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 retrospective contrasts rule-based stock selection with machine-learning ranking and describes backtesting as a way to evaluate a strategy on historical market data. Its central caution is that a strong fit on a small sample can reflect an irrelevant…
This document describes an expert advisor that trades using signals from the T3MA-ALARM indicator. It explains that the advisor was rewritten from an earlier MQL4 version and identifies the indicator as its signal source. No entry rules, signal calculations,…
This note describes a stock screen that combines technical conditions with a basic growth measure. It proposes selecting stocks with at least five aligned moving averages, ranking them by net large-order volume, and retaining those whose revenue in 2021 was…
This assignment turns a discretionary idea—finding concentrated holdings in recent hot industries—into a proposed equity research process. It suggests first identifying strong sectors with a sector momentum factor, then ranking stocks within those sectors…
This document describes an automated MetaTrader 5 strategy that uses an EMA envelope to trigger entries when price reaches configured boundaries. If price moves against an open position, the system can add trades at configured grid intervals, increase…
This Chinese equity screen selects stocks with daily amplitude above 1, a reversal or engulfing-style price pattern, and circulating market capitalization above 10 billion yuan. The article describes these filters as a mix of technical conditions and a size…
This expert advisor uses an unconventional MACD approach: it calculates the area of the indicator above and below its zero line over a user-selected number of bars. A reverse-signal option determines whether the resulting signal opens a buy or sell position.…
This document describes a trading expert advisor that uses the iVIDyA indicator to generate signals. It checks for a signal only when a new bar begins, then opens a position with specified stop-loss and take-profit levels. It does not use a trailing stop and…
This stock screen combines three conditions: a 14-period RSI below 65, first-level bid volume greater than ask volume, and a dividend ratio above 25% based on 2019 data. The article presents these filters as a way to combine a technical indicator, order-book…
The document explains Value at Risk (VaR) as a loss threshold for a portfolio over a specified period at a chosen confidence level. It outlines common uses, including setting risk limits for individual strategies and portfolios, comparing risk across…
This code describes a volatility-sensitive adjustment to trading forecasts. It calculates daily percentage volatility, compares it with a rolling ten-year average, and converts the normalized volatility observations into quantile ranks. A multiplier…
This post describes a stock screen combining daily price amplitude above 1, positive institutional money flow, and a 10-day return greater than zero but below 35%. Its example indicator logic aggregates positive net institutional flow across five periods,…
This post outlines a Chinese A-share screening rule using three conditions: current trading volume above 10,000 lots, an opening price above the prior close, and a positive 10-day return below 35%. It presents the volume condition as a proxy for stronger…
Gamma exposure (GEX) describes how an option’s delta changes as the underlying asset moves. The document explains why this matters in crypto options: as delta shifts, market makers may adjust their hedges, creating flows that can affect volatility and…
The document discusses how to estimate hedging costs for Chinese equity index futures. It argues that raw futures premiums or discounts need adjustment for time to expiry, convergence, and expected dividends. A dividend model and quadratic equation are…
This stock selection idea combines membership in the metaverse concept group with two technical conditions: the close is above the prior day’s low, and the KDJ indicator has just produced a bullish K-over-D cross while its J value is rising. The document…
The indicator applies Cardwell’s RSI range concept to classify market regimes. It combines price relative to a 50-period simple moving average with RSI(14) membership in a bull band of 40–80 or a bear band of 20–60; otherwise the state is neutral. The…
The document describes a short-term stock selection screen for companies classified in the Chinese metaverse theme. It combines three technical conditions—MACD signal-line crossover, a short moving-average crossover, and an additional MACD-related…
This guide explains how to turn a trading idea into a Freqtrade strategy, from generating a template to defining indicators, entry and exit signals, stop losses, and optional position adjustments. It describes how Freqtrade represents candle data in pandas…
This A-share stock screen combines three conditions: daily price amplitude above 1%, at least one limit-up event in the prior 25 days, and reported institutional buying within the past three months. The article frames the conditions as a mix of volatility,…
The document contrasts selecting stocks by relative rank with selecting them by an absolute model score. A ranking method can always choose the highest-ranked names in a universe, even when their scores are weak. The proposed alternative sets a minimum score…
This stock selection approach combines three price conditions: daily amplitude above 1, upward-diverging moving averages, and at least one limit-up event during the prior 25 trading days. It aims to find volatile stocks with recent strong price action and an…
This Chinese-language post outlines a short-term equity screen based on a large amplitude, a high same-day control reading, and a three-session limit-up sequence ending the previous day. It discusses adding filters for dividend yield relative to the market…
This short description explains an automated method for calculating price levels from the Average True Range (ATR). It sets a maximum level by adding ATR multiplied by a target parameter to the opening price, and a minimum level by subtracting the same…