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 presents a Chinese-equity screening rule that combines a minimum daily amplitude, a circulating-market-cap threshold, and a morning star candlestick signal. It describes the pattern as a possible bullish reversal after a decline and provides…
The document outlines an exploratory method for studying whether historical indicator patterns relate to later price movement. It encodes a sequence of MACD values over a lookback window, uses that sequence to name a CSV file, and records how often the…
The document describes a stock strategy that scores candidates with a neural network, buys up to three holdings, and aims to sell each after three trading days. It stores each stock and its entry-day index in a context list, then compares that index with the…
This post proposes screening Chinese equities using three conditions: buying-pressure share above a threshold, prior-day turnover value above a threshold, and a high dividend ratio in a specified historical year. It frames buying pressure as a sign of…
This brief description outlines an MT5 indicator that constructs a moving line by extrapolating a fourth-degree polynomial. It describes deriving candidate lines from a sine-like curve and from an axial or nearly constant line, with different line-power…
This introductory guide lays out five areas for developing quantitative trading capability: mathematics and statistics, programming, financial knowledge, strategy research, and practical testing. It highlights time-series and cross-sectional econometrics,…
This post proposes screening Chinese stocks by metaverse industry membership, a custom “arc” pattern, and dates within 2021. It describes using industry data and a date filter, then adding technical and fundamental measures for a broader assessment. The…
Gold Dust proposes a robustness check for optimized trading systems that addresses the instability of financial-market statistics. Instead of optimizing one parameter set on one historical interval and forward-testing it, the method optimizes separate…
This document describes an Expert Advisor that trades signals from the CronexAC oscillator. A signal is generated when a completed bar shows a change in the indicator cloud's color. For the EA to run, the compiled CronexAC indicator must be installed in the…
This guide outlines a workflow that combines TQ EDB market and indicator data services with Coze as a conversational research assistant. After adding the EDB skill, a researcher can describe a task and request data retrieval, idea checks, simple backtests,…
This beginner guide introduces Python syntax and core programming constructs that are useful when starting quantitative strategy research. It covers indentation, comments, assignment, imports, basic types and arithmetic, comparisons, and conditional logic.…
The document explains a least-significant-digit radix sort that processes numeric values byte by byte, using 8-bit digits. It presents an MQL implementation intended for large arrays and describes support for several integer and floating-point types,…
This Chinese-language research summary describes a stock-selection factor built from quarterly profitability data. It defines a trend measure as the sensitivity of profitability to time in a linear regression, with separate versions based on…
This script configures WtCtaOptimizer to run parameter searches for a Dual Thrust strategy on a China Financial Futures Exchange index futures contract. It fixes inputs such as bar count, bar interval, lookback days, and contract, then varies the strategy…
This document describes an expert advisor that offers several ways to move a stop as a trade progresses. The stop can follow price by a fixed point distance or use Parabolic SAR, ATR, moving averages, candlestick patterns, or fractals. It can also be set as…
This five-minute EURUSD strategy combines a stochastic oscillator with a long-term exponential moving average. A long entry requires the oscillator to remain in an oversold range across several candles, price to be above the moving average, and the…
This BigQuant forum answer explains how to use a different feature set in each iteration of a rolling model workflow. The example loop updates training and test start and end dates for each rolling window, disables the backtest module during model runs, and…
This guide describes a workflow for moving historical daily futures bars from Ricequant into a local VeighNa database backed by MongoDB. It first uses Ricequant’s research environment to retrieve listed futures contracts and daily price fields over a chosen…
The document explains a configurable scanner for five- and six-pivot harmonic structures. Rather than hard-coding named patterns, users specify acceptable ranges for ratios between legs such as XAB, ABC, and BCD. The scanner builds a recursive zigzag from…
This guide recommends choosing community trading strategies according to an investor's capital, return expectations, and tolerance for drawdown. It distinguishes a conservative profile, associated with diversified holdings, a smoother equity curve, a longer…
The article outlines an A-share stock selection screen combining turnover, company size, profitability, and past price-limit events. It selects shares with turnover between 3% and 12%, market capitalization below 10 billion yuan, no reported loss, and at…
This document describes an expert advisor that trades around Bollinger Bands. Its stated rule is contrarian: a downward break below the lower band triggers a buy, while a break above the upper band triggers a sell. An update says entries are placed after a…
This article examines whether financial factors such as value, size, profitability, investment, and momentum can be timed using predictive signals. It groups candidate signals into financial conditions, economic conditions, investor sentiment, factor…
This overview surveys recurring problems in quantitative trading, including unreliable or incomplete data, model risk, slippage and fees, parameter selection, real-time monitoring, and processing speed. It also discusses choosing machine-learning methods and…