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
The indicator estimates the likely size of the current price leg from recent completed swings. It detects swing turns using a rolling high or low, records each leg’s percentage move and duration, and uses a weighted average, ordinary average, or median of…
This glossary introduces common measures for evaluating investments and trading strategies. It explains cumulative, annualized, and monthly returns; benchmark-relative performance; win rate and reward-to-risk; information ratio; standard deviation; alpha and…
This report summary presents a framework for converting intraday or other medium-to-high-frequency signals into factors intended to predict returns over a monthly horizon. It separates factor construction into signal generation, aggregation from intraday…
The document describes a bivariate Clayton copula as a way to model dependence between two uniform variables. It provides methods to generate dependent pairs from independent uniform draws, calculate the copula density and cumulative distribution, and…
This platform discussion addresses a reporting difference between older and newer versions of a StockRanker workflow. A user says the older version displayed feature importance and NDCG after a backtest, while those results were not visible in the newer…
This stock screen combines three technical conditions: daily price range relative to the previous close exceeds a threshold, weekly MACD is above zero, and at least one daily gain of 10% or more occurred during the latest 25 trading days. The stated…
This stock screen selects shares with daily high-low amplitude of at least 1% and turnover above 2% but no greater than 9%, then ranks candidates by a measure of trading activity or investor attention. The article's example formula uses traded amount as the…
This platform discussion describes a data-ordering problem in a quantitative feature extraction workflow. The author reports that extracted rows and the original data may be separated or misaligned instead of being grouped and ordered by stock. Applying a…
This discussion explains how a quantitative platform interprets factor weights and describes its StockRanker as a learning-to-rank model based on a gradient-boosted decision tree structure. The response says the model does not require independent factors,…
This documentation describes a function for estimating the half-life of a mean-reverting process under an Ornstein-Uhlenbeck assumption. The model represents changes in a variable as a pull toward a level, plus Gaussian noise. The half-life is a way to…
This research compares ways to construct and transform analyst-consensus forecast factors for stock selection and industry rotation. It examines expected return on equity, net profit, net-profit growth, and a two-year compound-growth measure. The approaches…
This BigQuant forum exchange addresses two questions about accessing A-share financial statement data. The first asks why requesting a prior-year return-on-equity field by adding a suffix to the current field name causes an error. The reply explains that the…
This research summary tests whether machine-generated stock-selection factors add value to established manually designed factor libraries. It uses genetic programming to evolve candidate formulas from market data, then applies random forests to turn factor…
This document outlines a research tool for recording custom single-candle patterns and searching historical or current data for similar examples. A pattern is represented by open, high, low, and close values, with an optional label such as a bullish…
The document briefly describes a linear regression channel indicator. It says the indicator stores its values in output buffers and colors the background within the channel. This makes the channel’s plotted area visually distinct on a chart and suggests the…
This product description outlines an MT5 indicator for tracking trading performance over the current broker day. It reports closed profits and losses, net results, floating profit or loss, and combined daily performance. The dashboard also includes daily…
The document describes a two-stage calculation for a TMA indicator. First, one is added to the configured moving-average period, the result is divided by two, and any fractional result is rounded up. A simple moving average of closing prices is then…
The Mean Indicator displays two reference levels: the average price across bars for the current day and the average price for the previous day. Its configurable setting is the hour used to define the beginning of the trading day, which determines how bars…
The document presents a translated Ehlers-style indicator that estimates a composite cyclical wave from closing prices. It first differences price with a two-bar lag, then applies band-pass filters at a base period and its second and third harmonics. Each…
This Chinese equity-selection note combines three filters: daily amplitude above 1%, tradable shares no greater than 5.5 billion, and return on equity above 15% across a five-year period. It frames the filters as a way to find volatile stocks with relatively…
This indicator calculates a separate historical average daily high-low range for each weekday and displays that weekday’s range around a chosen price on charts at daily or faster intervals. A multiplier widens or narrows the bands; the center can use close…
This short introductory note defines quantitative investing as using numerical and mathematical methods to describe market behavior, identify patterns, and inform investment decisions. It presents the approach as an attempt to make decisions more objective…
This implementation describes an equity pairs strategy that selects stocks with highly correlated historical returns, then compares each stock’s return with a portfolio of its selected peers. It estimates a regression coefficient during a formation period…
This note groups four risk-based portfolio approaches—global minimum variance, equal risk contribution, maximum diversification, and equal weight—within one optimization framework. The framework uses three adjustable parameters to represent the individual…