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 note tests an A-share stock screen inspired by a “Beautiful 50” concept. It selects companies using three annual-report criteria: net profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below…
This Chinese equity screen selects stocks using three filters: an amplitude threshold, previous-day actual turnover between 3% and 28%, and a ten-day price gain between 0% and 35%. The stated intent is to combine recent price behavior with trading activity…
This MetaTrader chart utility saves periodic image snapshots into folders named for the trading pair. It chooses a capture interval based on the chart timeframe, with separate defaults ranging from frequent captures on minute charts to less frequent captures…
This Chinese stock screener combines a daily range filter, afternoon large-order net inflow, and a ratio of aggressive buying volume to selling volume above 1.3. Among stocks that pass, it proposes selecting those with the strongest recent price gains. The…
This brief description outlines an Expert Advisor that uses a TSI-MACD oscillator. It says the EA generates a signal when a bar closes and the indicator’s cloud changes color. The document also notes that the indicator file must be installed in the…
This stock screen selects shares using three stated conditions: a price-range measure above one, a 2019 dividend payout ratio above 25%, and three consecutive limit-up sessions ending the previous day. The article interprets these filters as combining…
This code example shows a scheduled strategy that checks for its first trading iteration, creates a forex asset using a configurable currency symbol, and submits a buy-to-open order for a fixed quantity. Its daily sleep interval means the strategy is…
This example configures a Backtrader strategy with simple moving average and MACD indicators, then runs an optimization over ranges of their periods. A CSV feed and date bounds define the input data, while command-line settings let the user adjust parameter…
This workflow demonstrates an equity prediction pipeline using CSI 300 constituent data, Alpha158 features, and a multilayer perceptron. It defines training, validation, and test periods, prepares constituent-filtered data, normalizes features using robust…
This note addresses a mismatch in factor analysis: a prediction set has been restricted by strategy conditions, so only a small number of stocks receive scores, while the analysis module still expects broad market coverage. The suggested response is to skip…
The document describes an automated EUR/USD strategy that uses a moving-average crossing on a 15-minute chart to enter trades. A 50-pip noise filter is intended to avoid reacting to small price moves. The stated setup uses a 350-pip take-profit and a 20-pip…
This community post describes a discrepancy between a CNN-based stock strategy's backtest and simulated-trading signals. With a rolling window of five, both reportedly signal the same stock on January 4. With a window of ten, the simulation notification…
This stock-selection screen combines a daily price-range filter, a minimum prior-day trading-value threshold, and a negative MACD histogram reading from two sessions earlier. The article presents the range and trading activity conditions as ways to find…
This document explains how OctoBot’s Python codebase is organized as a monorepo. It describes the repository root as housing the main program initialization and community data management, while separate packages handle trading and exchange connections,…
This document describes an experimental variation on the Schaff Trend Cycle indicator. The conventional indicator applies a stochastic calculation to the MACD line to create a cyclical oscillator intended to smooth short-term fluctuations while responding to…
This stock-selection idea combines three signals: a stated daily increase in holdings above 5%, a recent institutional buying or bottom-fishing signal, and an upward-sloping 30-day moving average. The accompanying discussion interprets the first two as signs…
The document outlines a Chinese stock screening and trading strategy that targets shares which closed at the daily limit-up on each of the previous two days. Candidates must trade above their five-day moving average, have a price-to-earnings ratio of roughly…
A user reports that a VeighNa spread backtest loads no data after changing an example notebook from bar mode to tick mode. The database’s tick overview shows records for both futures legs, but debugging finds no rows when the SQLite query filters by a leg’s…
This research explores whether online search interest can serve as a timely measure of investor sentiment and help identify shifts between large-cap and small-cap Chinese equities. It treats search activity related to each style as a sentiment proxy,…
This exchange asks whether MACD components and a short-window swing-volatility feature used in model training and prediction contain future information. The response says these factors are calculated from historical data, implying that the indicators…
This script outlines a FinRL training workflow for stock trading. It reads training data, derives the stock universe size and state-space dimensions, and configures a stock-trading environment with technical indicators, transaction costs, initial capital,…
This Expert Advisor uses the relationship between moving averages calculated on two timeframes. When the current timeframe’s average crosses the higher-timeframe average upward, it signals a long entry; a downward cross signals a short entry. A new signal…
This brief support note answers when a newly purchased position’s cost information appears in BigQuant. It distinguishes three operating modes: backtests and simulated trading update the value after the market close on the trade date, while live trading…
The document explains how LumiBot uses historical data from an Alpaca account to backtest stocks, ETFs, crypto, and US equity options. It describes credential setup and two configuration paths, then clarifies bar timing: history contains completed bars,…