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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
Quantopian lectures
45 documents
Binance API docs
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

79,386 documents

MQL5 code base

This document describes a smoothed correlation indicator intended to distinguish trending price action from ranging or erratic movement. It calculates a bar-to-bar correlation coefficient over a correlation period and then applies smoothing, with both…

Technical indicatorsStatisticsTrend followingMean reversion
SuperMind

This stock-screening proposal selects equities whose 5-, 10-, 20-, 30-, and 60-day moving averages converge, with turnover above 2% and below 9%, and a dividend payout ratio above 25% for 2019. The author interprets clustered short- and medium-term averages…

EquitiesTechnical indicatorsFactor investing
FMZ forum

This introductory programming note describes several Python mistakes that can make code behave unexpectedly or become harder to maintain. It recommends checking which Python version a program targets, favoring clear code over compressed one-liners, and…

StatisticsExecution
vn.py community

This short forum exchange discusses how to handle large orders when building options strategies with the elite_optionstrategy module. A response explains that the module does not provide detailed control over placing and canceling orders. Instead, it…

OptionsExecutionMarket microstructure
SuperMind

This overview organizes common machine learning methods in two ways: by their form or function, and by how they learn from data. It surveys regression, instance-based methods, regularization, decision trees, Bayesian methods, clustering, association rules,…

Machine learningStatistics
Cryptohopper blog

The document explains how cryptocurrency traders can use automated triggers to adapt buying behavior to market conditions. Its trend example uses a fast 10-period EMA and a slow 20-period EMA on a daily chart: a bullish signal enables buying, while a bearish…

CryptoTrend followingTechnical indicatorsRisk management
MQL5 code base

The indicator described here creates an index for one of the eight major currencies from a configurable basket of as many as ten components. Users can select currency pairs or other instruments, turn each component on or off, and choose whether to invert the…

ForexTechnical indicatorsPortfolio construction
vn.py community

This Chinese research summary examines whether intraday data can support sector rotation signals, focusing on realized skewness and the share of volatility attributable to downside moves. It describes constructing industry level factors inspired by high…

China marketsEquitiesHigh-frequency tradingVolatility
MQL5 code base

This MetaTrader expert advisor combines three moving averages with the Moving Average of Oscillator and Relative Vigor Index indicators. It evaluates signals only when a new bar forms, and exposes a minimum separation setting for the moving averages. The…

ForexTechnical indicatorsRisk managementPosition sizing
SuperMind

The document describes a short-term stock screen combining daily price range, company size, profitability, and a reversal pattern called a bearish-to-bullish “wraparound” or reversal setup. Its proposed criteria include a daily range above one percent,…

EquitiesTechnical indicatorsMean reversionRisk management
BigQuant

A trader reports that a stock-selection strategy using TA-Lib indicators produces different results each time it is run. The response points to an SQL query in one module that lacks an explicit sort order as the likely cause. When rows arrive in an…

BacktestingStatistics
MQL5 code base

Paromon is a chart indicator that marks the start of each trading day and displays that day’s high and low prices. Its purpose is to make the daily range visible on a price chart, which can help traders orient intraday price action around the session’s…

Technical indicators
MQL5 code base

The document briefly describes an indicator built from two Double Exponential Moving Averages applied to averaged high and low price series. Together, these averages form a channel. Candles that move beyond the channel receive a color associated with the…

Technical indicatorsTrend followingBreakout
SuperMind

The document presents a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, displayed first-level bid volume greater than ask volume, and reported holder concentration below 20%. The candidates are then ranked by price change,…

EquitiesChina marketsMarket microstructureBacktesting
ProRealCode

The document describes a configurable engine that combines up to 11 common indicators into long or short signals. Users can require every enabled indicator to agree or allow any one of them to trigger. The indicators include moving average crossovers, RSI,…

Technical indicatorsRisk managementBacktestingTrend following
SuperMind

The document presents a method for moderating drawdowns by reducing the capital base used to size trades as portfolio value falls. It first defines maximum drawdown as the largest peak-to-later-trough decline relative to the earlier value. Its adjustment…

Risk managementPosition sizingBacktestingEquities
BigQuant

This article proposes a compact framework for reviewing the equity market by sector rather than inspecting every stock individually. To gauge sector persistence, it counts stocks moving from an initial limit-up session to a second consecutive limit-up…

EquitiesMomentumRisk managementChina markets
quant-trading

The document outlines a mean-reversion strategy for two assets selected for cointegration. It uses the Engle–Granger two-step approach: regress one price series on the other, test whether the residuals are stationary, then fit an error-correction model and…

Pairs tradingMean reversionStatisticsBacktesting
MQL5 code base

The document explains how to create synthetic currency strength instruments in MetaTrader 5. For each currency, it combines readings from several currency pairs, where each reading represents the close price’s position within the recent high-low range. The…

ForexTechnical indicatorsMulti-asset
BigQuant

This research summary describes a study of retail investor attention and asymmetric volatility in China’s A-share market. The authors use the balance of positive, negative, and neutral posts on online stock message boards to construct a proxy for asymmetry…

EquitiesChina marketsSentimentVolatility
BigQuant

This user post describes rolling model training for stock forecasts using two approaches. The StockRanker example updates the model annually, fitting on one year of data and predicting over the following year. The XGBoost example instead constructs monthly…

EquitiesMachine learningBacktesting
BigQuant

This Chinese equity research excerpt analyzes the beer industry’s shift from pursuing output scale toward improving profitability through premium products. It separates the outlook into volume and price per ton: production depends on the number of operating…

EquitiesChina marketsFactor investing
Amberdata research

The primer explains how Curve developed from a stablecoin-focused automated market maker into a broader DeFi ecosystem. It contrasts Curve’s dynamic invariant with constant-product pricing: the curve is flatter when a pool is balanced to reduce slippage,…

CryptoDeFiMarket makingRisk management