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.
263 documents
The article presents a notebook-based workflow for quantitative research: obtain exchange candlestick history through an API, store and inspect it with pandas, plot price and trade-flow measures, and build a Python backtest for multiple spot or perpetual…
This A-share stock-selection idea filters for companies associated with the metaverse theme that appeared on the prior day's trading leaderboard, then ranks eligible names by the current day's auction value and selects the highest-ranked group. The article…
The proposed stock screen selects shares whose turnover rate is between 3% and 12%, that were listed in the current year, and whose actual turnover on the referenced prior day is between 3% and 28%. The article frames these conditions as a way to find…
These reading notes survey high-frequency trading from market structure through strategy and infrastructure. They describe electronic order books, the roles of investors, market makers, arbitrageurs, and directional predictors, and how market makers earn…
This Chinese equity screening idea requires a stock to belong to the metaverse theme, show positive net buying by major participants during the opening auction, and have prior-day auction turnover above 0.26. The rationale is to combine a market-theme filter…
The proposed Chinese equity screen focuses on stocks classified in the metaverse sector. It ranks them by the day’s auction amount, keeps the top five, and requires the prior day’s main-fund-flow measure to be positive. The post presents this as a way to…
The document describes a short-term forex approach that opens a position around the transition between trading days, following the direction indicated by the previous day’s candle. It also discusses a script designed to collect statistics on whether a price…
This stock screen selects A-shares with turnover between 3% and 12%, excludes Beijing-listed shares, and requires prior-day trading value above 60 million. The article argues that trading value can serve as a rough indicator of market participation and…
This Chinese community post outlines an equity screen combining three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and an appearance on the prior day’s public trading activity…
The document describes a simple Chinese equity screening rule. It selects stocks with a daily high-low range of at least one percent, turnover above two percent but below nine percent, and prior-day trading value above sixty million. The stated rationale is…
This post outlines a Chinese equity screen for stocks classified in the metaverse industry. It ranks candidates by the day’s opening-auction amount, keeps the top five, and restricts the auction price change to between -2% and 5%. The post gives…
This article explains how market orders and limit orders interact in an electronic market. Limit orders state a desired price and add available liquidity to the limit order book; market orders seek immediate execution against that liquidity and consume it.…
This Chinese-language post presents a short-term A-share stock screen focused on the metaverse industry. It combines appearance on the prior day’s 龙虎榜, a list highlighting unusual trading activity, with auction-period indicators for large and very large buy…
The document demonstrates how to adapt a simple Chinese equity strategy from the JoinQuant platform to Tonghuashun SuperMind. The example uses a five-day average: it buys a stock when the latest price exceeds the average by one percent and available cash is…
This FAQ explains how an exchange prevents a user’s orders, or orders from accounts sharing a trade group, from matching against each other. It describes the available outcomes: allow the match, expire the taker or maker order, expire both, decrement both…
This guide explains how to configure and operate a live trading node, including its core settings, client registration, cache and message bus backings, strategy configuration, and shutdown behavior. It emphasizes running live nodes as standalone scripts or…
This stock-selection note proposes screening mainland Chinese equities in the metaverse theme by current-day auction amount, taking the top five, then excluding stocks that closed at the daily limit the previous day. It provides platform formula expressions…
This Chinese-language forum exchange discusses excluding special-treatment, suspended, and delisted shares from a stock universe. A reply provides two approaches based on historical name-change records: retrieve securities available around the relevant date,…
The post describes a way to prompt a language model to produce backtest code for the SuperMind platform: provide platform-specific function documentation, spell out the desired trading logic, and warn against known invalid patterns. Its example requests a…
This article proposes screening Chinese beverage and alcohol import-export stocks for turnover between 3% and 12%, while excluding stocks that reached the previous day's upper price limit. The stated rationale combines trading activity with an industry…
This Chinese stock screen selects listed shares with turnover rates between three and twelve percent, excludes Beijing-listed stocks, and keeps stock codes beginning with 60. The article describes these filters as a way to focus on relatively active shares…
This screening rule selects Chinese stocks with turnover between 3% and 12% and year-over-year growth in net profit attributable to the parent company above 20% and up to 100%. It then ranks qualifying stocks by the day’s auction amount and chooses the first…
This community post proposes a Chinese stock screen within the metaverse industry. It filters for prior-session actual turnover between 3% and 28%, an opening-auction price move ranked among the strongest in the market, and combined net buying by very large…
This document proposes screening stocks whose codes begin with 60, keeping those with turnover between 3% and 12%, then ranking them by a measure described as capital strength. The commentary presents the ranking as a way to identify actively financed market…