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.
16,761 documents
The document outlines the role of an integrated quantitative trading platform. It describes a workflow that brings market data analysis, strategy development, historical backtesting, risk assessment, and automated execution together. It also notes that…
The Arnaud Legoux Moving Average (ALMA) is described as a price-smoothing method that applies Gaussian weights across a rolling window. Its offset parameter shifts the weight distribution and adjusts the balance between smoothness and responsiveness, while…
The document outlines a broad framework for evaluating equity factors. It combines periodic cross-sectional robust linear regression to estimate factor returns, information coefficients (IC) to measure the relationship between factor exposures and subsequent…
This stock-selection strategy ranks shares using large-order net inflow and relative price performance. Its stated purchase screen looks at the prior 30 trading days, selecting stocks whose net inflow share from very large orders is among the top 5% of the…
This research note describes a method for detecting support and resistance lines in Chinese A-share price series. It adapts a local high and low point approach with quantile regression, defining line slopes for continuation patterns such as triangles,…
This proposed Chinese A-share screen selects companies classified in the metaverse industry, with circulating market capitalization at or below the stated 55 hundred million shares threshold, and a listing age greater than a configurable number of years. The…
The document describes a draft expert advisor that opens long and short positions simultaneously. Its defining condition is that the losing position’s stop loss is reached five points before the profitable position’s take profit. It says the strategy…
This guide explains how to use historical backtests and parameter optimization as research checks before deploying a trading strategy. It outlines setup choices such as the instrument and exchange, bar interval, date range, fees, slippage, contract…
The document defines Qlib data handlers for one-minute bars, aimed at high-frequency research and backtesting. The training handler creates normalized open, high, low, close, and approximate VWAP features, along with volume features. Price features are…
A user reports that BigQuant’s trade simulation showed a purchase at the market open and a sale at the close on the same day, despite having no carried position and expecting the position to be zero. The response explains that this can be normal because the…
This document describes a simple Expert Advisor that uses a fractal Williams Percent Range oscillator to generate entries. It sells when the oscillator crosses downward through its overbought threshold and buys when it crosses upward through its oversold…
This Backtrader example demonstrates a simple trend-following strategy and order-monitoring setup. It calculates a 15-period simple moving average and uses a crossover between the closing price and the average: an upward cross creates a buy signal, while a…
This BigQuant example builds a mainland Chinese stock portfolio by screening for eligible main-board shares and excluding suspended, ST, and recently listed names. It requires positive trailing earnings and dividend yield, caps float market capitalization,…
The post outlines a way to backtest a continuous sequence of dominant futures contracts in a VeighNa-based system. It argues that an exchange-style continuous index can differ from trading actual contracts because it blends contract prices and may produce…
This stock-selection idea combines three filters: daily amplitude above one, a rising short-term moving-average relationship, and at least two limit-up sessions within the past 500 days. The stated rationale is that amplitude and the moving-average condition…
Alphalens is a Python library for evaluating predictive stock factors. It turns a factor signal and pricing data into a structured dataset of forward returns, optionally assigning observations to quantiles and groups such as sectors. The resulting analysis…
This Chinese-language article outlines an equity screening rule that combines a relative strength index below 65, a positive product of price change and a proxy for net large-order activity, and a shortening MACD histogram on a 15-minute interval. The stated…
The report analyzes cross-sectional price momentum in Chinese equities and organizes possible improvements along two dimensions: whether a change refines the measurement or the formation process, and whether it uses price or return information. Examples…
This report surveys asset-allocation approaches grouped by their inputs: mean-variance models, risk-allocation models, and subjective methods. It expresses several optimization-based risk models, including mean-variance, risk parity, and maximum…
This example selects stocks from the Chinese equity market using dividend yield, share price, and circulating market capitalization. It first keeps the highest-dividend-yield quarter of the market and stocks priced below 10 yuan, then excludes certain…
This proposed Chinese stock screen combines a turnover range of three to twelve percent, a reversal pattern described as a rebound after a decline, and at least five overlapping moving averages. The rationale is that clustered averages may indicate a…
This stock screen focuses on companies classified in the metaverse theme that recorded at least one limit-up day within the previous twenty-five days and have a positive return on the current day. The stated rationale is to identify recent strength and…
The document proposes an Ichimoku-based classifier for market regime and trade setup. It compares price with the cloud and checks whether the current and forward clouds share the same direction. It assigns positive or negative values to bullish or bearish…
The document describes an Expert Advisor that takes trade signals from a CMO-based cloud indicator. It opens a position when a bar closes and the indicator cloud changes to the opposite color. The supplied description identifies the indicator file required…