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.
79,386 documents
This Chinese A-share screening idea selects stocks whose intraday high-low range exceeds 1%, whose day low is between 4% and 5% below the prior close, and whose MACD is above zero. The rationale combines elevated volatility and a sharp intraday decline with…
This proposed stock screen selects shares with a daily high-low range above 1, three consecutive limit-up sessions as of the previous day, and at least two limit-up events during the prior 500 days. The post interprets the range as a sign of activity and the…
This proposed Chinese stock screen looks for a daily price range above 1, a ratio between 0.5 and 2 formed from the previous day’s turnover rate and the current auction volume relative to the previous day’s volume, and a current large-order accumulation…
This Chinese stock screen combines a positive MACD reading, an external-to-internal trading volume ratio above 1.3, and more than two limit-up days in the prior ten days. It ranks qualifying stocks by percentage gain, favoring recent price strength and…
This document describes an example of a multicurrency Expert Advisor that processes symbols one at a time in a loop. It uses a timer event to run trading logic independently of ticks arriving for any particular symbol, and Bollinger Band values provide the…
This example turns a CAPM regression into a monthly stock-selection process. It takes a recent window of daily returns for eligible constituents, adjusts stock and benchmark returns by a stated daily risk-free rate, and regresses each stock’s returns against…
This brief coding question outlines a way to calculate fund performance statistics from a price series. It first derives periodic returns from price changes, then uses a performance-analysis library to compute cumulative return, annualized return, Sharpe…
This screening proposal combines three conditions: price amplitude above one, a value for today’s control measure above 21, and a date in or after 2021. The description frames the first two conditions as filters for more volatile stocks and stocks with…
This stock-screening proposal targets companies in the metaverse industry that have had more than two limit-up sessions in the recent ten-day window and have just formed a KDJ golden cross. It calls for screening before 10:00 on each trading day and…
The document summarizes CapTE, a model for predicting stock movements from social media text. A Transformer encoder extracts semantic features from posts, while a capsule network is used to represent structural relationships in the text. The approach is…
This short platform discussion explains that an adjust factor is used to convert a stock’s real price into an adjusted price. Adjusted prices, including forward- and backward-adjusted series, are intended to keep price charts continuous across corporate…
This Chinese stock-screening post describes a rule based on price range, recent turnover, and limit-up frequency. Its initial description calls for an amplitude above 1, prior-day actual turnover between 3% and 28%, and more than two limit-up sessions in a…
This short forum exchange explains how to configure BigQuant’s trading engine to rebalance on a weekly or monthly schedule. For weekly scheduling, it specifies the weekly trading-day mode and a day value of 5; for monthly scheduling, it specifies the monthly…
This stock-screening rule selects shares with turnover between 3% and 12%, a seven-day falling-price pattern, and no limit-up session on the previous day. The document gives both a platform-style condition and a Python example, and explains the intended…
The document introduces Temporal Routing Adaptor (TRA), a model designed to learn multiple trading patterns from stock market data. It describes using TRA with Qlib datasets and workflows, and notes that the paper’s reproduction setup first trains a backbone…
This Chinese equity screen combines price amplitude above one, appearance on the previous day’s market top list, and a positive price-to-earnings ratio. The article interprets amplitude as a sign of short-term volatility, top-list inclusion as a possible…
This Chinese equity screen looks for stocks with price amplitude above one, an opening price near the ten-day moving average, and simultaneous bullish crossover signals from three indicators. The examples use MACD, RSI, and KDJ: MACD and KDJ cross above…
This article introduces the autoregressive moving-average model as a combination of AR terms, which use past observations, and MA terms, which represent past shocks. It describes choosing the orders p and q with autocorrelation and partial autocorrelation…
This stock screen combines three conditions: net buying today must exceed five percent, the previous day’s turnover must be above 60 million, and the ten-day price gain must be positive but below 35 percent. The document presents these as signs of buying…
The document describes an Expert Advisor that trades when the i-KlPrice histogram crosses an overbought or oversold level. A signal is confirmed at bar close, so the strategy acts on completed-bar threshold breaks rather than intrabar movement. The advisor…
The document explains that MetaTrader 5 exposes generic, loss-side, and profit-side tick values for each symbol, and that these values may not be identical. This matters when an expert advisor calculates trade size from a risk budget: using a tick value that…
The document summarizes a study that develops a probabilistic classifier to identify high-frequency trading activity from intraday order data. Using French BEDOFIH market records, the researchers engineered features describing orders, including their prices,…
The document describes three high-frequency trading approaches through an example in which an institution splits a large stock order into smaller child orders. Liquidity rebate trading detects likely follow-on orders and provides liquidity to earn exchange…
The document proposes a Chinese equity screening approach that selects robot concept stocks with daily amplitude above 1%, float capitalization below 10 billion, and no ST designation. It specifies screening before 10 a.m. and says a five-step limit-up…