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 module supports copula analysis by mapping observations to marginal empirical cumulative probabilities, with optional linear interpolation and probability bounds. It provides a multivariate row-wise transform, fits a supplied copula to two series after…
This ProRealTime indicator estimates a directional move from the latest p candles and draws a line from the current close, projecting the estimate both backward and forward by p bars. The move is based on the sum of close-minus-open changes, calculated…
This project specification proposes analyzing primary-level Shenwan industry indices over a chosen date range. At five-trading-day intervals, it would calculate each industry’s share of total A-share turnover and its excess return relative to the CSI 300.…
The document explains historical volatility as the dispersion of asset returns and distinguishes it from implied volatility, which is inferred from option prices. It describes calculating the standard deviation of daily returns and annualizing it by…
This research summary proposes measuring stock valuation through time as well as across stocks. It separates a valuation series into a longer-run trend and a short-term deviation, then uses an error-correction model to define deviation factors from the…
The document gives a broad introduction to quantitative trading as the use of data, statistical or machine-learning models, and programmed rules to inform and execute investment decisions. It surveys common components: historical and live market data,…
The document summarizes a study of factors associated with bilateral trade between Egypt and BRICS partners. It applies a gravity-model framework to panel data spanning 2001–2021, using information attributed to the World Bank and International Monetary…
The document introduces Lévy processes as a way to model asset-price behavior with jumps and distributions that can have heavier tails than a normal model. It describes a price process combining drift, Brownian motion, and a Lévy component, then outlines…
This beginner-oriented guide explains machine learning through classification and house-price estimation. It distinguishes supervised learning, which uses examples with known outcomes, from unsupervised learning, which can group observations or identify…
The Weighted CCI is described as a two-line oscillator with fast and slow Commodity Channel Index components. Its calculations incorporate the relationship between fast and slow Average True Range values, with a weighting input intended to control ATR…
Hedge ratios set the relative sizes of legs in a spread so that price differences do not leave the position unintentionally unbalanced in dollar terms. The document introduces a simple price-ratio method, then describes normalizing weights so the dependent…
This method adapts mean-reversion pairs trading to the risk that a spread shift reflects a lasting structural change rather than a temporary deviation. It models the pair spread as having two Markov-switching states, each with its own mean and volatility,…
The essay examines limits of using large language models and deep learning as autonomous trading decision makers. It contrasts their strength in finding patterns in historical data with the market researcher’s need to reason about current conditions, causal…
The document introduces an implementation of the simple moving average intended to address shortcomings the author sees in existing versions. It argues that some implementations become slower as the lookback period grows because they repeatedly loop over…
The Market Structure RSI applies the familiar RSI calculation to counts of broken swing points rather than to bar-by-bar price changes. It identifies simple three-bar pivot highs and lows, then checks whether price has crossed the stored levels. Each broken…
The post describes a simple pattern study on constituents of the CSI 300. It defines a five-day sequence: the first day falls by more than 1%, the second falls by more than 2%, the third moves either way but rises no more than 1%, the fourth rises by more…
The document outlines an MT4 indicator that calculates an anchored volume-weighted average price from the start of a daily, weekly, or monthly session. It uses typical price, formed from the high, low, and close, weighted by tick volume. Standard deviation…
The document describes an audit of terminal-held price bars before they are used for indicators or backtests. It checks OHLC consistency, bar timestamps, missing openings relative to the broker’s stated quote sessions, empty or flat bars, higher-timeframe…
The Synthetic Oscillator constructs a smooth sine wave from an estimated market cycle rather than smoothing the output of a conventional oscillator. It first applies a Hann window and band-pass filtering to price, then uses normalized cycle components to…
The article discusses how artificial intelligence and machine learning may affect trading, investment advice, and market structure. It describes machine learning as a way to identify economically useful predictive features and combine them with classifiers.…
This document outlines a variation on the Commodity Channel Index. It replaces the conventional mean absolute deviation calculation with standard deviation and offers an option to filter prices using a double-smoothed Wilder exponential moving average. The…
The document describes John Ehlers’ MADH oscillator, an extension of the moving average difference indicator intended to improve cycle and trend analysis. It forms two price filters with different lengths, applies Hann-window weighting to their inputs, and…
This tutorial outlines a machine-learning workflow for selecting Chinese A-share stocks with a convolutional neural network. It describes defining a stock universe and input factors, extracting and splitting data, turning observations into rolling sequences,…
This research summary explains a method for separating a mutual fund’s alpha into stock-selection alpha and weighting alpha. It estimates selection skill by reweighting a fund’s holdings by market capitalization, then defines weighting alpha as the…