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.
29,558 documents
This article presents a broad framework for choosing and assessing quantitative trading strategies. It recommends matching a strategy to an investor’s temperament, available time, preferred trading frequency, capital, programming skills, and goals. It argues…
This study compares ways to hedge stock holdings, motivated by investors who hold equities as a base for IPO subscriptions and want to reduce exposure to price swings. It measures hedge costs using annualized futures discounts and compares those costs across…
The article defines a bounce number as the count of price touches at the two boundaries of a range before price reaches a take-profit level. It proposes measuring these counts across a symbol’s historical price data to inform lot sizing or the number of…
This article explains how to assess a systematic futures model through test design and several complementary performance measures. It recommends testing across multiple instruments and long historical periods, and including commissions and slippage. The…
This document describes settings for an Expert Advisor and mentions tester reports for EUR/USD across a long historical period, with and without lot increases. It says stop-loss and take-profit levels are applied after a position opens, and a retry parameter…
The document describes a stock selection rule combining daily price amplitude, a weekly moving-average crossover, and the presence of an outstanding convertible bond. Its stated rationale is to consider both price trend and volatility alongside a…
This overview presents basic ways to assess broad equity-market conditions and limit portfolio exposure during potential declines. It describes moving-average crossovers as timing signals, with a shorter average crossing above a longer one treated as bullish…
This opinion piece presents stock trading as a possible independent career, emphasizing schedule autonomy, reduced dependence on an employer, access to shares in public companies, and the ability to shift attention among sectors. It argues that market…
This A-share stock selection approach looks for MACD above zero, a rising DEA line, and at least two limit-up events during the previous 500 days. It treats positive MACD and an improving signal line as evidence of strength, while repeated limit-ups identify…
This Chinese A-share screening idea combines three conditions: MACD is above zero, parent-company net profit growth is above 20% and no more than 100%, and the stock has reached the daily limit-up at least twice in the prior 500 days. The intended rationale…
The post proposes a Chinese stock watchlist screen for companies associated with beverage or alcohol imports and exports. It combines daily price amplitude above 1% with at least one limit-up event in a recent window. The accompanying indicator and Python…
The post describes a Chinese equity screen requiring daily amplitude above 1%, a positive 10-day return below 35%, and at least one daily gain of 10% or more during the preceding 25 trading days. It frames these conditions as a way to find volatile stocks…
This example describes a five-minute long-only strategy built from moving averages, Heikin-Ashi candles, and RSI. It enters when the 20-period EMA crosses above the 50-period EMA, the Heikin-Ashi close is above the faster average, and the candle is positive.…
The document describes an indicator that gathers a trading symbol’s contract, pricing, margin, swap, execution, and session settings into a chart panel. It converts many values to account currency per standard lot, flags settings that can invalidate…
This product description outlines a trading bot designed for Martingale-style trading. It lists stop loss, take profit, and trailing stop functions measured in points, plus user-defined high and low price levels. Entry can be based on tick volume for a…
This note describes a stock screen requiring daily price amplitude above 1, MACD above its zero line, and a positive price-to-earnings ratio. The conditions aim to combine elevated price movement, a bullish technical signal, and a company reporting positive…
This note presents a China A-share selection screen focused on metaverse-related stocks. Its final criteria combine a volume ratio between 1.5 and 6, turnover above 3%, a prior close above the 10-day moving average, an opening price below the prior close, a…
This stock selection note describes a screen for beverage and alcohol import-export companies. It combines turnover between 3% and 12% with prior-day trading activity above the stated 60 million threshold. The article also gives formula and Python examples…
This stock-screening method combines a 14-period RSI below 65, three consecutive bearish daily candles, and a positive daily MACD condition. The document presents the combination as a way to find shares with recent short-term weakness while retaining a…
The document proposes screening Chinese equities for three conditions: price amplitude above a threshold, the close above its five-day moving average, and a positive Morning Star candlestick signal. It presents the combination as a way to find stocks with…
The document describes a trading expert advisor built around zone-recovery hedging. It says the approach averages positions and uses a targeted take-profit line, with trades entered either manually or automatically. Its automatic mode uses a multi-timeframe…
Risk parity allocates portfolio weights so that assets contribute more evenly to total portfolio risk, rather than assigning capital according to expected returns or equal dollar amounts. The document outlines a workflow: estimate asset volatilities and…
This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…
This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…