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 explains a replay mode for reviewing a trading strategy against historical market data for a chosen trading day. Unlike event-driven backtesting, replay is time-driven: the service streams the day’s historical data for subscribed contracts,…
This report tests the ratio of research and development spending to revenue as an equity-selection factor across industries. Single-factor tests find some effectiveness in technology-oriented sectors, including pharmaceuticals, electronics, communications,…
A short forum exchange asks how to obtain roughly two decades of historical futures and options data at hourly, daily, weekly, and monthly frequencies for backtesting. One reply says that such data must be purchased, particularly minute-level data. The…
This Chinese stock-screening example combines a high-amplitude condition with a morning-star candlestick pattern and a rounded price shape. Its Python illustration adds filters for listing market, market capitalization, positive earnings, and a recent close…
The document gives a brief historical overview of quantitative investing. It describes how advances in computing made it practical to store and process large amounts of historical data, supporting the use of statistical and mathematical models in investment…
This expert advisor describes a trend-following system using two ColorX2MA indicators on separate timeframes. The slower indicator sets the prevailing trend from its line color; the faster indicator supplies entry timing when its color changes. A signal is…
A BigQuant user raises a timing problem involving premarket data processing in backtests. In the example, a signal generated on one day leads to an order for the next day; premarket history in the backtest appears to expose that day’s open and close. Such…
This strategy combines daily mid-level filters with gap-related price comparisons to generate one long or short trade during the 9:00 AM bar. It calculates the midpoint of the prior day and the midpoint of the highest high and lowest low across configurable…
This stock-selection approach combines a price-movement filter, a weekly moving-average crossover, and valuation bounds. It screens Shenzhen Main Board stocks for amplitude above 1, a weekly five-period moving average crossing above the ten-period average, a…
This documentation explains how VeighNa Elite Trader’s option strategy module supports strategy setup, initialization, automated trading, monitoring, and removal. It describes the ContractManager’s role in loading daily contract information and maintaining…
This repository overview describes a Python framework for building rule-based strategies, AI-assisted decision systems, and combinations of the two. Its central workflow is to test strategy decisions on historical data, inspect simulated orders and reports,…
This example shows how to replay lower-timeframe price data as daily, weekly, or monthly bars in Backtrader. A simple strategy calculates a configurable simple moving average and prints lifecycle messages as the replayed data advances. The script lets users…
This report challenges mean-variance optimization assumptions that returns are normally distributed, volatility captures risk symmetrically, and portfolios should maximize return per unit of risk. It instead frames investor concerns as preserving principal…
This page describes an Expert Advisor that uses the EMAAngle indicator as an initial directional gate, then checks additional indicators, including Laguerre RSI with a Laguerre filter, two moving averages, and CCI. It states that the EA compares the EMAAngle…
This reference describes several candidate fitness objectives for genetic programming that produces equity factors. It defines IC information ratio as the mean information coefficient divided by its standard deviation, with the information coefficient…
This 2017 review compares commodity trading adviser factors and explores ways to combine them. It covers time-series and return-signal momentum, roll yield, basis momentum, and changes in warehouse receipts and inventories. The report says standalone…
This Expert Advisor implements a Bill Williams style trend entry by placing pending orders around fractal breakouts. It places a stop at the Alligator Lips level and sets profit targets at Fibonacci extensions. The first order is described as twice the size…
HftBacktest uses Numba-compiled classes and strategy functions, so importing the library and compiling a strategy can add startup time before a backtest begins. The document describes enabling Numba’s cache option on a strategy function so compiled code can…
This Expert Advisor trades when the XAng_Zad_C indicator cloud changes color. It can restrict entries to a configured daily time window and close open positions at the selected end time. If the start time falls later than the end time, closure is scheduled…
This reference distinguishes local simulation accounts from remote Quick simulated accounts for futures and stocks. It describes TqSim as a local futures simulation option for development and backtests, TqKq as a Quick linked futures account, and…
This Expert Advisor design runs separate long and short trading systems based on signals from the ColorMETRO indicator. Inputs with one prefix control long trades, while another group controls short trades; each side has its own magic number, position-sizing…
This documentation explains how Freqtrade strategy callbacks complement vectorized indicator and signal functions. Callbacks run when needed, often repeatedly during live trading or at each simulated candle, so the guidance warns against costly calculations…
This document outlines an Expert Advisor that uses the RSIOMA_V2 indicator to generate trade decisions. It describes three possible triggers: a change in direction of the fast cloud envelope, a move through an oversold or overbought level, or a change in the…
This strategy uses the range-based RSRS indicator to time exposure and rotate between large-cap and small-cap Chinese equity ETFs. It fits a rolling ordinary least squares regression of daily highs on lows, standardizes the recent regression slope, and…