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
This brief forum exchange addresses a feature calculation that displayed missing values and offers a warning relevant to strategy construction: using a shift with a negative offset can incorporate future observations into a feature. Such a feature may appear…
This brief indicator description explains that a moving average based tool dynamically calculates and displays potential support and resistance levels. It exposes two user settings: the calculation period and the price series used in the calculation. The…
The note distinguishes selecting a stock universe from testing whether a factor can rank future returns within that universe. It describes factor analysis as sorting stocks by a factor, dividing them into equal-sized groups, and comparing group returns.…
This platform support discussion explains two apparent backtest anomalies in a single-stock strategy: why a position did not begin on the requested date at full allocation, and why the stock appeared to be sold later. The response attributes the delayed…
This document explains how to validate a company’s SEC submissions response before using it in an incremental filing dataset. It distinguishes the recent filings arrays from historical filing shards and recommends preserving the raw response, its hash,…
This brief response defines quantitative investing as using tools to extract patterns from historical data. It frames time-series analysis as a way to improve the odds of making a successful decision and cross-sectional analysis as a way to seek better…
This ProRealTime indicator compares current volume with its moving average to highlight unusually large or small activity. It divides volume by a configurable average, with a default lookback of 60 bars, then caps the displayed ratio at an upper limit.…
The document explains a model-training error caused by a feature stored as an object or string rather than a numeric value. Its diagnostic approach is to inspect the training data and identify which input column has the incompatible type. The example points…
The document presents a price range detector that tests three nested lookback windows and selects the longest window satisfying a set of structural filters. These include volatility compression ranked against the instrument’s own history, repeated closes…
This forum post asks how to migrate several legacy factors from an earlier version of a quantitative research platform into a newer one. The expressions cover an industry-grouped beta adjustment, a rolling correlation between log volume and absolute returns,…
This research summary explains how alpha factors can be represented by factor-mimicking portfolios (FMPs) under a stock covariance model, and how linear combinations of factors correspond to combinations of their mimicking portfolios. It frames factor…
This documentation describes a simulator for autoregressive series and pairs whose cointegration error follows an AR(1) process. One series is modeled through its changes, while a linear combination of the two series represents the spread or cointegration…
This short indicator description explains a semaphore-style signal based on crossovers between the main line and signal line of a LinearRegSlope_V1 indicator. In principle, such crossovers translate changes in a linear-regression slope measure into discrete…
This research review examines whether stocks moving together always reduce active mutual fund performance. It distinguishes synchronicity driven by broad market information from synchronicity associated with noise trading, proposing that investor sentiment…
This short library description outlines a basic volume profile tool for a selected time range. The user supplies start and end times and a price resolution, expressed in points, which determines how adjacent prices are grouped. The library can plot the…
The indicator measures how far the closing price lies above or below a chosen moving average in standard-deviation steps. Users configure the averaging period and type, plus the first and maximum deviation levels and the increment between levels. Its signed…
This Chinese stock-screening post combines three filters: membership in the metaverse industry, a rounded price pattern, and a turnover rate between the stated lower and upper bounds. It describes turnover as a way to focus on liquidity and trading activity.…
The document explains two settings in a rolling-data module used to prepare features for securities. The window size controls how many consecutive observations are grouped into each sample. Its example uses five sequential values and a window of three to…
This note describes a Chinese equity screen that seeks stocks with a daily trading range above 1, no prior-day limit-up, and a current-day increase in buying activity above 5%. It frames the activity filter as a way to find stocks attracting institutional…
This data-preparation workflow builds model inputs for a momentum strategy from asset closing prices. It clips prices using bounds based on an exponentially weighted mean and standard deviation, derives daily returns and volatility, and creates a next-period…
This BigQuant support exchange explains a prediction error associated with missing or infinite values while constructing label bins. It suggests checking whether the target label is absent or contains many missing values. The further diagnosis is that the…
UltraMFI builds a trend display from multiple smoothed Money Flow Index readings. It creates a range of smoothing periods using an arithmetic progression: a starting length, a step size, and a count of period changes. For each period, it assesses the…
This article explains the theoretical link between beta pricing models, including the Fama-French three-factor model, and stochastic discount factors (SDFs). It distinguishes absolute pricing, which connects asset values to macroeconomic risks, from relative…
This document explains a rolling volume profile that estimates the Point of Control (POC), the price bin with the greatest accumulated volume over a recent lookback window. It divides the window’s high-to-low price range into bins, assigns each bar’s volume…