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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 Chinese-language post proposes screening metaverse-related stocks using the previous day's actual turnover rate, with a stated range above 3% and below 28%, and a 14-period RSI below 65. The stated rationale is to focus on stocks with some trading…

China marketsEquitiesTechnical indicatorsStatistics
BigQuant

The report develops stock selection factors from abnormal operating cash flow as proxies for real earnings management. Its premise is that firms can alter real business activity to make reported performance look stronger, potentially harming future…

China marketsEquitiesFactor investingBacktesting
SuperMind

This Chinese-language post proposes a stock screen combining at least five clustered moving averages, a close above the Bollinger middle band but below its upper band, and a dividend measure above a stated threshold for 2019. It describes the combination as…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This document describes a China A-share screening idea that selects stocks associated with the metaverse theme, requires the close to be above a five-day moving average, filters for a daily gain greater than 1%, and restricts candidates to main-board…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This post outlines a Chinese equity screen that requires daily amplitude above 1, turnover between 2% and 9%, and a rising KDJ K value. It presents these as technical filters intended to identify stocks showing activity and possible short-term strength. The…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This document describes a short-term Chinese equity screen combining daily amplitude above 1, a 9:25 price gain below 6%, and a stock price or average price above its five-day moving average. The intended rationale is to find stocks with some price movement…

EquitiesChina marketsTechnical indicatorsTrend following
BigQuant

This trading exercise translates a discretionary method into explicit stock-selection rules. A candidate must close above its five-day moving average for three consecutive days and remain within ten percent above its lowest price over the previous twenty…

EquitiesTechnical indicatorsMomentumRisk management
BigQuant

The report develops stock-selection factors from one-minute Chinese equity data, adding transaction counts to price and volume inputs. It examines average trade value and the direction of large-trade activity, then evaluates these signals both alone and…

EquitiesChina marketsFactor investingHigh-frequency trading
SuperMind

This note compares portfolio construction approaches, including equal weighting, market-cap weighting, and stratified sampling, with optimization methods such as mean-variance optimization, risk parity, target-risk, ABL, and tracking-error models. It…

EquitiesChina marketsPortfolio constructionRisk management
SuperMind

This proposed Chinese equity screen combines three conditions: daily price range above 1%, positive afternoon large-order net inflow, and growth in beverage and alcohol imports and exports. The note interprets the range and order-flow measures as signs of…

EquitiesChina marketsMarket microstructureTechnical indicators
SuperMind

This note describes a simple Chinese equity screen combining daily price range, a recent high, and share supply. It selects stocks whose high is the highest of the current and prior day, whose daily range exceeds 1%, and whose tradable share count is no more…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This stock screen combines three conditions: daily amplitude above a stated threshold, no limit-up close on the previous day, and at least one limit-up event during the past month. The article frames larger amplitude as a way to find more active stocks,…

EquitiesChina marketsMomentumVolatility
SuperMind

This Chinese equity screen combines three filters: at least five moving averages should converge, the price-to-earnings ratio must be positive, and the dividend payout ratio for 2019 must exceed 25%. The document interprets moving average convergence as a…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This proposed Chinese equity screen combines a relative strength index below 65 with price change and net activity from very large orders, plus a revenue growth test: 2021 revenue divided by 2018 revenue must exceed 1.1. The narrative presents these filters…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This platform guide distinguishes raw financial statement records from processed point-in-time (PIT) data and explains why the distinction matters in quantitative investing. Raw records are organized by instrument, report date, publication date, and change…

EquitiesChina marketsBacktestingStatistics
SuperMind

This document presents a Chinese equity screening rule that selects stocks whose codes begin with 60, whose turnover rate is between 3% and 12%, and whose short and long moving averages show alignment. The initial description calls for at least five…

EquitiesChina marketsTechnical indicatorsRisk management
FMZ forum

The document explains a high-frequency tactic called penny jumping through a limit-order-book example. A large visible bid may signal that an institutional buyer is willing to trade at a particular price. A faster trader can step one tick ahead of that bid,…

EquitiesHigh-frequency tradingMarket microstructureExecution
BigQuant

This monthly review compares equity factors using information coefficients (IC) and long-short returns. It reports that growth and turnover factors were relatively consistent over the preceding three months, while profitability and reversal results varied;…

EquitiesFactor investingStatisticsBacktesting
SuperMind

This Chinese equity screening proposal selects stocks in the metaverse theme, applies a circulating market capitalization threshold, and requires a positive institutional-holdings measure. The article explains institutional ownership as a possible signal of…

EquitiesChina marketsFactor investingRisk management
SuperMind

This Chinese stock screening proposal combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the auction, and a listing date in 2021. It frames the screen as a way to focus on newer companies in…

EquitiesChina marketsSentimentEvent-driven
SuperMind

This stock selection rule combines an RSI reading below 65, a daily gain greater than 1%, main-board listing status, and an intraday low between 4% and 5% below the reference level. The stated rationale is to find shares with possible rebound potential,…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese stock screen combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and exclusion of stocks that hit the daily limit the previous day. The rationale is to seek…

China marketsEquitiesMomentumEvent-driven
SuperMind

This Chinese equity screen combines an amplitude threshold with two MACD-based conditions: a positive weekly histogram, described as a red bar, and a positive daily MACD reading. The article frames the amplitude filter as a way to retain stocks with price…

EquitiesTechnical indicatorsMomentum
SuperMind

This Chinese stock screen combines three filters: daily amplitude above one, more than a year since listing, and a closing price above its five-day moving average. The article presents the moving-average condition as a way to identify a short-term upward…

EquitiesTechnical indicatorsMomentum