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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
Quantpedia
86 documents
TqSdk
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

ProRealCode

This indicator labels price bars using comparisons between each bar’s high and low and those of the preceding bar. It distinguishes inside bars, outside bars, bars making both a higher high and higher low, and bars making both a lower high and lower low. The…

Technical indicatorsEquities
SuperMind

The document describes a Chinese equity screening rule combining three conditions: daily amplitude above a threshold, evidence of main-fund control on the previous day, and a close above the previous day’s low. It frames the combination as a way to find…

EquitiesTechnical indicatorsChina markets
BigQuant

This brief support note addresses a BigQuant workflow where a ranking strategy appears to backtest normally but produces no rebalance signals in simulated trading. It points to configuration and data-window checks: bind the code-list module’s end date to…

BacktestingEquities
SuperMind

This stock screen selects companies associated with the metaverse concept, then applies a price condition and a relative-volume band. It requires the close to exceed the previous session’s low and volume relative to its five-session average to be above 1.5…

EquitiesChina marketsTechnical indicatorsRisk management
SuperMind

This Chinese equity screen combines three conditions: at least five moving averages are described as converging, the tradable share float is no more than 5.5 billion shares, and the ten-day return is positive but below 35%. The article frames this…

EquitiesMomentumTechnical indicatorsChina markets
MQL5 code base

The document describes a small expert advisor that manages an already open position using a trailing stop distance supplied by the trader. If that requested distance is smaller than the platform’s allowed minimum stop distance, the advisor adjusts it to the…

ExecutionRisk management
SuperMind

This stock screen combines turnover between 3% and 12% with seven consecutive sessions in which the closing price falls, then filters for a daily price change below 2.6% and above -5%. The article presents the rule as a way to find stocks after a sustained…

EquitiesMean reversionTechnical indicatorsChina markets
NautilusTrader

The guide explains how NautilusTrader connects to Bybit for live market data and order execution across spot, linear and inverse contracts, and options. It describes product-specific symbol suffixes, instrument loading, and the differences among mainnet,…

CryptoExecutionMarket microstructureSpot markets
SuperMind

This stock screen combines three daily price conditions: amplitude greater than 1%, an opening price within 5% of the 10-day moving average, and a current low below the previous day's low. The document includes formula and Python examples for calculating…

EquitiesTechnical indicatorsVolatilityChina markets
SuperMind

This equity screen targets stocks in the metaverse sector that recorded a limit-up move within the prior 25 days and whose opening price falls between 2% below and 5% above the reference close. The post describes selecting candidates before 10 a.m. for…

EquitiesChina marketsMomentumBreakout
SuperMind

This stock screen combines a daily turnover rate between 3% and 12%, a positive change in the KDJ K value, and an indicator intended to identify institutional accumulation. The document provides formula and Python examples, with the Python version also…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

The document explains the Crank–Nicolson implicit finite-difference scheme for solving the one-dimensional heat equation. It contrasts this approach with an explicit method that requires small time steps, describing Crank–Nicolson as averaging spatial…

Statistics
BigQuant

The document introduces a moving-average arrangement scoring model, or MASS, that assesses market direction and trend strength from the relative ordering of multiple moving averages. It aims to combine the smoothness of longer averages with the quicker…

EquitiesTrend followingMomentumTechnical indicators
SuperMind

The document proposes a stock screen combining three conditions: relatively large price amplitude, upward divergence in the day’s moving averages, and a limit-down price at the prior session’s 9:15 matching stage. The stated rationale is to find volatile…

China marketsEquitiesTechnical indicatorsMean reversion
MQL5 code base

This document describes a MetaTrader 5 class for rebuilding closed trades from their opening and closing deals in account history. The history is selected over a time range and organized by close time; callers can then enumerate reconstructed trades or…

BacktestingStatisticsRisk managementExecution
MQL5 code base

This short reference describes a higher-timeframe variant of the LeManChanel indicator for MetaTrader 5. The indicator exposes a timeframe input, with a four-hour period shown as the default, so users can select the chart period from which the indicator…

Technical indicators
MQL5 code base

The document describes a chart indicator that automatically positions two standard deviation channels. It offers a visual channel-based view of price behavior, but does not explain the calculation method, how the channels are anchored, or how a trader might…

Technical indicatorsVolatility
SuperMind

This Chinese A-share stock screen selects shares with a daily high-low range above a stated threshold, while excluding Beijing-listed stocks and specified board categories. The article also describes a refinement that keeps prices close to a 60-period moving…

EquitiesChina marketsTechnical indicatorsRisk management
MQL5 code base

The document outlines a function for opening a trade in an MQL5 environment. It describes deriving an opening price and take-profit and stop-loss levels from symbol data and user parameters, then preparing a trade request with details such as instrument,…

ExecutionRisk management
MQL5 code base

CronexCCI adapts the MACD concept by applying it to a time series of Commodity Channel Index (CCI) values instead of prices. It displays the resulting indicator as a colored cloud, offering a visual way to examine changes and relationships in the transformed…

Technical indicators
Qlib

This paper description presents a learnable scheduler for sequence-learning problems with related prediction tasks, such as forecasting returns at different future horizons. During training, the scheduler chooses an auxiliary task based on the current model…

Machine learningEquitiesChina marketsBacktesting
BigQuant

This forum post presents a workflow for combining predictions from three model outputs. It merges the datasets on instrument and date, preserves columns that are not already present, renames each model’s prediction column, and computes their arithmetic mean…

Machine learningPortfolio constructionBacktesting
MQL5 code base

This short indicator description introduces round price levels as possible support or resistance. It gives EUR/USD examples at prices ending in two zeroes after the decimal point and describes an indicator that displays the two nearest such levels above the…

ForexTechnical indicators