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Knowledge library

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.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

16,761 documents

vn.py community

This brief forum exchange describes a live-trading problem: a VeighNa strategy initializes and starts, market data appears connected, and its entry condition is met, yet it sends no order. The author reports that the same strategy behaves as expected in…

ExecutionBacktesting
MQL5 code base

This expert-advisor description outlines a trading system that acts when a bar closes and the AverageChangeCandle indicator changes direction. It identifies the indicator file needed for the advisor to run and notes that its trading library assumes brokers…

ForexTechnical indicatorsBacktestingExecution
BigQuant

This research reviews technology-focused equity indices in China, comparing their historical performance, construction rules, and constituent distributions. It then examines whether patent information can improve index selection. The proposed patent measures…

China marketsEquitiesFactor investingBacktesting
SuperMind

The article describes a short-term A-share screening rule that combines price range, closing price, and the session’s low relative to the previous close. Its initial version calls for amplitude above one percent, a close at 18.5 yuan, and a maximum decline…

EquitiesChina marketsTechnical indicatorsBacktesting
MQL5 code base

This Expert Advisor bases its trading signals on the BlauTVI trend indicator. It enters when the indicator histogram changes direction, with the signal checked after a bar closes. The rule therefore treats a shift in histogram slope or direction as a…

ForexTechnical indicatorsTrend followingBacktesting
MQL5 code base

This Expert Advisor uses the ColorSchaffMFITrendCycle oscillator to generate trades when its position crosses an overbought or oversold level. Signals are evaluated when a bar closes, so the described trigger depends on a completed bar rather than an…

ForexTechnical indicatorsBreakoutBacktesting
MQL5 code base

The document briefly introduces Walter Downs’ Point of Balance Oscillator, describing a bar-color display intended to show the prevailing trend in the current balance. The color marks the balance associated with the current trend. An opposite-color signal is…

Technical indicatorsTrend followingBacktesting
Cryptohopper blog

This beginner-oriented guide surveys tools for working in cryptocurrency markets, which it characterizes as continuous, volatile, and crowded with many tokens. It groups tools by task: market data for checking prices, volume, capitalization, and charts;…

CryptoTechnical indicatorsExecutionBacktesting
BigQuant

This report adapts hidden Markov models (HMMs), a technique associated with speech recognition, to rank stocks by the likelihood of an upward move. It assumes that rising and falling stocks follow distinct patterns and models those patterns separately. Six…

EquitiesMachine learningFactor investingBacktesting
BigQuant

This report outlines a method for analyzing open-ended bond fund returns and deriving a residual alpha measure for fund screening. It groups risk exposures into eight factors spanning interest-rate curve movements, credit risk, equity markets, and money…

Fixed incomeFactor investingStatisticsBacktesting
vn.py community

This VeighNa community contribution describes additions to a backtesting statistics engine for evaluating strategies with regressed annual return (RAR), R-Cubed, and Robust Sharpe. RAR is calculated by regressing cumulative returns across time intervals and…

BacktestingStatisticsRisk management
SuperMind

The screen combines a relative strength index below 65 with a ratio of external to internal trading volume above 1.3, then ranks qualifying stocks by the day’s auction amount and selects the top five. The document presents both a database-style query and a…

China marketsEquitiesTechnical indicatorsMarket microstructure
BigQuant

This research summary presents a framework for timing equity factors whose returns have become less reliable. It reviews indicators such as valuation spreads and pairwise correlations, and examines their relationship with future factor returns. A random…

Factor investingMachine learningEquitiesPortfolio construction
Hummingbot docs

Hummingbot version 2.2.0 adds two trading controllers to its V2 framework. The Arbitrage controller is designed to trade price differences between spot venues, including automated market makers and central limit order books. It supports configurable exchange…

ArbitrageGrid tradingExecutionBacktesting
BigQuant

This document outlines a long-horizon commodity futures strategy that uses machine learning to forecast the following week’s direction. It calculates signals at the end of each week and adjusts positions on the first trading day of the next week using TWAP…

CommoditiesFuturesMachine learningBacktesting
SuperMind

This document describes a Chinese equity screen combining daily turnover with growth in net profit attributable to the parent company. It selects stocks with turnover between 3% and 12%, profit growth above 20% and up to 100%, and an earnings forecast for…

EquitiesChina marketsFactor investingBacktesting
SuperMind

This document outlines a stock-selection screen requiring MACD above zero, upward-moving averages, and at least one limit-up event during the preceding 25 days. The conditions are framed as signals of positive trend and recent market attention. It includes…

EquitiesMomentumTechnical indicatorsBacktesting
BigQuant

This practitioner note compares very high-return, moderate-return, and lower-return backtests for short-horizon equity models, focusing on whether their apparent performance persists out of sample. The author reports that aggressive timing filters and models…

EquitiesMachine learningFactor investingBacktesting
BigQuant

This research summary presents factor timing as a risk-control problem rather than solely as a forecast of factor returns. In a multi-factor portfolio, the approach adjusts upper and lower bounds on factor exposures. Those bounds are tied to factor risk,…

Factor investingRisk managementPortfolio constructionBacktesting
Lumibot

This engineering guide explains how to locate backtest slowdowns while preserving simulation behavior. It separates startup, historical data loading, strategy computation, and report generation, and recommends first distinguishing cold runs that fetch data…

BacktestingExecutionOptions
BigQuant

This discussion contrasts quantitative trading with manual trading, emphasizing that the main difference lies in execution. It characterizes quantitative trading as using mathematical or statistical models and historical data to identify strategies that may…

StatisticsExecutionRisk managementBacktesting
MQL5 code base

The document describes an indicator concept that searches across moving-average periods and selects one using historical trade expectancy, combining win rate with average reward. It also proposes using maximum favorable excursion to estimate a typical trend…

Technical indicatorsTrend followingStatisticsBacktesting
MQL5 code base

This document describes an Expert Advisor that opens trades when the DynamicRS_C indicator changes direction. It gives a practical setup requirement: the compiled indicator must be placed in the platform’s indicators folder. It also notes that a supporting…

ForexTechnical indicatorsBacktesting
MQL5 code base

This document describes a modified chart indicator for practicing and reviewing manual trading strategies on historical data. It produces operation reports in tables and charts and saves chart templates, with and without annotations. The stated purpose is to…

BacktestingRisk managementPosition sizingExecution