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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
WonderTrader
14 documents
Alphalens
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

FMZ forum

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…

CryptoExecutionBacktestingMarket microstructure
SuperMind

This post outlines an A-share screen that combines RSI below 65, parent-company net profit growth above 20% and no more than 100%, and three consecutive declining sessions. It presents the combination as a way to identify stocks with both technical weakness…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This post proposes an A-share stock screen combining a daily price range of at least one percent with a volume ratio between 1.5 and 6. It also applies two concentration-related filters based on circulating market value and total shares. The rationale is to…

EquitiesVolatilityTechnical indicatorsRisk management
MQL5 code base

This trading-tool description argues that viewing positions and risk as percentages can help traders manage emotions and apply a consistent plan. It illustrates how traders following the same plan may make different decisions, such as holding losing…

Risk managementPosition sizing
BigQuant

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…

EquitiesTechnical indicatorsBacktestingStatistics
SuperMind

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…

EquitiesTechnical indicatorsTrend followingBacktesting
SuperMind

This stock screen targets companies classified in the metaverse theme that recorded at least one limit-up event within the prior 25 days, while excluding Beijing-listed A-shares. The post presents this as a way to identify candidates with potential short- to…

EquitiesChina marketsBreakoutTechnical indicators
SuperMind

This stock-selection example combines a relative strength index below 65 with a rise in current volume relative to the prior session, then applies a 2021 date condition. The post frames the RSI threshold as identifying weaker stocks and the volume condition…

EquitiesChina marketsTechnical indicatorsMomentum
Amberdata research

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…

CryptoOptionsVolatilityBacktesting
ProRealCode

Haos Visual is described as a zero-centered histogram indicator built from two Williams %R oscillators smoothed with T3 calculations using different lookback periods. The shorter oscillator uses a 14-period Williams %R input, while the slower one uses a…

Technical indicatorsMean reversionVolatilityTrend following
MQL5 code base

This document introduces an indicator that plots two channels of moving averages derived from high and low prices. Users can configure a fast and a slow channel by choosing the period and calculation method for each moving average. The examples illustrate…

Technical indicatorsTrend following
FMZ forum

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…

High-frequency tradingBacktestingStatisticsExecution
SuperMind

This document describes a daily stock screen for companies classified in the metaverse industry. It selects stocks with a newly formed KDJ bullish crossover and a positive price-to-earnings ratio, then limits candidates to actively trading stocks identified…

EquitiesChina marketsTechnical indicatorsMomentum
NautilusTrader

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…

ForexTechnical indicatorsBacktestingExecution
SuperMind

The document outlines a Chinese A-share stock screen that combines RSI below 65, an external-to-internal trade ratio above 1.3, and recent consecutive limit-up activity. It interprets the RSI threshold as avoiding an overbought condition, the trade ratio as…

EquitiesTechnical indicatorsMomentumChina markets
vn.py community

This forum exchange documents a connection problem between VeighNa's CTP interface and a Guangfa Futures simulation system. The user reports running a newer CTP interface build than the simulation system's stated version; connections to another simulation…

FuturesExecution
SuperMind

This post outlines a Chinese equities screen that selects stocks with a stated amplitude above 1, a price below 20, and positive net buying attributed to major participants during the opening auction. It provides example indicator and Python-style…

China marketsEquitiesTechnical indicatorsMarket microstructure
SuperMind

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…

China marketsEquitiesTechnical indicatorsBacktesting
ProRealCode

This indicator automatically draws horizontal reference levels near the current Forex price. It rounds the close to a nearby base level, then checks whether adjacent levels fall within a specified distance before drawing them. It uses one rounding scale for…

ForexTechnical indicators
Alphalens

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…

Factor investingBacktestingStatistics
BigQuant

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…

BacktestingRisk managementPosition sizingPortfolio construction
MQL5 code base

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…

BacktestingTechnical indicators
MQL5 code base

This indicator describes a breakout approach built around a channel drawn through peaks from a Zigzag2_R indicator. It generates alerts when price moves outside the channel, with the stated purpose of signaling a possible change in direction. After a…

BreakoutTechnical indicatorsTrend following