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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

22,592 documents

SuperMind

This community post outlines a China A-share stock screen that excludes Beijing-listed companies and selects stocks with turnover between 3% and 12% and a positive but limited recent price gain. It then proposes refining the candidates using net profit…

EquitiesChina marketsMomentumFactor investing
BigQuant

The document reviews research on whether investor sentiment helps explain stock return anomalies or appears predictive because of spurious regression. Persistent predictors can seem to forecast returns in finite samples when expected returns also vary over…

SentimentStatisticsFactor investingEquities
SuperMind

This Chinese-language post describes an A-share screening idea that combines daily turnover between 3% and 12%, a newly formed KDJ bullish crossover, and a company-type filter. It frames turnover as a liquidity condition and the KDJ signal as a short-term…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

This research summary examines high-frequency equity factors built from minute bars, tick data, and transaction-level records. The factors capture intraday skewness, downside volatility, reversals, late-session trading, price-volume relationships,…

EquitiesChina marketsHigh-frequency tradingFactor investing
SuperMind

This proposed Chinese equity selection rule screens for stocks with turnover between 3% and 12%, then requires the product of the day’s percentage price change and net buying flow attributed to very large orders to be positive. Eligible stocks are ranked by…

EquitiesChina marketsMomentumSentiment
BigQuant

This brief exchange explains how to exclude Beijing Stock Exchange listings when labeling Chinese A-share stocks with a default template. It recommends using an A-share filtering module or adding a custom Python filter to the workflow. The suggested…

EquitiesChina markets
SuperMind

This stock-selection screen filters for turnover between 3% and 12%, circulating market capitalization between 1 and 55 in the stated units, and at least one daily gain of 10% or more during the previous 25 trading days. The post gives both a formula-style…

China marketsEquitiesMomentumTechnical indicators
SuperMind

The proposed equity screen selects stocks with RSI below 65, seven consecutive down sessions, and a 20 day moving average above the 120 day average. The combination looks for a recent pullback within a longer-term upward trend, using the RSI threshold as an…

EquitiesTechnical indicatorsMean reversionTrend following
SuperMind

The document presents a Chinese stock selection rule combining daily amplitude above 1, a morning-star pattern, and weekly MACD above zero. Its indicator examples add moving-average ordering and other price, volume, and size conditions. The intended…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

This research summary explains a dynamic firm model in which companies can expand or shrink their operating scale, but face adjustment costs. Expansion and contraction options alter exposure to productivity shocks: the ability to reduce scale can buffer…

EquitiesFactor investingPortfolio constructionStatistics
SuperMind

The document describes a Chinese equity screen requiring a position increase above 5%, evidence of large-investor control on the prior day, and a gain below 6% at 9:25. Its rationale is that rising holdings may indicate inflows, institutional ownership may…

EquitiesChina marketsTechnical indicatorsMomentum
FMZ forum

The article describes an intraday pairs strategy for SPY and IWM, using one-minute bars from April 2007 through February 2014. It aligns timestamps, estimates a rolling regression hedge ratio, forms a price spread, and converts that spread to a z-score. The…

EquitiesPairs tradingMean reversionBacktesting
SuperMind

This stock screen combines three filters: a daily price range above a stated threshold, the closing price above its five-day moving average, and a dividend payout ratio above 25% for 2019. The article presents the range condition as a way to find stocks…

EquitiesTechnical indicatorsVolatilityChina markets
SuperMind

This stock-selection idea filters for companies in the metaverse industry, then looks for a rising five-day moving average and a potential start of a strong advance. The proposed rules combine an industry classification with price and volume conditions,…

EquitiesMomentumTechnical indicatorsChina markets
SuperMind

This Chinese equity screening idea combines three signals: today’s position increase share above 5%, the product of daily return and net large-order volume above 0.5, and a shortening MACD histogram green bar on a 15-minute chart. The document interprets the…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

The report treats corporate events as equity style factors and evaluates them within a multi-factor research framework. It describes differences in event prevalence across industries and relationships between event factors: private placements and dividends…

EquitiesFactor investingEvent-drivenStatistics
SuperMind

The strategy selects stocks in the metaverse industry that recorded a limit-up within the prior 25 days and have turnover between 3% and 12%. It calls for screening before 10 a.m. and selecting stocks eligible to trade that day. The cited formula also…

EquitiesChina marketsTechnical indicatorsBreakout
SuperMind

The document outlines an equity screen combining turnover, circulating market capitalization, and a morning star candlestick pattern. Its stated criteria use a turnover range of 3% to 12%, a circulating share count cap of 5.5 billion shares in the headline,…

EquitiesTechnical indicatorsRisk management
BigQuant

This Chinese-language article describes a customizable stock-selection strategy built around five rules, mainly seeking shares that appear oversold and stable, with some rules intended to identify possible rallies. It distinguishes rule-based coding from an…

EquitiesMean reversionBacktestingFactor investing
SuperMind

The post describes an equity screen combining company profitability, market capitalization, and a measure of today’s increase in holdings. Its stated conditions include companies without losses and a buying-activity threshold above 5%. The title refers to…

EquitiesChina marketsStatistics
SuperMind

The document describes a Chinese A-share screening approach for Shenzhen main-board stocks. It selects shares with amplitude above 1, price-to-earnings ratios from 0 to 29.01, price-to-book ratios from 0 to 3.11, market capitalization below 10 billion yuan,…

EquitiesChina marketsFactor investingTechnical indicators
BigQuant

This A-share stock-selection approach combines an earnings-surprise proxy with the price response to earnings news. Instead of comparing reported profit with a numerical consensus estimate, it analyzes analyst research-report titles for wording that signals…

EquitiesChina marketsEvent-drivenMomentum
SuperMind

This strategy selects the ten lowest-priced eligible stocks within the SSE 50 universe, excluding special-treatment, suspended, and delisted stocks. It allows each holding to remain open for up to twenty days and sells a stock if its decline exceeds eight…

EquitiesChina marketsBacktestingRisk management
SuperMind

This A-share screening strategy combines daily price and trading activity conditions with a weekly trend signal. It selects stocks whose amplitude exceeds the stated threshold, whose prior-day turnover rate multiplied by the ratio of today’s opening-auction…

EquitiesChina marketsTechnical indicatorsMomentum