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 report proposes identifying Chinese quantitative private funds through exchange-disclosed trading-seat data. It matches stocks held by four funds among the largest tradable shareholders at quarter-end with the broker seats that appeared on those stocks’…
The document presents an experimental stochastic oscillator that changes the averaging method used in its calculation while leaving the price inputs unchanged. It offers four variants based on simple, exponential, smoothed, and linearly weighted averages.…
The MA Sabres indicator marks possible changes in trend using the direction of a configurable moving average. It can use TEMA or another selected average, then track whether the average has been rising or falling. A reversal cue appears when the average…
The article describes an ability parity model for allocating among actively managed funds. It extends portfolio optimization by estimating each fund manager’s stock-selection skill and market-timing skill, with timing measured using the Treynor–Mazuy…
The document addresses how to retrieve financial figures from multiple quarters and combine them into a factor for analysis. The examples ask about comparing current-quarter cash flow with the prior quarter to measure change, and averaging current and…
This guide explains FMZ’s simulated-tick and real-tick backtesting modes. Simulated ticks are generated from candlestick data, while real-tick mode replays recorded tick data and can include depth and trade records. The guide describes the trade-off between…
This document presents a Chinese equity screen for Shenzhen Main Board stocks, combining turnover from 3% to 12%, circulating market capitalization from 5 billion to 10 billion, price-to-earnings ratio from 0 to 29.01, and price-to-book ratio from 0 to 3.11.…
This Chinese-language post proposes screening stocks using turnover, displayed best-level bid and ask volume, and large-order net inflow. Its final selection rule requires turnover between 3% and 15%, bid volume greater than ask volume, and large-order net…
Wildhog is an oscillator intended to flag overbought and oversold conditions and identify divergences. It is described as usable across timeframes and uses the most recent high, low, and close data over a configurable lookback period. The user can set the…
The article explains Active Fundamental Performance (AFP), a measure intended to identify mutual fund managers who select stocks well on fundamental information. For each fund, it computes the covariance between benchmark-adjusted portfolio weights, or…
The document explains the Volume Flow Indicator (VFI), a volume-based measure described as a modified form of On Balance Volume. It uses typical price rather than the close, applies a volatility threshold so small price changes do not count as directional…
The article summarizes research on whether information spreads through mutual fund families and how that relates to fund performance. It describes a diffusion measure based on the order in which affiliated funds buy a stock after it first appears in a family…
This MQL5 utility evaluates how sensitive a trading strategy’s historical results are to assumed execution costs. It reads closing-deal records containing dates, profits, and optionally volumes, then recalculates net profit and profit factor at the chosen…
The document asks how to tune two component parameters together, specifically start and end dates as a pair. It provides an example tuning function that returns a parameter grid, with a list of candidate values for a single estimator-count parameter, then…
The document explains the price-to-earnings ratio as a measure of a share price relative to earnings per share. It defines the ratio using current share price and earnings per share based on the prior year’s net income and share count, then illustrates the…
This study examines whether sell-side analysts use peer forecasts on other companies in their own coverage portfolios to inform estimates for a target company. Using quarterly earnings forecasts and actual results, it measures optimism through forecast…
This forum post argues that AI should be treated as a tool rather than an autonomous source of trading intelligence. It emphasizes the difficulty of learning financial patterns from noisy data, the challenge of achieving stable profits even with…
The article argues that markets are uncertain and that technical indicators cannot deliver dependable forecasts by themselves. It makes the broad claim that trend-following indicators may have accuracy below 50%, attributing this to lag and uncertainty, but…
This Chinese-language article surveys quantitative finance work through six role types: desk quant, model validation, research, quant development, statistical arbitrage, and capital modeling. It describes how these roles differ in their proximity to trading,…
This indicator expresses a candle’s position within its high-low range as a centered value. It compares the open with the low, scales that distance by the full range, and shifts the result so the output is centered around zero. The display separates bullish…
This module implements analytical trading calculations for an Ornstein–Uhlenbeck mean-reverting process, following a published statistical-arbitrage model. Given an entry threshold, an exit threshold, and transaction costs, it computes expected trade length,…
The document poses a quantitative modeling question: how to turn continuous data into discrete categories, then encode those categories as model features. It briefly explains one-hot encoding as representing each category with a vector that has a single…
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 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…