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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

79,386 documents

BigQuant

This support exchange concerns warnings from BigQuant’s feature extractor that it cannot find the open, high, low, close, and volume fields in its field mapping. The logs show the warnings recurring across multiple years while basic feature extraction still…

EquitiesTechnical indicators
MQL5 code base

This document describes an oscillator that expresses the percentage ratio between prices and candlestick sizes over a selected range. It identifies two settings: the calculation period, which determines the range length, and whether the range begins on the…

Technical indicatorsStatistics
MQL5 code base

This document outlines an Expert Advisor that trades when the Ozymandias indicator’s middle line changes color. It is a simple signal-based approach, with the color transition serving as the trade decision trigger. The system requires the compiled indicator…

ForexTechnical indicatorsTrend followingBacktesting
SuperMind

This Chinese-language post describes an equity screen combining price movement, large-order net volume, and valuation. It selects stocks with amplitude above 1, large-order net volume above 0.05 for at least three consecutive days, and positive P/E. The post…

EquitiesTechnical indicatorsVolatilityChina markets
Kraken Learn

This platform comparison organizes crypto futures venues around practical selection criteria: contract and market availability, fees, leverage, regional access, and security or regulatory status. Its table contrasts several exchanges, while the surrounding…

CryptoFuturesPerpetual futuresExecution
MQL5 code base

This automated trading system implements the principal components of the Original Turtle rules. It sizes positions according to market volatility, enters on breakouts of fast or slow Donchian channels, and skips a later signal after a successful breakout. It…

Trend followingBreakoutVolatilityPosition sizing
MQL5 code base

This indicator is described as a Donchian channel modified with a slope, with the Moving Average of Momentum mentioned as part of its use. Its key control is the xslope parameter: when set to zero, the indicator behaves like a regular Donchian channel. The…

Technical indicatorsMomentumBreakout
SuperMind

The document presents an equity screen using three conditions: daily price amplitude above 1%, RSI below 65, and the prior day’s price above its 250-day moving average. It frames the moving-average condition as a way to favor stocks with stronger long-term…

EquitiesTechnical indicatorsMomentumRisk management
BigQuant

The document describes a method for testing factor effectiveness dynamically and selecting stocks within industries. It examines whether differences in style-factor exposure relate to differences in stock returns, then uses the results to form industry-based…

EquitiesFactor investingStatisticsBacktesting
SuperMind

The document describes a Chinese equity screen restricted to the metaverse industry. It selects stocks whose opening price is near the ten-day moving average and whose weekly five-period moving average crosses above the ten-period average. The article…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This guide describes how a BigAlpha competition participant can build equity factors using BigQuant’s DAI data engine. The specified universe is the historical membership of the CSI 1000, and the listed inputs include one-minute bars and order-book…

EquitiesChina marketsFactor investingStatistics
SuperMind

The document presents a Chinese equity screen combining three conditions: MACD above its zero line, a price-change and very-large-order-flow condition, and a dividend ratio above 25% for 2019. It describes MACD as a trend filter and trading-flow data as a…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This proposed equity screen combines several filters: a reported increase in position holdings above 5%, a price change below 2.6% and above -5%, market capitalization no greater than 10 billion yuan, and a history without losses. The post interprets the…

EquitiesChina marketsFactor investing
MQL5 code base

This document describes configurable indicators for marking local highs and lows, also called swing points or fractals. A candidate high or low is identified by comparing a candle with neighboring candles. Users can set the neighborhood radius, which lets…

Technical indicatorsForex
BigQuant

This overview explains the main stages of a machine-learning workflow for quantitative investing, using a fruit-selection analogy to introduce training data, labels, features, prediction, and validation. It recommends defining the market and stock universe,…

EquitiesMachine learningFactor investingBacktesting
MQL5 code base

ASQ SuperTrend is described as an ATR-based trend-following indicator for MetaTrader 5. It draws a changing line around price, uses color to indicate bullish or bearish direction, and marks trend reversals with arrows. The line can be used to track a trend…

Trend followingTechnical indicatorsVolatilityRisk management
SuperMind

This Chinese equity screening proposal selects stocks with amplitude above 1, a specified ratio between yesterday’s turnover rate and today’s auction volume relative to yesterday’s volume between 0.5 and 2, and a circulating share count no greater than 5.5…

EquitiesVolatilityChina marketsTechnical indicators
Qlib

This Qlib demonstration explains how to reuse a processed data handler across repeated model training runs. It first trains the same configured task more than once without explicitly reusing the handler, then constructs the configured data handler in memory…

Backtesting
SuperMind

This Chinese stock screen combines three conditions: amplitude above 1, a shrinking negative MACD histogram on a 15-minute chart, and prior-day trading value above 60 million. The document interprets amplitude as a way to find more volatile stocks, the MACD…

EquitiesTechnical indicatorsVolatilityChina markets
SuperMind

The document describes a simple A-share stock screen using a minimum daily high-low range, a specified closing price, and a bounded daily return. It frames the filters as a way to select for price movement while restricting the current price and recent…

EquitiesChina marketsTechnical indicatorsBacktesting
BigQuant

This research summary examines stock selection factors derived from operating financial statement items, especially changes in operating current liabilities. It reports that these factors showed selection ability, with the strongest cited result for a…

EquitiesFactor investingChina marketsBacktesting
Amberdata research

The article explains why investment managers entering digital assets need consolidated data on markets, liquidity, risk, and blockchain activity. Crypto trading is spread across global venues that operate continuously, with each venue using its own changing…

CryptoMarket microstructureOn-chain dataExecution
BigQuant

This research overview examines risk parity within the broader development of portfolio allocation methods. It describes several risk measures and risk-allocation principles, emphasizing Euler allocation to define each asset’s contribution to portfolio risk.…

Multi-assetPortfolio constructionRisk managementBacktesting
MQL5 code base

This MetaTrader indicator overlays candles from a higher timeframe as filled rectangles, using DRAW_FILLING buffers. Their colors follow the cloud direction of the CronexAC indicator: bullish or bearish cloud states determine the candle body color, while the…

Technical indicatorsTrend followingExecution