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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
Quantpedia
86 documents
TqSdk
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
Quantopian lectures
45 documents
Binance API docs
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 stock screen combines an RSI reading below 65, three consecutive sessions in which the close is below the open, and a KDJ K-line reading below 20. It is intended to identify shares with recent technical weakness, with the low KDJ value treated as a…

EquitiesTechnical indicatorsMean reversionChina markets
SuperMind

This stock selection idea combines three filters: daily amplitude above 1%, a dividend yield above 25% associated with 2019, and a ranking intended to favor stronger capital flows. The explanation treats amplitude as a way to find more volatile shares, the…

EquitiesTechnical indicatorsFactor investingChina markets
SuperMind

This post describes a stock-selection rule that combines membership in the metaverse theme with a prior-day close at or above the 250-day moving average and a condition labeled as a rising arc. It frames the theme membership as exposure to a popular sector,…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese-language post proposes a stock screen combining a relative strength index below 65, seven consecutive sessions in which the close is no higher than the open, and valuation bounds. It targets Shenzhen main-board stocks with price-to-earnings…

EquitiesChina marketsTechnical indicatorsFactor investing
MQL5 code base

This brief indicator description explains a custom MACD tool that plots only the MACD signal line in a separate pane and marks detected divergences both there and on the price chart. It distinguishes the indicator from a standard MACD display, which…

Technical indicatorsMomentumEquities
SuperMind

This post describes a stock screen using three conditions: a daily high-low range exceeding one percent of the previous close, a trading date in 2021, and a smoothed stochastic-style K value below 20. It supplies formula and Python examples for calculating…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This Chinese-language post proposes a short-term A-share screening rule that combines membership in the metaverse industry, a rounded-base shape, and a bullish morning-star reversal signal. It gives a formula based on the prior and current sessions’ open and…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

The post proposes a Chinese A-share stock screen using three conditions: RSI below 65, seven consecutive sessions in which the close is no higher than the open, and a holder-concentration measure between 20% and 70%. It also provides example code intended to…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This Chinese A-share stock screen ranks stocks by volume ratio and selects the top 100, then filters for a positive price-to-earnings ratio and an IPO year of 2021. The post interprets high volume ratio as possible inflow strength and positive P/E as a basic…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This note outlines a stock screen combining MACD above zero, an upward price trend, and a volume ratio between 1.5 and 6. It describes the volume ratio as current volume relative to an average over recent sessions and includes formula and Python examples. A…

EquitiesMomentumTechnical indicatorsChina markets
SuperMind

This note describes a daily stock screen that selects A-shares in 2021 when the intraday high-low range exceeds 1% and the daily return is between -5% and 2.6%. It gives example implementations using a market formula and Python data processing, although the…

EquitiesVolatilityTechnical indicatorsChina markets
BigQuant

This forum exchange describes a fix for a BigQuant data query that failed with a missing date key while combining two data sources. The suggested query explicitly selects the date and instrument fields along with technical factor fields. It also filters…

EquitiesTechnical indicatorsBacktesting
BigQuant

This research summary forecasts constituent changes for China’s CSI 300 and CSI 500 indices ahead of their scheduled December 2018 reviews. It explains that the indices are reviewed in June and December, and that changes can create trading opportunities when…

EquitiesChina marketsEvent-drivenPortfolio construction
SuperMind

This post describes a Chinese A-share screening rule using three conditions: the day’s increase in buying-position share must exceed five percent, the opening auction price change must be between minus two and five percent, and the ten-day return must be…

EquitiesMomentumChina markets
BigQuant

This brief platform discussion explains how users can call MACD in BigQuant 3.0 after an older expression format stopped working. It gives two supported expression forms: a windowed MACD function and a shorthand helper. Both calculate MACD from closing…

Technical indicatorsEquities
BigQuant

A user reports a discrepancy between a trade’s recorded execution price and the stock’s historical prices on the same date after adjustment for corporate actions. The example contrasts a reported buy price with lower adjusted open and close values. The…

EquitiesBacktestingStatistics
SuperMind

This A-share screening example looks for stocks with MACD above zero and an upward-moving-average condition, using a historical period associated with 2021. The article presents MACD as a momentum or trend filter and rising averages as a sign of upward…

EquitiesMomentumTechnical indicatorsChina markets
MQL5 code base

This brief indicator description explains a visual aid for chart reading: bullish and bearish candles are plotted in different colors so that their direction is easier to distinguish when a chart’s default colors are alike or confusing. Its purpose is…

EquitiesTechnical indicators
SuperMind

This stock screen combines an intraday range threshold with a year filter and a ranking by auction amount, selecting the five highest-ranked stocks. The accompanying explanation treats a larger range as a sign of greater volatility and auction amount as a…

EquitiesVolatilityChina markets
SuperMind

The document outlines a Chinese A-share stock screen combining daily price range, relative trading volume, and a measure described as today’s control or large-order share. Its stated selection conditions require a range of at least one percent, relative…

EquitiesTechnical indicatorsChina markets
BigQuant

This excerpt summarizes a Chinese weekly research note on machine learning and commodity trading advisor strategies. It reports recent results for a neural network strategy on the CSI 500, a commodity futures strategy, and a commodity strategy combining…

Machine learningFuturesEquitiesCommodities
SuperMind

The document proposes a stock screen combining membership in the metaverse industry, a rounded-base chart pattern, and a favorable company-quality classification. It argues that company characteristics may relate to prospects, management, and profitability,…

EquitiesTechnical indicatorsRisk management
SuperMind

This Chinese equity screening proposal selects stocks associated with the robotics concept, with daily price amplitude above 1%, circulating market capitalization below 10 billion, and a rule excluding a board category identified in the post as the STAR…

China marketsEquitiesTechnical indicatorsRisk management