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 Chinese-language community discussion asks how to calculate a market measure commonly translated as main-force net inflow. The post proposes defining it as the sum of actively initiated buy orders classified as large and extra-large. This frames the…
This indicator fits a Lagrange interpolating polynomial to selected price points on a chart, then uses the polynomial to calculate subsequent points. The user selects a starting bar and an ending bar for the analysis, along with the number of bars to…
This document introduces a Python library for engineering technical-analysis features from financial time series, using price and volume fields such as open, high, low, close, and volume. It catalogs indicators across volume, volatility, and trend…
This meetup Q&A discusses several practical questions in quantitative research. It explains that traders can label chart patterns for AI training in principle, but visual labels may vary with chart scale and between annotators. A model can only learn useful…
The document describes an adaptive moving average that uses the efficiency ratio to adjust how an EMA responds to price movement. It attributes the efficiency ratio to Perry Kaufman and presents this version as a simplified alternative to his adaptive moving…
This note introduces the Easley, Kiefer, O’Hara, and Paperman (EKOP) model to explain how informed and uninformed trading can shape a stock’s bid-ask spread. It describes a discrete-day, continuous-within-day setting in which information events may be good…
This lecture listing introduces policy-gradient methods, which learn a policy directly, and actor-critic methods, which pair a policy learner with a value estimator. The description highlights the actor-critic combination as a way to use value predictions to…
This document explains an indicator that fits a linear regression channel from a user-selected date and time through the latest chart bar. It calculates the regression slope and intercept from closing prices, then estimates channel width using the standard…
The document describes an indicator that modifies a simple moving average using a configurable lag reduction factor. Users choose the lookback period, applied price, and factor. The calculation raises the ratio of the current moving average to its previous…
The document introduces a recursive median oscillator based on John Ehlers’s discussion of recursive median filters. Median filtering is presented as a way to reduce the influence of extreme price or volume observations that can distort conventional…
This BigQuant assignment asks learners to modify a classic quantitative strategy by adding an indicator, then search across hyperparameters. It directs them to collect the historical performance curve for every parameter configuration into a data frame, plot…
The document proposes a Chinese equity screen based on a daily price range above a stated threshold, a product combining the prior day's turnover rate with the ratio of current auction volume to prior volume, and a closing price below 12. It frames these…
This research summary proposes measuring whether trading in a stock is unusually one-sided. It classifies five-minute candles by their bodies as consensus or non-consensus activity, then measures consensus volume as a share of daily volume. Splitting that…
This code example outlines a vn.py workflow for backtesting an ATR-RSI strategy on a Chinese equity index futures contract. It configures the instrument, minute interval, historical dates, commissions, slippage, contract size, tick size, and starting…
This literature summary describes research on the historical characteristics and investment relevance of sentiment signals drawn from news and social media over a 20-year period. The underlying study compares the information in the two source types, examines…
This note describes a Rate of Change (ROC) oscillator paired with a moving average signal line. ROC measures the percentage change in closing price relative to the close a chosen number of bars earlier; the signal line smooths the ROC series using a selected…
This Chinese-language post outlines a stock screen that ranks shares by trading-volume strength and selects those near the top of the ranking. It adds a 15-minute MACD condition: the green histogram bars should be shrinking, which the post interprets as a…
This document is a brief summary of an A-share quantitative market-timing report titled around the possibility that a lower open can offer an opportunity. It reports contemporaneous observations on sector strength, index valuations, sector relative…
This article proposes six checks to run before deploying a strategy that has performed well in historical backtests. It recommends perturbing data with delays, missing observations, and outliers; scanning core parameters for broad regions of acceptable…
This Chinese stock-selection strategy filters for an RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and prior-day turnover above 8%. The accompanying Python example calculates a 14-period RSI, applies the three…
The indicator counts false breaks of the previous bar’s high and low. An upside false break occurs when the current bar trades above the previous high but closes back below it; a downside false break occurs when price trades below the previous low and closes…
This study proposes a stock-selection factor derived from intraday volume patterns. It defines a daily volume “tide” by smoothing minute-level volume with a nine-minute neighborhood, locating its peak, and identifying low-volume points before and after that…
This note offers informal Sharpe-ratio thresholds for screening strategies under a stated evaluation context: a single strategy rotating half-capital among at least three stocks, with million-level capacity and a backtest covering roughly three years. It…
This article describes an A-share screen for stocks with turnover between 3% and 12%, market capitalization below 10 billion yuan, no reported loss, and a volume ratio between 1.5 and 6. The rationale centers on trading activity: turnover and volume ratio…