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
A forum question examines whether checking an asset's tradeability during a daily backtest is useful when the resulting order may execute on the following day. The concern is that an asset deemed tradable on the signal date could be suspended by the time the…
This research note describes a method for detecting support and resistance lines in Chinese A-share price data and studying breakout behavior. It defines slope patterns for continuation formations, including triangles, rectangles, flags, and broadening…
This tutorial describes a futures order-following bot that copies changes in a reference account’s long and short positions to additional accounts. It reads the reference account’s positions, tracks long and short quantities separately, and sends…
The document presents a fixed-box Renko indicator designed to make Renko-like signals usable in ProRealTime backtests. It initializes upper and lower levels around the closing price, then shifts both levels by one box when the close crosses beyond the next…
The report examines how different types of restricted-share unlocks relate to stock performance before and after the release date. It describes supply pressure from newly tradable shares and anticipatory trading by other market participants as possible…
The document outlines a Chinese stock selection rule combining daily price movement, a price threshold, and the return implied by the opening auction. It describes screening for amplitude above 1, a close below 20, and an auction return between -2% and 5%.…
This strategy ranks stocks by their return during the month one year earlier, then buys the strongest group and shorts the weakest. It forms portfolios monthly and rebalances at month end. The described source approach uses equal weighting and a large-cap…
This roadmap outlines development work for a quantitative trading toolkit spanning Python reporting, Rust backtesting, live trading, exchange connectors, orchestration, and examples. Its backtesting topics include Level 3 order-book simulation, combining…
This A-share stock screen combines a turnover range of 3% to 12% with a newly formed KDJ bullish crossover and a weekly moving-average crossover in which the five-week average moves above the ten-week average. Its final stated selection logic also requires…
This stock-selection note proposes filtering equities by three conditions: a daily range above 1%, a current high equal to the highest high over the current and previous sessions, and listing age above an unspecified threshold. The range is calculated…
This research summary tests stock-selection signals derived from candlestick upper and lower shadows, then compares them with shadow measures based on the Williams indicator. The reported results distinguish the two approaches: candlestick upper-shadow…
The document explains a utility for recording an Expert Advisor’s backtest equity data in a history file, then viewing that data as an offline chart. The workflow creates an instance of the class, updates it on each tick, saves the data when the test ends,…
The document describes a stock screen that selects shares with daily amplitude above a threshold, at least three years since listing, and exclusion from China’s STAR Market. It presents amplitude as a proxy for trading attention and the listing-age filter as…
This note describes ways to reduce memory use and speed up parameter tuning for an ETF rotation strategy. It recommends moving suitable calculations into SQL, loading only needed data, reusing cached data, releasing large objects, precomputing values during…
This event outline introduces advanced FinRL development topics, including the FinRL-Tutorials project, reinforcement-learning portfolio allocation, stock trading in China’s A-share market, and ensemble strategies. It distinguishes portfolio allocation from…
This study examines equity factors built from changes in analyst forecasts and tests how forecast stability affects their relationship with next-month stock returns. It reports that revision factors are positively associated with subsequent returns, but…
This post proposes screening stocks for turnover between 3% and 12%, an outside-volume to inside-volume ratio above 1.3, and positive net buying by major participants during the auction. The filters aim to combine trading activity, buy-versus-sell volume,…
This post describes a Chinese equity screen combining daily price range, five consecutive years of return on equity above 15%, and a circulating market capitalization between 5 and 10 billion yuan. Its proposed refinement adds a price-to-book ceiling of 3.…
This post outlines a monthly small-cap stock strategy. On the first trading day of each month, it excludes ST-designated stocks and listings on the STAR Market and Beijing Stock Exchange, then invests equally in the 30 stocks with the smallest market…
The report describes tests of 14 Ethereum trading strategies using stablecoin issuance and Uniswap V2 USDC/ETH pool activity. It outlines signals based on rolling issuance sums, moving averages, standard-deviation thresholds, Pearson correlation, and pool…
This indicator study compares three exit rules applied to the same Turtle-style Donchian breakout entries: an ATR trailing stop, a shorter exit channel, and a fixed profit target. Entries occur when a closed bar first crosses beyond the previous channel;…
This brief description introduces an Expert Advisor based on the TrendEnvelopes semaphore indicator. It generates a trade signal when a colored point appears at the close of a bar, with the point’s color indicating the trade direction. The document also…
The described expert advisor looks for a bar whose range is slightly smaller than the minimum bar range observed over a configurable lookback period. When this condition occurs, it places pending stop orders around the previous bar's high and low, offset by…
This note outlines a Chinese equity screen combining daily turnover between 3% and 12%, a reversal-candle condition, and evidence of institutional fund buying. Its code examples estimate the reversal condition from the prior close relative to the day’s high…