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 document describes a Chinese equity screen that combines price activity and trend conditions. It looks for stocks with daily amplitude above 1%, excludes special-treatment stocks, applies a five-session closing-high rule described as a limit-up method,…
This Chinese-language report summary describes an A-share stock selection approach combining an earnings surprise proxy with the price gap after an earnings announcement. Instead of comparing reported profit directly with analyst expectations, it identifies…
The Echo Forecast indicator searches recent price history for a similar earlier pattern, then uses the price changes that followed that historical match to project a possible path forward. It compares a reference window against candidate windows in a…
This brief description outlines an expert advisor that trades at the minimum lot size and alternates between closing its existing position and opening a new one at a configurable interval. A random number determines whether the new position is long or short,…
The article examines how benchmark choice affects estimates of active mutual fund skill. It distinguishes investable index benchmarks from factor-based benchmarks, arguing that omitted common risks can bias factor-model alpha, while choosing the wrong index…
The article reviews how benchmark choice affects estimates of active mutual fund performance. It argues that factor benchmarks and investable index benchmarks are not necessarily equivalent: omitted common risks can make factor-model alpha misleading, while…
The AntiFragile EA applies a grid-like approach to EUR/USD: it places buy and sell limit orders at intervals, increasing trade size with each additional order, then relies on price reversals to close positions profitably. The stated premise is that price…
This stock-selection example screens China A-share names for three conditions: membership in the metaverse theme, a prior close at or above the 250-day moving average, and an opening auction return between negative two and positive five percent. The article…
A platform support exchange explains one reason a strategy may produce trades in backtesting but no signals in simulated trading. The strategy’s prediction start and end dates were tied to live-trading parameters, while no lookback days were requested.…
This indicator marks the high and low prices within two user-defined time intervals during a trading day. It draws those extrema as horizontal levels, which traders can use to examine breakout or pullback setups. The interval start and end times are…
This article examines how training-window length affects AI stock-selection models, comparing multi-year datasets with shorter windows and proposing rolling training and evaluation on a designated validation period. It reports that, in its experiments,…
This guide explains how a backtest engine can use trade ticks as evidence for executing resting orders, and how that behavior changes with L1, L2, or L3 market data. Trade aggressor direction determines which passive side can be filled. The guide describes…
The document presents a simplified high-frequency grid market-making approach inspired by GLFT. Rather than dynamically estimating order-arrival intensity to set spreads and skew, it uses recent price volatility to determine quote distance. Inventory is…
The document presents a two-hour strategy adapted for Brent crude, combining smoothed RSI crossover signals from the Traders Dynamic Index approach with Heiken Ashi price values and a shifted moving average of typical price. Long entries occur when the…
This proposed breakout strategy enters long after a bullish candle closes above the prior eight-bar high, or short after a bearish candle closes below the prior eight-bar low. In either direction, the candle’s body must exceed the 24-period average true…
This tutorial explains why backtests need to account for more than commissions. It separates costs into fees and taxes, slippage from the delay between a signal and execution, and market impact and liquidity effects, including bid-ask spreads. It compares…
The document presents an intraday CAC 40 strategy built around trend filters across several timeframes, from seconds to tens of minutes. It calculates position size from capital and price, then uses one-minute ATR crossovers to trigger long entries when a…
The document describes an expert advisor for detecting gaps in a broker’s historical price data for a chosen symbol and timeframe. It instructs the user to run the tool in the strategy tester with the date restriction disabled and open-prices-only modeling;…
The document describes processing Bybit’s compressed raw feed files into event data compatible with a high-frequency backtesting system. It handles order book snapshots and updates, as well as public trades, and offers two approaches: combine multiple book…
The note shows how to retrieve Chinese A-share index membership data in BigQuant and filter it for a chosen index. It reads the basic index constituent table, then selects records by the index identifier; an additional filter narrows membership to a…
The system enters when a bar closes and the EF distance indicator shows a change in the direction of its moving average. A separate Flat-Trend volatility indicator can filter entries according to whether trend force is sufficient; a configurable volatility…
The document presents a China-market stock screen that combines membership in the metaverse industry, a rounding-shaped price pattern, a daily gain above one percent, and main-board listing status. It frames the pattern and recent positive return as…
The document raises a visualization concern: a smooth backtest equity curve may conceal the size of fluctuations a strategy could experience in practice. It proposes displaying results as daily candles, including each day’s high and low, so readers can see…
This guide explains operational differences between backtests and simulated or live brokerage trading that can cause strategies to behave differently. It highlights initial account holdings, delayed or unfilled orders, missing holding-period fields, manual…