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 sample describes a high-dividend stock-selection model for Chinese equities. The process excludes special-treatment stocks, suspended securities, and Beijing Stock Exchange listings. It then screens for larger companies by market-capitalization rank,…
This sample strategy selects Chinese equities using a dividend yield ranking alongside size and valuation filters. It first removes special-treatment stocks, suspended shares, and Beijing Stock Exchange listings. From the remaining universe, it favors…
This report surveys several approaches to allocating across asset classes: macro and cycle-based fundamentals, mean-variance optimization, Kelly-CVaR, Black-Litterman, and risk parity. It describes a macro model that separates directional forecasts from…
The document explains how Qlib’s tuner searches hyperparameters and combinations of models, trainers, strategies, and data labels. A configuration defines each tuner’s search spaces and evaluation limit, then organizes tuners into a pipeline. Users choose a…
This MetaTrader 5 Expert Advisor generates trades from an Oracle indicator that can redraw its historical signals. At bar close, it can trigger when the signal line crosses the zero level, changes direction, or crosses the indicator line, depending on the…
This indicator attempts to identify periods around a potential crossing between a shorter weighted moving average and a longer simple moving average. It marks a bullish zone when the weighted average is above the simple average while a second, smoothed…
This report describes a Chinese equity index-enhancement strategy built from a composite stock-selection signal and portfolio constraints. It combines factors spanning company size, valuation, growth, profitability, technical behavior, liquidity, and…
The document describes a short-term DAX strategy on five-minute bars that trades breaks of the prior day’s high or low during a morning window. Long entries require price above a 14-period moving average and are allowed Monday through Thursday, with up to…
This guide describes NautilusTrader’s system for turning completed backtests into interactive or static performance reports. Users can select charts and themes, include run metadata and performance statistics, and inspect equity, drawdown, monthly and yearly…
This stock-selection idea combines three filters: price amplitude above a stated threshold, actual turnover from the prior day within a specified range, and exclusion of stocks that closed at the daily upper price limit on the previous day. The document…
This brief forum exchange answers a question about where log messages go during a backtest when using the BacktestingEngine. The questioner observes that the engine stores messages in a logs collection and asks how to access them. The reply says the messages…
This index timing method fits a quadratic function to a local segment of a historical price series, using either closing prices or the average of opening and closing prices. It treats the slope at the newest fitted point as an indicator of whether the series…
This document describes an Expert Advisor that trades from signals produced by the iRSISign indicator. A signal is generated when the indicator displays a colored icon at a bar’s close. The strategy therefore uses the indicator’s signal as its entry trigger;…
This indicator overlays two kinds of bands calculated from log-transformed closing prices. The statistical bands use a rolling average and standard deviation, similar in spirit to Bollinger Bands. The regression bands use a rolling ordinary least squares…
This stock-selection rule focuses on companies in the metaverse industry that recorded at least one limit-up day during the previous 25 days. It further requires the current volume ratio to be above 1.5 and below 6, where the ratio is described as trading…
This note surveys seven pitfalls in quantitative investing: survivorship bias, look-ahead bias, storytelling, data mining, signal decay and trading costs, outliers, and asymmetric long-short payoffs. It explains how current index constituents can distort…
This Chinese equity screening approach combines three technical conditions: daily price amplitude above 1, a positive weekly histogram signal, and the 20-day moving average above the 120-day moving average. The stated rationale is that larger amplitude…
This document describes an Expert Advisor based on the 2pbIdealXOSMA indicator. It opens a trade when the indicator’s histogram changes direction, with the signal evaluated at the close of a bar. The described setup is a rules-based technical approach whose…
This tutorial demonstrates parameter optimization and result analysis using a moving average crossover strategy with separate averages for trend, entry, and exit decisions. It first applies randomized grid search across constrained parameter combinations and…
This document describes an Expert Advisor strategy that uses the XDeMarker_Histogram_Vol_Direct indicator. It opens trades when a bar closes and the indicator histogram changes direction, shown by a change in the color of its star markers. The description…
Automated trading uses software to monitor markets and place trades when predefined entry and exit conditions are met. Rules can range from simple moving average crossovers to custom strategies, with order types, timing, stops, and profit targets specified…
The document explains how the Capital Asset Pricing Model can be used to assess stock returns relative to market risk. Under CAPM, expected return is linked to the risk-free rate and the stock’s beta multiplied by the market risk premium. A regression of a…
This Expert Advisor uses the Fractal Weight Oscillator to generate signals at bar close. It buys when the oscillator crosses upward through its oversold level and sells when it crosses downward through its overbought level. A higher-timeframe indicator is…
The report outlines a framework for timing equity factors whose performance has become less stable. It first examines indicators such as valuation spreads and pairwise correlations, testing their relationship with future factor returns. It then uses a random…