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 brief description outlines an Expert Advisor that processes signals from four Williams Percent Range indicators, using averaging periods of 26, 27, 29, and 30. It says the program displays text objects on the chart and maintains a log file, indicating…
This Chinese stock-selection post describes a screen for companies associated with the metaverse theme and a rounded price pattern. Its initial rule combines the prior day’s turnover rate with the ratio of current auction volume to the prior day’s volume,…
This Expert Advisor example applies two moving averages, MACD, and the Commodity Channel Index to USDJPY on an hourly chart. It reads indicator values from completed bars, including consecutive MACD readings, and uses trade-transaction events to track…
The AFL Winner indicator is described as a tool for identifying possible trend changes around established turnover areas at the negative and positive 50 levels. The document gives this threshold-based description as the indicator’s central trading concept,…
This brief Chinese-language support exchange addresses a strategy configured for daily rebalancing that appears to trade only every seven days in backtesting and does not rebalance in simulation. The response points to a condition in the backtest module’s…
This stock screen selects companies in the metaverse industry whose share price is above its five-day moving average and that have outstanding convertible bonds. The moving-average condition is intended to retain stocks showing short-term price strength; the…
This Chinese equity screening strategy ranks stocks using cross-sectional measures of circulating market capitalization, closing price, and earnings per share, then combines the ranked factors into a total score. Its stated filters exclude special-treatment…
The document describes the U.S. Dollar Index, also known as USDX or DXY, as a measure of the U.S. dollar’s value relative to a basket of foreign currencies. It explains the index’s direction: it rises when the dollar strengthens against the basket. ICE…
This report examines two style-allocation ideas for Chinese equities: rotating between value and growth using value spread, and reducing market exposure to systematic risk through low-beta investing. It argues that value spread tends to revert toward its…
This stock-selection rule screens for turnover between 3% and 12%, a ratio of outside volume to inside volume above 1.3, and exclusion of China’s Science and Technology Innovation Board. The accompanying implementation also includes a recent volume surge…
This market snapshot interprets crypto conditions across derivatives, spot flows, order books, stablecoins, and DeFi lending. It describes continued long liquidations in BTC, ETH, and SOL, funding turning negative across major assets, and BTC–ETH correlation…
This stock screen looks for turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and no limit-up on the previous day. The stated rationale is to find liquid, actively followed stocks with a recent strong move, followed by a possible…
This note outlines a workflow for creating an AI-assisted stock selection strategy. It recommends combining signals about the broad market, industry groups, and individual stocks rather than relying on a single factor. Example inputs include index returns…
The strategy defines a recent price range from the highest high and lowest low over a lookback window. It places a buy stop above the range and a sell stop below it, with a configurable distance. When one order triggers, the other should be cancelled; after…
This Expert Advisor combines two indicators to identify trend-following entries. ColorX2MA sets the slower trend direction, while ColorJFatl signals a possible entry when the faster trend changes. A trade signal occurs at bar close when the indicator…
The response explains how to structure a multi-stock, multi-date dataset for a multiple regression of stock returns on factors. Each stock on each date forms one observation: the return is the target variable, and that stock-date’s factor values are the…
This stock-selection example combines three filters: daily amplitude above 1%, circulating shares no greater than 5.5 billion, and simultaneous bullish crossovers among 5-, 10-, and 20-day moving averages. The article describes calculating amplitude from the…
The discussion addresses missing broad-market risk-control data in a rolling-training workflow. Its suggested remedy is to load benchmark index history directly in the backtest data-preparation function instead of relying on an external data merge. The…
This Expert Advisor searches the previous 500 closing bars for price levels where closes cluster, then uses a cross of three moving averages of different lengths as a trend-development signal. After detecting a directional trend, it identifies the nearest…
The document describes an order-management issue in a Binance perpetual futures example. A partially filled sell order has an original quantity and an executed quantity; subtracting the latter from the former in JavaScript produces a residual quantity with a…
This stock-selection proposal combines three technical conditions: RSI below 65, a pattern described as the start of a major rise, and a shortening MACD histogram on a 15-minute interval. The article interprets the MACD condition as weakening downside…
This account describes a BigQuant assignment that applied linear regression and XGBoost within a rolling-training strategy, then compared their backtest returns. The author reports annual returns of 30% for linear regression and 52% for XGBoost, but provides…
This experiment describes a directional strategy for the APE-BUSD perpetual futures market that combines Bollinger Band position with the MACD line and histogram. It takes a long signal when %BB is below 0.2, the MACD histogram is positive, and the MACD line…
This indicator plots a colored histogram of the closing price’s percentage distance from a selected ZigZag pivot. It calculates the difference between the close and the pivot price, divides by that pivot price, and scales the result by 100. Positive and…