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
This guide lays out a futures data workflow for a trading system. It starts with instrument settings, spread costs, and roll parameters, then gathers individual contract histories, builds roll calendars, creates multiple-price series, derives back-adjusted…
The report proposes benchmark indexes built from funds that seek to outperform the CSI 300 or CSI 500. It combines contractually designated index-enhanced funds with other funds identified as similar through their benchmarks, tracking error, and historical…
This brief student response defines quantitative investing as using data, statistics, research, systematic data collection, backtesting, and programmed trading to make investment decisions. It highlights several perceived advantages: a repeatable process,…
This Chinese-language support exchange concerns missing dividend information for Contemporary Amperex Technology in a China A-share data table. The user asks why a recent September distribution, reportedly paid on September 28, does not appear and how to…
This document outlines an Expert Advisor that uses the Blau Ergodic oscillator to generate trade entries. It lists three possible signal events: a change in histogram direction, a move through the zero line, or a change in the signal-line cloud's color. An…
This research summary reviews trend-following indicators and how to build strategies for broad asset allocation and industry allocation. It groups 41 indicators by their input data, filtering, moving-average construction, and signal generation, arguing that…
The document describes an expert advisor that trades signals from the XRSI DeMarker Histogram. It generates a signal when a bar closes and the indicator changes direction, so the strategy acts on confirmed direction shifts rather than intrabar moves. The EA…
The document outlines an Expert Advisor that trades signals from two moving-average lines of the FractalAMA_MBK indicator. A signal is generated at bar close when the indicator’s main line crosses its signal line. Running the advisor requires a separately…
The document describes a MetaTrader tool for checking whether stored market ticks are reliable inputs to real-tick backtests. It counts invalid or crossed quotes, timestamp anomalies, sharp one-tick reversals relative to median spread, gaps compared with…
The document explains how factor mining outputs can be connected to strategy research. The mining module produces factor expressions as strings; researchers can then use those expressions to test factor effectiveness and run strategy backtests. It offers no…
This document presents a Chinese-stock ranking workflow built around an XGBoost RankNet model. It constructs price-return and trading-activity features, labels stocks using clipped forward returns divided into quantile bins, and separates training data from…
This stock selection rule screens Chinese A-shares using three conditions: turnover between 3% and 12%, a newly formed KDJ bullish crossover, and first-level bid volume greater than first-level ask volume. The article presents the rule as a way to combine…
This overview of a trading automation section introduces the MQL5 concepts used to build Expert Advisors. It begins with instrument specifications and trading account settings, then covers built-in functions, data structures, robot events, and the Strategy…
This trading system uses the Extremum indicator’s histogram color changes to generate entries. A trade signal occurs when a bar closes and the histogram switches from green to red or red to green. The description does not specify the indicator’s calculation…
The screen selects stocks whose daily high-low range exceeds one percent, excludes Beijing-listed A-shares, and requires the opening price to lie above the ten-day moving average of closing prices but below 110% of that average. The article presents the…
The document outlines a Chinese A-share screening idea focused on metaverse stocks with prior-day turnover above 8% and excluding specially treated stocks. Its proposed limit-up pattern looks for activity before 10 a.m. and checks successive five-minute bars…
The document discusses replacing MQL4’s iBarShift function in MQL5. It says MQL5 provides lower-level functions for implementing the same operation and reviews four community versions written as alternatives. According to the author, those versions return…
This post describes a historical A-share stock screen using an RSI reading below 65, a price range greater than 1%, and a 2021 date filter. It presents RSI as a gauge of price strength and overbought or oversold conditions, while the range criterion is…
The report describes stock-return prediction with machine-learning models built for short, medium, and long forecast horizons. It groups selection factors according to their information coefficients at different horizons, reflecting the idea that factor…
This Expert Advisor uses the Money Flow Index (MFI) as a threshold-crossing signal. It sells when the oscillator crosses downward through an overbought level and buys when it crosses upward through an oversold level. Signals are evaluated at bar close, so…
This research summary outlines three refinements to genetic programming for finding stock-selection factors: fitness measures based on mutual information and long-only excess return, ways to transform nonlinear factors, and validation procedures intended to…
This overview explains vn.py as a modular framework for automated trading. The MainEngine coordinates gateways, applications, databases, and data services, while the EventEngine routes market, order, and other messages to subscribed components. A typical…
This document outlines a simple automated trading rule based on comparing the opens and closes of the two most recent completed candles. When no position is open, it enters a buy if the newer candle opens above the older candle but closes below the older…
This stock-selection screen combines three conditions: daily high-to-low range above 1% of the opening price, prior-day trading activity above the stated threshold, and a positive weekly MACD condition. The document presents the rules as a way to focus on…