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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

12,226 documents

SuperMind

This stock-selection idea builds a candidate pool from shares with a daily high-low range greater than one percent, at least one limit-up event in the prior 25 days, and a limit-up event within the past month. The post interprets range as a sign of…

EquitiesChina marketsVolatilityBreakout
SuperMind

This proposed China A-share screen combines three conditions: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and at least one limit-up event within the past month. The rationale is to focus…

EquitiesChina marketsMomentumBreakout
SuperMind

The document outlines a Chinese A-share screening rule that selects stocks with a daily high-low range of at least one percent, relative volume between 1.5 and 6 times its five-day average, and a nonempty outstanding convertible-bond name field. It…

EquitiesChina marketsTechnical indicatorsStatistics
SuperMind

This stock-selection rule screens for turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and no more than 100%, and a 9:25 price change below 6% in absolute value. The article combines a…

China marketsEquitiesFactor investingTechnical indicators
SuperMind

This Chinese equity screen combines a turnover range of 3% to 12%, at least one limit-up event in the prior 25 days, and a moving-average condition intended to identify upward divergence. The accompanying discussion frames these filters as proxies for…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The proposed stock screen looks for turnover between 3% and 12%, a circulating share count at or below 5.5 billion, and a daily maximum decline between 4% and 5%. The article frames the combination as a way to avoid very inactive stocks, limit exposure to…

EquitiesChina marketsMean reversionTechnical indicators
SuperMind

This stock selection idea combines three screens: membership in the metaverse industry, a positive institutional activity reading, and a 10-day return above zero but no higher than 35%. The rationale is to focus on a growth-oriented theme and stocks with…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This post describes a stock selection rule that combines daily turnover, a low KDJ K value, and prior-day opening-auction turnover. It treats the conditions as a buy signal: turnover must fall within a stated band, K must be below a threshold, and auction…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This document proposes screening stocks for price amplitude above a threshold, MACD above zero, and a positive change in the KDJ K value. It argues that amplitude can capture movement, MACD can indicate positive trend conditions, and rising K may reflect…

EquitiesTechnical indicatorsMomentumStatistics
SuperMind

This document describes a stock screen combining daily price amplitude, a dividend ratio for 2019, and a rising DEA value from MACD. Its rationale is that amplitude identifies more volatile shares, the dividend condition favors higher-yielding stocks, and…

EquitiesTechnical indicatorsVolatilityTrend following
SuperMind

This stock-selection screen looks for A-shares with daily amplitude above one percent, at least one limit-up event within the recent 21 trading days, and a 30-day average close above the 60-day average. The reference formula also filters for listed shares…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This stock screen selects shares with an intraday high-low range above 1%, a closing price exactly at 18.5 yuan, and volume between 1.5 and 6 times its five-day average. It sorts qualifying names by turnover. The stated rationale is to find stocks showing…

EquitiesTechnical indicatorsMomentum
SuperMind

This proposed stock screen combines a turnover rate between 3% and 12%, seven consecutive declining sessions, and a rising DEA line from MACD. The author frames the combination as a possible early signal of a trend reversal: recent weakness is paired with an…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This proposed A-share screening rule selects stocks before each trading day opens, requiring MACD to be above zero and the 2019 dividend amount relative to current price to exceed 25%. Candidates are ranked by stock popularity, which the article treats as a…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This post introduces an autoregressive model for financial time series, using CSI 300 prices and returns as the subjects of study. It says the material walks through fitting the model and attempting forecasts, presenting a modeling workflow focused on this…

EquitiesChina marketsStatisticsBacktesting
SuperMind

This Chinese stock-screening post combines trading activity, recent price weakness, and historical revenue growth. It selects stocks with turnover between 3% and 12%, seven consecutive declining sessions, and 2021 revenue more than 10% above 2018 revenue.…

EquitiesChina marketsMean reversionTechnical indicators
SuperMind

This note describes a Chinese A-share screen for metaverse stocks with prior-day turnover above 8% and a prior-day opening auction match price at the limit down. It also presents a simplified final rule based on metaverse classification, turnover, and a…

EquitiesChina marketsTechnical indicators
SuperMind

This Chinese equity screen selects stocks associated with the robotics concept, with turnover between 3% and 12%, circulating market value below 10 billion, and a stated scale threshold above 200 million. The post says the added scale filter is intended to…

EquitiesChina marketsFactor investingPortfolio construction
SuperMind

This post presents a Chinese stock-selection screen using daily amplitude, a measure described as current control above 21%, and a morning-star signal attributed to Kute Intelligent. Its discussion characterizes the setup as a short-term technical approach…

EquitiesTechnical indicatorsSentimentChina markets
SuperMind

This document describes a short-term Chinese stock screen combining daily price amplitude above 1%, a newly formed KDJ crossover, and classification in the metaverse concept. Its indicator example calculates K, D, and J from recent closing prices and selects…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

The document defines maximum drawdown as the largest decline from a historical net asset value peak to a subsequent trough within a selected period. It frames the measure as an estimate of the worst loss an investor might have experienced after buying a…

Risk managementStatisticsPortfolio construction
SuperMind

The document describes three equity strategies built around a bull-bear indicator: a direct timing rule for broad indexes, monthly indicator-change rotation among industries, and index allocation based on the share of constituent stocks signaling a long…

EquitiesChina marketsTrend followingMomentum