multi-factor strategy for OKX that ranks a universe of coins by a composite factor value and divides them into three roughly equal groups. It proposes going long the lowest-ranked group and short the highest-ranked group. If…
This guide recommends six books for readers learning quantitative and algorithmic trading, describing the topics each covers and the intended audience. The selections span professional quant fund operations, system building, momentum and mean-reversion…
The report discusses using the Black–Litterman (B-L) framework to incorporate an investment manager’s judgments into a quantitative factor portfolio. It frames factor information coefficients as the return inputs and their covariance matrix as a…
This brief summary outlines several approaches to rotating among equity industries. It discusses adapting the investment clock framework from asset allocation to sector selection, while noting that macroeconomic data may be delayed or unreliable and that…
This Chinese-language post describes an equity selection screen combining a positive MACD reading, membership in a specified business concept, and a rising-bottom condition. Its example code uses the new-energy-vehicle concept and compares the current high…
This research summary explains why monthly and year-over-year macroeconomic readings can mislead when economic series contain seasonal and calendar effects. It describes X-13-ARIMA-SEATS as a widely used adjustment approach and emphasizes that seasonal…
The document describes an A-share stock screen combining a technical condition with fundamental growth and a low share-price ceiling. It selects stocks with a 14-period RSI below 65, year-over-year growth in net profit attributable to the parent company…
This market note summarizes a difficult week for major Chinese equity indexes and sectors, then reports changes in factor behavior. It says quality and analyst sentiment factors strengthened relative to the prior week, while value, reversal, and alternative…
This Chinese language literature digest summarizes research on return predictability and portfolio covariance estimation. One study examines stock prices and dividends in the Netherlands, the United Kingdom, and the United States over nearly four centuries.…
This research summary examines how broad equity factors behaved across Chinese A-share industries from July 2009 through November 2018. It links differences in factor effectiveness to industry characteristics: small-cap effects were stronger in industries…
The proposed stock screen combines daily price range, a market-capitalization ceiling, positive net profit, and a historical dividend payout threshold. Its rationale is to seek smaller companies that are profitable and return a substantial share of earnings…
This tutorial introduces two strategy-building approaches on BigQuant: an AI-driven workflow that trains a model from selected factors and filters, and a user-coded approach with explicit selection rules. It focuses on the latter, outlining how to clone a…
This document proposes a Chinese equity screen combining daily turnover, year-over-year net profit growth attributable to parent-company shareholders, and a filter excluding stocks that closed at their daily high the prior day. The stated thresholds are…
This meetup note explains factor exposure as an asset’s sensitivity to factor returns. It sketches a way to estimate that sensitivity: form a low-versus-high valuation long-short portfolio, treat its return series as the factor return, and regress an asset’s…
This article discusses practical choices when tuning a short-term stock-selection strategy: starting capital, number of holdings, capital allocated per holding, holding period, and factor selection. Its author argues that the number of names and per-name…
The document examines whether rolling Fama-French five-factor (FF5) alphas can guide U.S. sector rotation. It compares FF5 with the three-factor model (FF3), using monthly returns for ten U.S. industry portfolios from 1964 to 2014. The rotation signal is…
This document outlines a Chinese A-share stock screen combining a technical indicator, earnings growth, a thematic classification, and a size limit. It seeks robot-concept stocks with a 14-period RSI below 65, positive net profit attributable to the parent…
This stock screen combines a price amplitude threshold with a condition described as upward dispersion in the moving averages, then applies configurable company filters. The fundamental criteria can include industry, market capitalization, price to earnings,…
This stock-selection note proposes screening companies associated with the metaverse theme for three bullish technical crossovers: MACD crossing its signal line, a 5-day moving average crossing above the 10-day average, and the 5-day average crossing above…
The article summarizes research on how speculative stocks perform around earnings announcements. It measures speculative characteristics using proxies such as maximum daily return, idiosyncratic volatility, price, expected skewness, and jackpot probability,…
The article introduces quantitative trading as the use of mathematical models, statistical analysis, historical and real-time market data, and algorithms to guide or automate decisions. It describes stock screening and rule-based execution as common…
This forum post records an attempt to create an A-share factor from securities appearing on the trading ranking list, using a transaction category and several broker department codes. The submitted expression tests whether the category matches a specified…
This document presents a partial Python implementation of an Alpha101-style factor library. Its functions combine price and volume data using rolling ranks, correlations, covariance, moving averages, standard deviations, price changes, and volume averages.…
This Chinese stock-screening note combines a daily price-amplitude threshold, a Morning Star candlestick condition, a market-cap ceiling of 10 billion yuan, and positive net profit after extraordinary items. It frames the combination as joining a technical…