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.
21,023 documents
This study examines whether managers of equity-focused and mixed equity funds can anticipate shifts between market styles defined by company size, and whether any apparent skill persists. It identifies funds that ranked near the top around past style…
The post outlines a rules-based stock screen using three filters: price amplitude above 1, circulating market capitalization above 10 billion yuan, and a volume-ratio range above 1.5 but below 6. It presents the combination as a way to select stocks with…
The document presents a SQL approach to estimating annualized variance for Chinese stocks. It first calculates daily close-to-close returns for each instrument, then applies a rolling 20-observation standard deviation, squares that value, and multiplies by…
The PDFma indicator is described as a weighted average or digital filter whose coefficients are derived from a probability density function. It offers floating levels, quantile levels, or no levels, with the last option enabling a slope-based mode. Color…
This Expert Advisor variant adds a configurable weekly trading window to an EA based on a Spearman rank correlation histogram. Inputs set whether interval-based trading is enabled and define the start and end by weekday, hour, minute, and second. The example…
LaguerreVolume applies a Laguerre filter to smooth volume data. The document identifies the indicator’s creators as Emerald King and t_david and notes that it was first implemented in MQL4 and published in 2007. The description offers no equations, parameter…
The article compares long and short training windows for an AI stock selection strategy and recommends evaluating each window against a fixed validation period. In its rolling experiments, extending the sample from 2005 to 2021 changed labels, factor…
This Chinese-language post sketches a stock selection approach that ranks shares by trading activity, using volume and turnover as proxies for capital strength, and also considers share price. It proposes selecting highly ranked stocks on these measures,…
The document describes momentum deviation as a variation of standard deviation that applies the calculation to price momentum rather than to price itself. It says the method is designed to use minimal CPU resources and produces values similar to standard…
This Chinese post compiles a selection of 65 titles from a much larger collection of publicly released Springer books, focusing on data and machine learning. The bibliography spans foundations such as algebra, probability, statistics, optimization, and time…
This brief installment in a multi-factor modeling series contrasts two ways of estimating factor information. It says that Barra-style models typically take factor exposures directly from fundamental or technical data, while academic approaches often…
This notebook demonstrates a Monte Carlo approach to forecasting stock prices with geometric Brownian motion. It estimates drift and volatility from historical log returns, generates many simulated price paths, and splits the price series sequentially into…
This career guide outlines a self-study path for aspiring quantitative developers. It emphasizes strong programming and numerical implementation skills, with language choices shaped by likely workplaces: C++ and Python for broad applicability, while Java or…
This stock-selection idea combines daily amplitude above 1, positive large-order net volume for at least three consecutive days, and a nonempty outstanding convertible-bond name. The post treats the bond condition as a way to identify companies that have…
This research summary reviews several quantitative approaches to interpreting China’s 2018 equity market. It reports historical analysis of rebounds in the CSI 1000, saying smaller-cap indexes tended to outperform larger ones during rebounds, while sectors…
This BigQuant framework describes a workflow for computing and evaluating minute-frequency stock factors. Researchers define factors in SQL against a specialized derived minute-bar table, assign an output table name, and run the program to calculate and…
This indicator description explains a way to display trend strength on a DecEMA moving average using standard deviation. Two input thresholds divide the reading into strength levels: when the standard deviation falls between the lower and upper thresholds, a…
This historical essay introduces John Maynard Keynes’s views on probability and uncertainty, drawing on his work in probability theory and economics. It contrasts objective probabilities, which may exist independently of human beliefs, with the estimates…
This stock-selection idea combines three filters: daily turnover between 3% and 12%, appearance on the previous day’s broker trading list, and 2021 revenue more than 10% above 2018 revenue. The post frames the conditions as a way to find moderately active…
This indicator description explains a Fractal ZigZag port that uses ZigZag logic to identify swing highs and lows, then plots or estimates a version intended to avoid redrawing. It says that values are backdrawn by two bars from the current bar, a detail…
The document introduces Occam’s razor as a preference for explanations or solutions that require fewer assumptions when they account for the same observations. It stresses that simplicity is a guiding heuristic, not a scientific law, and that evidence must…
The document describes a trading-system risk analytics tool that processes closed-trade history and reports risk and performance measures. Its stated functions include Monte Carlo simulation, Value at Risk, Kelly Criterion position sizing, and more than a…
This method estimates portfolio weights for a spread using the Box–Tiao canonical decomposition. It first reorders the price columns so the selected dependent asset comes first, demeans the data, and fits a first-order vector autoregression. It combines the…
The article surveys the development of quantitative trading through stories about Jules Regnault, Edward Thorp, and James Simons. It describes using historical price data and mathematical models to identify market patterns, Thorp’s probability-based…