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 stock-selection design that first ranks Chinese market sectors using a weighted combination of price momentum, money flows, and recent policy-related news. It then scores sub-sectors using reported net-profit growth and price…
This FAQ describes LumiBot, a Python framework for backtesting and live algorithmic trading across several asset classes and brokers. It outlines the shared strategy workflow, data-source requirements, and common operations such as handling fills, tracking…
This report summary compares cross-sectional, market-neutral commodity futures strategies based on inventory deviation and historical momentum. The inventory signal favors commodities with inventories below their own trend and shorts those above trend. It is…
This brief description introduces an Expert Advisor that uses a moving average and standard deviation as trading indicators. It exposes a cap on the number of simultaneously open positions in one direction, giving the trader a way to limit directional…
This beginner tutorial introduces how to write automated trading strategies on the FMZ Quant platform. It explains the difference between REST requests and WebSocket subscriptions, describes the platform’s unified exchange API, and compares supported…
This forum post asks about a “Golden Cross Winner” ETF strategy that uses an unusual MACD-style calculation. The author questions why the signal line, DEA, is calculated as a 26-period exponential moving average of DIF instead of the commonly cited 9-period…
This Chinese-language post proposes screening stocks for amplitude above 1, simultaneous bullish crossovers among three moving averages, and an upward-trending 30-day average. It frames the criteria as combining price movement, technical signals, and a…
The article describes how historical crypto options data can support market research, algorithm development, and portfolio management. It identifies implied volatility, realized volatility, open interest, put/call ratios, price and volume records, and order…
This translated discussion distinguishes the apparent simplicity of a trading rule from the difficulty of implementing and validating it. A basic buy-low, sell-high idea may be easy to state, but high-frequency firms must receive market data, calculate, and…
The script runs an EMA-crossover backtest on USD/JPY five-minute bid bars built from one-minute FXCM data. It configures a simulated margin venue, balances, fees, rollover interest, and probabilistic fills, then collects bars and fills from the engine. The…
This post describes a Chinese equities screening idea intended for use before 10 a.m. It combines a price ceiling below 20, a minimum amplitude threshold, exclusion of stocks marked ST, and a five-part limit-up method. The post also offers example formulas…
This Python utility collection supports quantitative factor analysis. It assigns factor observations to quantile or value-based bins, with options to bucket within groups or separate positive and negative signals. It also infers a trading calendar from…
This introductory guide outlines a retail trader’s path into quantitative trading. It describes using market data and mathematical models to generate decisions, learning market concepts and a programming language, building models from historical data, and…
This indicator is a visual aid for reviewing trades produced by a strategy tester. It reads graphical objects created by the tester and changes which objects are displayed, while retaining their names and coordinates. Because it works with those existing…
The article argues that a factor can be useful even when its strongest information lies in identifying poor-performing stocks. It describes ranking stocks into daily groups by factor value and interpreting unusually strong performance in the worst-ranked…
The document outlines a proposed screen for Chinese equities that combines small market capitalization, profitability, moving average alignment, and recent limit-up activity. Its initial description calls for at least five overlapping moving averages,…
This example outlines a China A-share stock selection and portfolio backtest workflow. It screens for eligible, non-suspended stocks, calculates 30-day and 90-day returns, and ranks those returns cross-sectionally. The illustrated filter favors stocks in the…
This document describes a command-line tool for creating, backtesting, and running editable LumiBot strategies. Its ordinary Python template demonstrates a long-only moving-average rule: retrieve recent daily prices, compare the latest close with a rolling…
The study groups fifty Wind order-flow measures into eight categories, including inflows, outflows, net active buying, and large-order flows. It evaluates these signals as stock-selection factors using portfolio sorts, cross-sectional regressions, and…
This brief Q&A explains how to change the scoring function used during hyperparameter search. The question asks how to include annualized return, win rate, and maximum drawdown alongside a Sharpe-based score. The response says the score function can read…
This crude oil strategy uses 15-minute bars to combine a five-bar average of candle fullness with a moving average oscillator built from five- and 50-period averages. Candle fullness is defined as the close-to-open move divided by the candle’s high-low…
This report utility converts daily account snapshots and trade records into tables, then calculates summary statistics for simulated futures accounts or stock accounts. For both account types it derives daily profit and returns, cumulative profit and loss…
The document explains how to enable TqSdk’s browser-based chart interface by setting the API’s web GUI option. It describes using an automatically assigned local address or supplying a fixed address, then illustrates a live setup that subscribes to a futures…
The document explains net income compound annual growth rate (CAGR) as an annualized measure of change between an initial and a later profit value. It distinguishes CAGR, which represents compounding across multiple periods, from a simple endpoint growth…