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.
16,761 documents
This proposed stock screen combines three conditions: the weekly price crosses above its 30-week moving average, the stock’s gain at 9:25 is below 6%, and its daily position-building ratio exceeds 5%. The article interprets the moving-average crossover as a…
This document presents an intraday long-only system for the DAX40 CFD using hourly bars. It requires the close to exceed both a 185-period moving average, used as a broad trend filter, and a 16-period moving average, used to confirm nearer-term direction. It…
This document describes a Chinese stock strategy that combines classification and regression models to forecast intraday returns. It uses XGBoost and an ensemble of machine learning models, drawing on 15 features related to overnight returns, opening auction…
This Chinese stock-selection rule requires turnover between 3% and 12%, a rising DEA indicator, and at least one year since listing. The article describes turnover as a liquidity screen and rising DEA as a signal of improving short-term direction. It…
The document explains the Crypto Fear and Greed Index as a daily sentiment gauge scored from 0 to 100. It outlines its components: volatility and market momentum or volume each contribute 25%, social media and surveys 15% each, and Bitcoin dominance and…
This intraday system trades the CAC 40 on a 15-minute chart, taking both long and short positions during a defined daytime session. Long entries require the MACD line to cross above its signal line, RSI to remain below an upper threshold, and price to be…
This document describes an hourly MACD histogram setup intended to identify trend continuation. The rules use threshold levels and the sequence of histogram highs, lows, and reversals to define potential long and short signals. For a long setup, a histogram…
This script introduces a long straddle: buying a call and put with the same strike and expiration to seek gains from a sufficiently large move in either direction. It explains that the combined premium sets the loss at expiration and the distance the…
This trading-system description uses an AnchoredMomentum indicator to generate entries when price breaks above or below the indicator’s high or low level at bar close. Positions are exited through a pending order or when the indicator changes color between…
This brief BigQuant platform note explains how to use a factor written as a SQL function and field within a strategy workflow. It distinguishes platform expression factors, described as an operator paired with a field, from SQL factors, described as a…
This research review describes a study of whether year-over-year changes in company filings contain information about future stock returns and business performance. It compares filings using four text-similarity measures, sorts stocks by similarity, and…
The report describes a weekly market-timing model based on a linear-chain conditional random field (CRF). It frames the task as inferring market direction states from observed features, with CRFs able to represent dependencies between observations and…
This document describes an Expert Advisor that generates a trading signal when a Q2MA indicator changes cloud color as a bar closes. An input setting can invert the signal direction, allowing the system to trade against the indicator’s implied trend. The…
The document compares two ways to build multifactor equity portfolios. Integration ranks securities using a combined score for all target factors and selects a subset. Mixing first builds separate single-factor portfolios, then allocates among them. The…
This Freqtrade example defines a long-only strategy using three technical indicators: Commodity Channel Index, Money Flow Index, and Chande Momentum Oscillator. It enters when the prior bar has all three indicators in oversold territory, using thresholds of…
This expert-advisor method combines Commodity Channel Index readings across four bars with open and close prices across three bars. It evaluates entry conditions shortly before a bar closes, and opens a trade only when the advisor has no existing position.…
This stock screen combines three filters: daily price amplitude above 1%, a 2019 dividend ratio above 25%, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and no more than 100%. The document describes amplitude…
This stock selection idea combines a volatility screen with trend and momentum conditions: amplitude greater than one, a weekly five-period moving average crossing above the ten-period average, and a shortening green histogram on the 15-minute MACD. The…
This overview presents a multi-factor model as a way to explain stock returns through shared risk exposures, factor returns, and stock-specific residual returns. It frames quantitative management as estimating factor behavior and managing portfolio…
This guide introduces a workflow for testing a single-asset trading strategy with a Python backtesting framework. It describes the expected OHLC data format, explains how to prepare indicators in a strategy initialization step, and shows how the strategy…
This strategy allocates a portfolio across leveraged funds tied to US stock indexes, Treasury bonds, gold, and oil and gas companies. It assigns each holding a target weight, checks the portfolio daily, and rebalances every four days by comparing each target…
This Chinese equity screening idea combines a minimum daily price range, a session low falling within a specified band below the prior close, and a positive product of percentage price change and a large-order activity measure. The stated final conditions…
This utility reconstructs an order book from a supplied sequence of market-data files and returns the market-depth state at the end of that data. It configures a backtest asset with the relevant tick size and lot size, and can optionally seed reconstruction…
This personal account explains how an equity prediction model can appear strong in-sample yet fail when applied to unfamiliar stocks or later periods. The described experiment uses fundamental and technical features, including valuation, profitability,…