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
The document briefly describes a grid trading bot and says its stop loss is set at ten times the take profit. It mentions that the strategy uses four inputs, but does not identify them or explain the entry criteria, grid spacing, position sizing, or exit…
The document reports a single-factor study of operating-efficiency and growth measures. For six operating factors, it says the analysis used grouped portfolio net values, long-short group returns, information coefficients, and Fama–MacBeth methods. Four…
This beginner-oriented guide distinguishes algorithmic trading from quantitative, automated, and high-frequency trading. It describes algorithmic trading as expressing a trading idea in an algorithm that can be tested and then executed manually or…
This research overview presents a workflow for building stock-selection signals from daily price and volume data. Genetic programming generates candidate factors, using rank information coefficients to target linear relationships or mutual information to…
This summary of an equity research report explains portfolio optimization as a framework for managing risk exposures, holdings, weights, turnover, and market impact while incorporating investor views. It argues that simple portfolio construction may perform…
This research tool estimates the bid and ask as separate time series, fitting local quadratic curves to each side of the quote. It reports position, velocity, acceleration, standard errors, z-scores, and an estimated turning time across three event-count…
This stock-selection screen combines a short-term technical condition with valuation and historical dividend filters. It selects Shenzhen Main Board shares with a 14-period RSI below 65, positive price-to-earnings and price-to-book ratios below stated upper…
This overview catalogs Python examples for the WonderTrader framework, including CTA strategies, futures and stock backtests, futures arbitrage, optimization, reinforcement learning, and high-frequency trading. It names Dual Thrust as a sample strategy used…
This Pine Script example combines Bollinger Band %B signals with a martingale-style position increase. It calculates %B from a moving average and standard deviation bands, enters long when %B crosses above zero, and enters short when it crosses below one.…
This document outlines an Expert Advisor that opens trades when the Delta_RSI indicator histogram changes color at a bar close. The signal colors are described as light green or pink, indicating the EA’s trend-based entry trigger. Running the advisor…
The article describes a supervised learning approach that classifies whether a stock’s closing price will be higher or lower after a chosen horizon. It smooths historical prices with exponential weighting, then uses six technical indicators—including RSI,…
This brief description introduces a trading system that uses the Average Directional Movement Index (ADX) indicator to inform decisions about opening and closing positions. It credits the trading idea to Collector and the MQL5 implementation to Vladimir…
A forum question presents Python code that tests combinations of rolling volume windows and percentile thresholds on a Chinese stock index series. The script creates a signal when average volume over a chosen window exceeds a five-year rolling percentile,…
This notebook excerpt describes evaluating multiple cryptocurrency pairs from grid-trading backtests. It filters for assets listed before May 2024, excluding Bitcoin and Ether, and examines a run made in June 2024 using May data. For each pair, it builds an…
This note proposes screening Chinese A-shares for daily amplitude above 1%, excluding names containing a Beijing reference, and selecting stocks associated with 2021. It gives formula and Python examples that calculate the high-low range relative to the low,…
The document presents an oil strategy on 10-minute bars built around a two-candle hammer-negation pattern. A first candle has its body near one end of its range; the following candle’s body must move into or beyond the prior candle’s shadow, with its body…
This Expert Advisor trades reversals in the direction of the iAnchMom indicator histogram. It generates a signal when a completed bar shows a change in the histogram's direction, making the bar close the stated decision point. The document describes the…
This research examines whether large and small order money flows predict cross-sectional stock returns. It standardizes net inflow by trading value to form separate factors, then compares stocks grouped by factor strength. The reported results show a…
This Expert Advisor generates a signal when a bar closes and the direction of the i-AMMA moving average changes. The stated strategy is therefore a reversal in the indicator’s direction, with trades driven by the change detected at bar close. The description…
This Backtrader example demonstrates how to load minute-level CSV data for a chosen date range and trading session, optionally filter records to session hours, and fill missing bars within that session. The filler can assign a configurable volume to…
The post describes a short-term stock screen combining three filters: companies classified in the metaverse sector during 2021, stocks appearing on the previous day’s trading leaderboard, and Shanghai-listed shares whose codes begin with 60. It provides…
This note outlines a Chinese equity selection approach that first limits candidates to companies with market capitalization below 10 billion yuan and no losses, then ranks them by capital strength and selects the top five by the day’s auction amount. The…
This stock-selection rule combines a 14-period RSI below 65 with three consecutive down candles and a positive one-day price return. The document describes the conditions, gives sample implementations, and frames the screen as a way to identify stocks with…
The document discusses pricing path-dependent snowball structured notes by decomposing their payoff scenarios into exotic option components and valuing them with Monte Carlo simulation or partial differential equations. It also considers how equity index…