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.
21,023 documents
A platform support exchange explains one reason a strategy may produce trades in backtesting but no signals in simulated trading. The strategy’s prediction start and end dates were tied to live-trading parameters, while no lookback days were requested.…
This document defines a simple oscillator that measures how the Average Directional Movement Index has changed over a chosen lookback interval. The calculation subtracts the ADX value from a specified number of periods earlier from the current ADX value. A…
This source code implements a collection of momentum and related technical indicators as time series. The visible sections explain RSI as a comparison of smoothed gains and losses, TSI as smoothed price change relative to smoothed absolute change, the…
This research note examines an active-trading factor, called ACT, that characterizes aggressive versus passive order flow in China’s A-share market. It reports that the standard ACT measure has limited stock-selection ability, then splits observations by…
This article examines how training-window length affects AI stock-selection models, comparing multi-year datasets with shorter windows and proposing rolling training and evaluation on a designated validation period. It reports that, in its experiments,…
The document describes a technical screen for Chinese A-share stocks. It selects stocks with turnover between 3% and 12%, a newly formed bullish KDJ crossover, and a close at or above the 20-day moving average, with a date condition tied to 2021. The page…
The document explains a Stochastic RSI indicator for ProRealTime. It calculates a current RSI value, compares it with the lowest and highest RSI readings across a recent lookback, and scales the result to a range from zero to one. The example uses a…
This tutorial explains why backtests need to account for more than commissions. It separates costs into fees and taxes, slippage from the delay between a signal and execution, and market impact and liquidity effects, including bid-ask spreads. It compares…
This research outline proposes using value at risk (VaR) and stock factors to estimate future downside risk. It examines factors across several dimensions, selects those judged effective, and combines them into a multifactor model intended to quantify…
This indicator method estimates a desired-period RSI on a chart whose bars are shorter than the target timeframe. It infers the chart bar duration and the number of lower-timeframe closes needed to form each higher-timeframe change, then separates gains and…
The document describes an expert advisor for detecting gaps in a broker’s historical price data for a chosen symbol and timeframe. It instructs the user to run the tool in the strategy tester with the date restriction disabled and open-prices-only modeling;…
The document proposes a stock screen combining turnover between three and twelve percent, a beverage and alcohol industry classification, and a rounded or arc-shaped price pattern. It presents the screen as a way to combine trading activity, industry…
This brief discussion asks how to translate legacy rolling-factor expressions into SQL: a five-day sum of turnover, a five-day mean of closing prices shifted three days back, and a ten-day statistic. It also raises a practical data-type issue when…
This indicator builds a linear regression channel whose starting point is set by a chosen date and time. As new bars arrive, the lookback grows from that anchor, so the fitted trend line and its upper and lower bands update over an expanding period. The user…
This report summary studies whether mutual funds that performed relatively well continue to do so, and whether weak performers remain weak. It defines persistence through the serial relationship in a fund’s Sharpe ratios: each month, it calculates Sharpe…
The document describes an MT5 indicator for reviewing completed trades through a dashboard. It summarizes account history with measures such as trade count, win rate, gross gains and losses, net profit, average outcomes, and profit factor. The indicator is…
This note describes a Chinese equity screen for companies associated with the metaverse, with circulating market value above 10 billion yuan and return on equity above 15% in each of the past five years. It presents the criteria as a way to find businesses…
This paper proposes a Transformer model for predicting stock price movements, with enhancements intended to capture both local structure and longer-range relationships in financial time series. A multi-scale Gaussian prior is added to encourage the attention…
This overview explains several crypto market data types and their uses. OHLCV bars summarize opening, high, low, and closing prices alongside traded volume; the post connects OHLC data to candlestick chart analysis. It describes VWAP and TWAP as aggregated…
The document gives a suggested sequence for preparing quantitative factors: remove extreme values, handle missing observations, standardize the data, and then neutralize it. It describes neutralization as removing exposures that can obscure a factor’s…
This report overview argues that commodity price forecasts should combine fundamental and technical analysis. It groups actively traded Chinese commodity futures into five broad sectors—ferrous materials, chemicals, agriculture, nonferrous metals, and…
This short example describes a basic way to screen cryptocurrency listings using market data. It retrieves a listings dataset denominated in US dollars, then selects assets whose quoted price is below a very small threshold and whose reported 24-hour trading…
This brief troubleshooting exchange addresses an error encountered when industry features are passed to a shared data-cleaning module for industry neutralization. The reported failure says the industry field is not one-dimensional, but the exchange does not…
This study examines whether firms with predictable quarterly earnings patterns earn unusual stock returns when they announce earnings in their historically strong quarter. It measures seasonality mainly by ranking a firm’s earnings over five years and…