Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.
3,481 documenten
The document explains quantitative trading software as a system for turning investment rules into data analysis, strategy development, historical simulation, risk controls, and automated orders. It describes typical inputs such as prices, volumes, and…
The document outlines a screen for Chinese main board stocks that combines daily amplitude above 1, at least two limit-up events within 500 days, and a daily gain above 1%. It proposes sorting qualifying stocks by the size of the day’s gain. Formula…
This report summary outlines an investigation of how high-frequency factors behave across different periods and domains, along with an analysis of what may influence their performance. The authors say earlier work built factors from trading logic using…
This brief note explains that an MT4 drawdown calculation can be scoped by magic number and trading symbol. Those filters make the reported drawdown apply to trades associated with a particular Expert Advisor identifier and instrument, rather than…
The article presents five broad rules for surviving in equity markets: avoid borrowing to invest, do not rely excessively on technical analysis, combine macro views with industry and company research, remain humble about market uncertainty, and avoid…
This A-share commentary contrasts the time horizons and advantages attributed to institutions, quantitative firms, and short-term speculators, while arguing that retail traders often misread losses as deliberate targeting. Its practical advice is to focus…
This overview presents active quantitative management as a process of forecasting factor returns and managing portfolio exposures. It describes a linear model in which each stock’s return is associated with its factor exposures, factor returns, and a…
The article summarizes research that models mutual fund returns and performance persistence with a Bayesian dynamic panel. The model allows fund returns to have time-varying variances and covariances, autocorrelation, stochastic volatility, and measurement…
This forum exchange explains how to use a platform’s precomputed limit-up or limit-down factor in a stock backtest. The motivating problem is that adjusted closing prices cannot be directly compared with actual daily price limits, which are quoted in…
This review of Piotroski and So’s study examines whether value-growth return differences arise partly from investors’ mistaken expectations about future company performance. It describes FSCORE, a composite of nine binary signals covering profitability,…
This research report examines conditional generative adversarial networks (cGANs) for forecasting asset returns and covariance matrices, then using those forecasts in portfolio allocation. The model conditions on recent multi-asset returns and random inputs…
This brief troubleshooting post shows a trading order submission that failed with error -113. The accompanying Chinese error message indicates that no position was available. The logged request concerns selling 200 shares of a listed Chinese stock, and the…
The article gives a high-level taxonomy of nine quantitative approaches and the market effects each seeks to exploit. Trend following aims to capture persistent moves; mean reversion trades price dislocations around an average. Value and growth models screen…
This introductory note defines quantitative investing as using data and a processing method to guide investment decisions, with the aim of predicting returns consistently. It lists potential advantages: model-based decisions, historical performance that can…
This forum answer explains a workflow limitation when calculating factors for intraday futures data in BigQuant. It says the platform’s basic feature-extraction module supports stocks, while futures factor calculations require extracting market data through…
This summary describes version 3.0 of Xingye Securities’ Crystal Ball timing model, which uses activity in options on the SSE 50 ETF as a source of investor sentiment and potential leading information about the underlying. Its premise is that options…
The article presents a four-stage account of how institutions might exploit retail traders in Chinese equities: identify market themes and likely stop levels from data, display large buy orders during the cancellable part of the opening auction, short shares…
This report evaluates 56 equity factors built from Chinese A-share trading and financial statement data. It sorts stocks into ten groups by each factor, measures the next month’s value-weighted portfolio returns, and tests the return spread between the…
The document describes research that extracts information from high-frequency order-book data and turns it into two groups of factors. It says the researchers aggregate these measures into monthly signals and evaluate their stock-selection performance in…
This report reviews Chinese equity index enhancement portfolios and single-factor results for the week of March 14–18, 2022. Its portfolio construction process is described as combining return forecasts, risk controls, and portfolio optimization, with the…
The report summary challenges the traditional claim that a doji candlestick predicts a market turning point. It says tests found that returns associated with ordinary doji patterns were primarily explained by reversal effects, rather than by the candle…
The article presents five ideas attributed to an active Chinese stock trader: focus on the strongest leading shares rather than broad-market direction, buy into conspicuous strength, use small capital for flexibility, concentrate decisions in a short morning…
This report describes three Chinese equity portfolio approaches designed to compete with active mutual funds rather than broad market indices. The fund-enhancement portfolio selects funds by performance layers, uses their holdings as a universe, and applies…
This stock strategy uses KDJ oscillator divergence to identify possible reversals near 50-day price highs and lows. It describes selling when the stock reaches a new 50-day high but KDJ fails to make a corresponding high, subject to overbought readings. It…