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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

ProRealCode

This indicator uses a modified weighted moving average and a smoothed version of that average to locate candidate turning points. When the two lines cross, it records a recent local low or high, using a shorter lookback based on a fraction of the…

Technical indicatorsEquitiesFuturesForex
SuperMind

The document presents a Chinese equities screening idea: select stocks with turnover between 3% and 12%, a positive return over the prior 10 days below 35%, and an opening price near the 10-day moving average. Its example code adds further filters, including…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

The request specifies a stock factor backtest using a named factor table and factor. Factor values should be converted to ranks, with smaller values preferred. The intended universe is the CSI 1000, excluding Beijing Stock Exchange listings and ST-designated…

EquitiesFactor investingBacktestingPortfolio construction
ProRealCode

The strategy seeks long trades during a rebound after a bearish move. It uses a Donchian channel to divide the recent price range into four sections, then places a buy stop near the first level above the channel low when price remains below that level. A…

EquitiesMean reversionTechnical indicatorsPosition sizing
BigQuant

This article outlines a workflow for creating custom equity-selection rules from platform factors. It illustrates price-location features based on recent highs and lows, then combines return, volume, and market-relative conditions into a screening rule. The…

EquitiesFactor investingMomentumBacktesting
SuperMind

This Chinese-language post proposes a stock screen combining price movement and liquidity conditions: an amplitude threshold, at least one large daily gain within the past 25 trading days, and turnover between 3% and 12%. It frames the screen as potentially…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The proposed stock screen selects shares with a daily high-low range of at least one percent and relative volume between 1.5 and 6 times its five-day average. It also filters on company or industry classification, with consumer and healthcare sectors offered…

EquitiesTechnical indicatorsChina markets
SuperMind

This document describes a Chinese equities screening rule using three conditions: daily high-to-low amplitude above one percent of the open, a positive but less than 35% gain over ten days, and three consecutive sessions in which the close is below the open.…

EquitiesChina marketsMean reversionTechnical indicators
FMZ forum

This essay presents a framework for improving investment judgment through varied mental models rather than relying on one familiar way of thinking. It recommends learning core ideas from several disciplines, using an investor-specific checklist, and applying…

Risk managementStatisticsEquities
BigQuant

This research summary studies Chinese home appliance industry conditions using revenue and net profit growth as proxies, arguing that calculations on comparable constituents reduce distortions caused by changes in the historical stock universe. It frames…

EquitiesChina marketsStatisticsBacktesting
SuperMind

This stock selection proposal combines daily price amplitude, a measure of controlling-shareholder activity, and net buying by major participants during the opening auction. Its expanded version also requires the share price to be above its 30-day moving…

EquitiesChina marketsTechnical indicatorsMomentum
ProRealCode

SVAPO combines smoothed price movement and volume to gauge short-term directional pressure. The method derives a Heikin-Ashi-style price series, smooths it, and compares it with a volume trend. Volume is capped relative to a recent average before being…

Technical indicatorsMomentumStatisticsEquities
ProRealCode

This stock strategy uses changes in a modified Directional Index to switch between long and short bias. A local turn in the indicator sets the desired direction; entry is then permitted only when the close is on the corresponding side of a moving average,…

EquitiesTechnical indicatorsTrend followingRisk management
SuperMind

This Chinese equity-screening idea selects stocks with amplitude above 1, a rounded price pattern, a robotics-sector classification, and circulating market value below 10 billion. The text interprets the amplitude condition as targeting active shares, the…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

The document describes a Chinese equity screen combining an amplitude threshold above 1, a MACD condition above the zero axis, and a short-term MACD histogram change. Its analysis emphasizes volatility alongside a bullish momentum backdrop, with the…

EquitiesTechnical indicatorsMomentum
SuperMind

This A-share screening concept combines a daily price-range threshold, circulating market capitalization above 10 billion yuan, and simultaneous upward threshold crossings in RSI, ROC, and CCI. The examples define the crossings as RSI moving above 30, ROC…

EquitiesChina marketsTechnical indicators
SuperMind

This A-share screening rule selects stocks with turnover between 3% and 12%, an IPO year condition, and a ratio of outside-market to inside-market trading above 1.3. The article describes the listing-year condition as 2021, while its Python example appears…

EquitiesChina marketsMarket microstructure
SuperMind

This Chinese A-share stock screen combines a daily range condition, a specified closing price, and a check that the previous session was not a limit-up day. The article’s prose describes the closing-price threshold as 18.5 yuan and the range as greater than…

EquitiesChina marketsTechnical indicators
SuperMind

This note describes a short-term screen for metaverse-themed Chinese stocks that appeared on the prior day’s Dragon-Tiger list and whose daily price change multiplied by the net volume of very large orders is positive. The intended signal combines a public…

China marketsEquitiesMarket microstructureSentiment
SuperMind

This note proposes screening metaverse-themed Chinese stocks for a curved price pattern and more than two limit-up sessions within a 10-day window. It frames repeated limit-ups as a sign of strong recent price action and includes example formulas for…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This note describes a Chinese A-share screening rule for stocks classified in the metaverse theme. It selects stocks with turnover above 8% on the prior day and a 14-period RSI below 65, aiming to find actively traded shares that are not extremely…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This note outlines a Chinese equity screen that selects stocks with turnover between 3% and 12%, excludes Beijing-listed shares, and requires a measure described as today’s control concentration to exceed 21%. It argues that concentrated ownership may be…

China marketsEquitiesRisk managementStatistics
SuperMind

This note describes a Chinese equity screen using three conditions: amplitude above 1, a KDJ value below 20, and at least one daily gain of 10% or more during the previous 25 trading days. It sketches implementations in a charting formula and Python, using…

China marketsEquitiesTechnical indicatorsMomentum