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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

22,592 documents

SuperMind

This document describes an equities screening rule combining a turnover range, beverage and alcohol industry classification, and a comparison between displayed best bid and ask quantities. It presents the intended screen as selecting stocks with turnover…

EquitiesMarket microstructureTechnical indicatorsBacktesting
FMZ forum

This note introduces the Easley, Kiefer, O’Hara, and Paperman (EKOP) model to explain how informed and uninformed trading can shape a stock’s bid-ask spread. It describes a discrete-day, continuous-within-day setting in which information events may be good…

EquitiesMarket makingMarket microstructureStatistics
SuperMind

This document describes a short-term Chinese equity screen using three conditions: a share price below 12, more than two limit-up sessions within ten days, and amplitude above one. It frames repeated limit-ups as a possible sign of continued upside and…

EquitiesMomentumBreakoutChina markets
SuperMind

This stock-screening idea combines three conditions: a rising 30-day moving average, three consecutive declining sessions, and a reported increase in position or capital inflow greater than five percent. The rationale pairs a positive longer-term trend with…

EquitiesTechnical indicatorsMean reversionMomentum
SuperMind

This Chinese equity screen requires turnover between 3% and 12%, a rising DEA condition, and a reversal pattern described as a rebound after a short pullback. The note frames turnover as a measure of trading activity and rising DEA as evidence of an upward…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese stock-selection rule combines three filters: rank stocks among the top 100 by volume ratio, rank the top 100 by the absolute difference between the previous day’s limit-down price and opening price, and require at least two limit-up days within…

EquitiesMomentumVolatilityChina markets
SuperMind

This note describes a Chinese equity screen that selects beverage and alcohol import-export companies in 2021 when the daily high-to-low range exceeds 1% of the low. The stated rationale is that larger ranges may indicate volatility and return potential,…

EquitiesVolatilityChina markets
SuperMind

The post presents a Chinese-stock screening idea that combines a price-amplitude threshold with a range for yesterday’s turnover multiplied by today’s auction volume relative to yesterday’s volume. It also requires circulating market capitalization above a…

China marketsEquitiesTechnical indicatorsFactor investing
BigQuant

The post asks why a BigQuant strategy raises a parser error near FROM. Its factor expression defines several intraday features, including a bid-ask spread measure, weighted order-book volume imbalance, early-session price movement, and a volume ratio, then…

EquitiesMarket microstructureTechnical indicatorsExecution
SuperMind

The document describes a TD-style timing system attributed to Thomas DeMark. It begins with a setup: compare each close with the close a fixed number of bars earlier, and require that relationship to persist for a specified run of bars. A falling sequence…

China marketsEquitiesTechnical indicatorsTrend following
SuperMind

This Chinese-language post outlines a stock screen combining daily amplitude above 1, a condition described as main-force control on the prior day, and a newly formed KDJ golden cross. It interprets the range condition as a sign of greater movement, the…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese-language note proposes a daily, after-close stock screen requiring MACD to be positive and the reported daily position-increase share to exceed 5%. It then ranks qualifying stocks by descending popularity or heat, with an example that returns…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese-language strategy note describes a stock-selection screen combining turnover between 3% and 12%, a rising DEA measure, and a 20-day moving average above the 120-day average. It presents the screen as a way to find stocks with trading activity…

EquitiesChina marketsTechnical indicatorsMomentum
Lumibot

The document explains how to use ThetaData as a historical data source for LumiBot backtests covering stocks and options, as well as other asset types. It supports minute and daily bars directly; hourly bars can be built from minute data. Downloaded data is…

OptionsEquitiesBacktestingExecution
SuperMind

This post outlines a China A-share screening rule for stocks classified in the metaverse sector. It first describes selecting names with prior-day turnover above a threshold and positive institutional activity, then gives a final rule using prior-day…

EquitiesChina marketsFactor investingBacktesting
BigQuant

This post reports a suspected mismatch in BigTrader v35 minute backtests after an ETF share split. The author says the strategy-visible position fields—quantity, cost price, last price, and market value—appeared to retain their pre-split values, while a…

EquitiesBacktestingExecutionRisk management
SuperMind

The document presents a Chinese equity screening rule that selects stocks with amplitude above 1, circulating market capitalization above 10 billion yuan, and at least two limit-up events over the prior 500 days. It frames the combination as a way to find…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This post describes a Chinese stock screen based on daily amplitude, circulating market capitalization, and association with a robotics concept. Its narrative specifies amplitude above 1, a market-cap threshold above 10 billion yuan, and a cap below 10…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This post presents a Chinese equity screening rule combining RSI below 65, a rising KDJ K line, and an amplitude measure above 1. The accompanying indicator reference uses a 14-period RSI, a 9-period stochastic calculation with 3-period smoothing, and…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The document proposes a Chinese equity screen based on a daily price range above a stated threshold, a product combining the prior day's turnover rate with the ratio of current auction volume to prior volume, and a closing price below 12. It frames these…

China marketsEquitiesTechnical indicatorsStatistics
BigQuant

This weekly market review summarizes Chinese economic and financial developments for August 8–12, 2022. Its macro section reports trade growth and foreign-exchange reserve changes, alongside selected global policy and company news. The market section…

China marketsEquitiesFuturesFactor investing
BigQuant

This brief strategy note outlines an equity selection approach using a random forest regression model. It adds features such as beta and technical indicators, including MACD and Williams %R, and predicts a return-style target calculated from the difference…

EquitiesMachine learningTechnical indicatorsPosition sizing
BigQuant

This research summary proposes measuring whether trading in a stock is unusually one-sided. It classifies five-minute candles by their bodies as consensus or non-consensus activity, then measures consensus volume as a share of daily volume. Splitting that…

EquitiesFactor investingMomentumStatistics