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.
5,922 documents
This post outlines a monthly small-cap stock strategy. On the first trading day of each month, it excludes ST-designated stocks and listings on the STAR Market and Beijing Stock Exchange, then invests equally in the 30 stocks with the smallest market…
The document introduces tactical asset allocation (TAA) as a systematic, relatively low-frequency approach to adjusting a diversified portfolio. It contrasts TAA with both buy-and-hold investing and short-term trading, and describes potential benefits such…
This Chinese A-share selection concept ranks stocks by money-flow strength and limits the universe to companies listed after 2021. Its proposed final screen adds market capitalization above 10 billion yuan and positive profitability. The stated rationale is…
This Chinese-language announcement outlines a community session devoted to building FinRL agents and comparing reinforcement-learning algorithms for quantitative investment. Its educational agenda covers how the DRLAgent class wraps different algorithms…
The document explains how factor-based Smart Beta products can serve investors seeking diversified equity exposure and can act as underlying holdings in fund-of-funds portfolios. It describes the approach as using passive strategies that increase exposure to…
This Chinese-language account describes a learning project that builds a China stock selection strategy with five ranked factors and a two-day forward price label. It trains a Ridge regression model, standardizes the inputs, and periodically retrains before…
This report examines the predictive accuracy of a structured multi-factor risk model for China A-share portfolios, building on earlier work on style-neutral portfolio optimization. It reports that a bias test found statistically significant evidence related…
This stock screen combines three conditions: a company is associated with the metaverse concept, its current close is above the previous day’s low, and a measure called today’s control or main-fund inflow exceeds a threshold. The article presents the price…
The document describes two measures of active fund manager ability based on whether a manager’s holdings or portfolio changes resemble those of historically capable peers. The holdings measure assigns stocks a quality score from the weighted skill estimates…
The document summarizes lifecycle fund design through human-capital theory and liability-driven dynamic asset allocation. Under stated assumptions, it says an optimal glide path can be derived analytically, and discusses how design factors affect the path.…
This strategy ranks constituents of the CSI 300 by their trailing 12-month dividend yield and selects the ten highest-ranked stocks. It updates the target list on the first trading day of each month, sells names that leave the selection, and buys newly…
The report extends a single-asset drawdown adjustment approach to portfolios of strategies. It describes selecting the control parameter gamma directly from the single-dimension result, avoiding Monte Carlo optimization for the multidimensional case. The…
The article explains recurrent neural networks and LSTM gates, then outlines an A-share stock-selection example that predicts five-day returns from sequences of seven factors. It describes missing-value handling, outlier filtering, standardization, and…
The document describes a China equity index enhancement approach that combines a multi-factor return forecast with portfolio constraints. Candidate factors span size, valuation, growth, profitability, technical signals, liquidity, and volatility. Symmetric…
This introductory guide recommends spreading a crypto portfolio across multiple tokens and varying allocation sizes. It frames diversification as a way to avoid relying on a single asset and suggests researching a project’s market capitalization, roadmap,…
The document outlines a framework for allocating across asset classes according to macroeconomic trends. It first identifies whether individual indicators are rising or falling, using historical averages or filtering, then compares asset returns over the…
This overview surveys a broad set of quantitative approaches, describing their basic mechanisms and the market settings or investor capabilities they may suit. It covers trend following, machine learning, arbitrage and market neutral methods, factor…
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…
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…
The post asks how to adapt a portfolio-selling routine so that, when the equity allocation exceeds 60% of total portfolio value, the excess exposure is sold from the lowest-ranked holdings. The supplied routine builds a set of currently held securities,…
A short VeighNa community discussion asks whether performance statistics are calculated from total account capital or from the capital associated with the traded instrument. The poster observes that when starting capital is large relative to fixed order…
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 introduces quantitative investing as an approach that uses numerical models to build an investment process, contrasting it with methods that rely more on qualitative judgment. It describes how quantitative methods can combine computing with…
This portfolio overlay begins with CSI 300 constituents whose index weights exceed 0.35%. At the start of each month, it measures each eligible stock’s return over the previous 21 trading days, approximately one month. Stocks with positive returns are…