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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 note describes a stock screen combining metaverse sector membership, a rounded price pattern, and a share price below 12 yuan. It suggests these filters as a way to identify lower-priced stocks in an emerging industry, and mentions RSI, MACD, and moving…

EquitiesTechnical indicatorsChina markets
SuperMind

This Chinese community post outlines an equity screen combining three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and an appearance on the prior day’s public trading activity…

EquitiesChina marketsSentimentExecution
SuperMind

This Chinese community post describes a daily stock screen requiring an amplitude reading above 1, a daily percentage change between -5% and -4%, and no limit-up session on the previous day. It presents the conditions as a way to identify volatile stocks…

EquitiesVolatilityTechnical indicatorsRisk management
SuperMind

This note outlines a stock screen for beverage and alcohol related companies. It combines turnover between 3% and 12% with an industry classification and measures of buying by large or extra-large orders during the opening auction. The stated rule uses an…

EquitiesChina marketsMarket microstructureRisk management
SuperMind

This note describes a Chinese equity screen combining turnover, order book depth, and institutional trading. It selects stocks with turnover between 3% and 12%, displayed best bid volume above best ask volume, and a positive institutional trading measure. A…

EquitiesMarket microstructureChina marketsRisk management
SuperMind

This brief installment in a multi-factor modeling series contrasts two ways of estimating factor information. It says that Barra-style models typically take factor exposures directly from fundamental or technical data, while academic approaches often…

Factor investingStatistics
SuperMind

This post outlines a Chinese equity screen using three activity and size filters: daily turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and prior-day opening-auction turnover above 0.26. It gives a technical…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This Chinese-language post describes an equity screen for metaverse-related stocks. It combines an upward-sloping 30-day moving average with a measure intended to compare aggressive buying volume (外盘) against selling volume (内盘), using a stated threshold of…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese-language post describes an equity screen using three conditions: RSI below 65, turnover between 3% and 12%, and at least two limit-up price moves during the prior 500 days. It presents the screen as a way to find stocks with recent strong moves…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This stock-selection idea combines daily amplitude above 1, positive large-order net volume for at least three consecutive days, and a nonempty outstanding convertible-bond name. The post treats the bond condition as a way to identify companies that have…

EquitiesMarket microstructureStatisticsChina markets
SuperMind

This short-term stock screen selects shares with daily amplitude above 1, evidence of prior-day large-player control, and a closing price between the 20-period Bollinger middle and upper bands. The post explains that Bollinger Bands use a moving average and…

EquitiesTechnical indicatorsVolatilityChina markets
SuperMind

This stock screen combines a metaverse theme filter with RSI below 65 and a 15-minute MACD condition intended to identify a shrinking negative histogram. The post describes it as a way to find short-term trading opportunities in volatile stocks. Its formula…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This example describes a short-term screen for Chinese stocks assigned to the metaverse theme. It filters for a volume ratio above 1.5 and below 6, a three-day limit-up sequence as of the prior day, and, in its final stated logic, market value below 500…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock-screening example combines a turnover filter, a reversal-style candle condition, and simultaneous moving-average crossover signals. Its stated selection logic requires turnover between 3% and 12%, a reversal pattern, and upward crossings among the…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This post outlines an A-share screen for stocks with amplitude above 1, excluding ST-designated shares, selected before 10 a.m., priced below 12, and matching a named five-step limit-up approach. The sample Python implementation operationalizes the last…

EquitiesChina marketsBreakoutTechnical indicators
SuperMind

This post describes an A-share screen combining an intraday amplitude above 1%, a positive ten-day return below 35%, and an auction gain between -2% and 5%. It frames the amplitude as a measure of movement, the return band as a way to avoid both declining…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This Chinese stock-screening post proposes selecting A-shares with at least five converging moving averages, a limit-up day within the prior 25 days, and a 9:25 auction gain below 6%. It presents the combination as a way to find stocks with aligned trends…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This short-term stock screen selects shares when MACD is above zero, short-term moving averages are rising or spreading upward, and the latest price change lies between -5% and 2.6%. The article describes the conditions as a way to combine price trend…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This tutorial offers practical advice for getting more useful answers from the SuperMind assistant when asking trading and coding questions. It recommends stating the task clearly, providing relevant data formats and context, using precise terminology, and…

EquitiesTechnical indicatorsMachine learning
SuperMind

This stock-selection method combines price range, weekly MACD, and a moving-average crossover. It first looks for stocks with an amplitude above 1, a positive weekly MACD histogram, and a weekly close crossing above its 30-week moving average. The article…

EquitiesTechnical indicatorsMomentumBreakout
SuperMind

This stock selection post describes a technical screen for main board shares. It combines an RSI reading below 65, seven consecutive sessions in which the close is below the open, and a current session gain greater than 1%. The proposed interpretation is…

EquitiesTechnical indicatorsMean reversionChina markets
SuperMind

This brief description introduces an indicator implementing a trading approach based on Woodies CCI. The stated method is to focus on patterns formed by the Commodity Channel Index in the traded market. It says the approach does not rely on the appearance of…

Technical indicatorsFutures
SuperMind

The document describes a simple Chinese equity screening rule. It selects stocks with a daily high-low range of at least one percent, turnover above two percent but below nine percent, and prior-day trading value above sixty million. The stated rationale is…

China marketsEquitiesTechnical indicatorsExecution
SuperMind

This stock-selection proposal combines a turnover-rate range of 3% to 12%, a 2021 listing year, and a weekly bullish-bar condition. The article explains the weekly condition using K and D readings above 50, a rising K value, and a positive MACD histogram…

China marketsEquitiesTechnical indicatorsMomentum