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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

22,592 documents

SuperMind

This A-share stock screen combines three filters: turnover between 3% and 12%, market capitalization below 10 billion yuan, and positive net income. It then looks for stocks whose closing price is at or above each of five moving averages, using 5-, 10-, 20-,…

EquitiesTechnical indicatorsTrend followingChina markets
SuperMind

This stock screening proposal combines a metaverse industry classification and a rounded-bottom chart pattern with a price condition based on Bollinger Bands. It seeks shares whose close is above the middle band and above the upper band, using a moving…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese-equity screening proposal combines an RSI below 65, an external-to-internal trading-volume ratio above 1.3, and a weekly price cross above the 30-week moving average. The intended mix is a momentum or trend condition alongside a measure of…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This note proposes screening Chinese stocks after the open using positive MACD, a circulating share count no greater than 5.5 billion, and a ranking by individual-stock popularity. Its indicator example calculates MACD from 12- and 26-period exponential…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This note describes a Chinese-equity screen for metaverse stocks. It ranks candidates by today’s opening-auction value, selects the top five, and requires yesterday’s auction turnover rate to exceed 0.26. The stated rationale is that auction activity and…

EquitiesChina marketsMomentumMarket microstructure
SuperMind

This Chinese equity screen selects stocks classified in the metaverse industry when the opening price is near the ten-day moving average and the KDJ indicator has just crossed upward. The document explains that the moving average supplies a price reference…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This document describes a Chinese equity screening rule combining a turnover range of 3% to 12%, three consecutive declining sessions, and afternoon net inflows from large orders. It presents the screen as a way to combine price action, trading activity, and…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This stock-selection rule combines a 14-period RSI below 65 with three consecutive declining sessions and a minimum listing age. The example implementation specifies more than 120 days since listing and evaluates the RSI and recent candle conditions to form…

EquitiesTechnical indicatorsMean reversion
SuperMind

This stock-selection proposal combines a technical filter with a profitability screen: choose main board stocks with RSI below 65, a daily gain above 1%, and return on equity above 15% in each of the previous five years. The author presents RSI as a way to…

EquitiesChina marketsTechnical indicatorsMomentum
ProRealCode

The Commodity Selection Index (CSI) is presented as a way to rank commodities by trend strength before applying a trend-following system. The document describes Wilder’s original calculation as combining ADXR, a 14-period average true range, and factors…

CommoditiesEquitiesTrend followingTechnical indicators
BigQuant

The document presents Follow-the-Leader, a factor-based method for constructing a smaller portfolio that tracks a broad equity index. Instead of selecting stocks only by index weight or correlation with index returns, the method estimates the number of…

EquitiesFactor investingPortfolio constructionBacktesting
SuperMind

The document describes a Chinese equity screen that combines daily price amplitude above 1%, a circulating share count no greater than 5.5 billion, and a day-over-day increase in volume above 5%. It explains the intended rationale: price movement may…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

The screen targets Chinese stocks with a daily amplitude above 1%, appearance on the prior day's 龙虎榜 (top trading list), and more than two limit-up days in the previous ten sessions. It combines recent price movement, reported trading attention, and repeated…

EquitiesChina marketsVolatilityMomentum
SuperMind

This stock-selection rule looks for companies associated with the metaverse concept, with a rising 30-day moving average and at least two limit-up events during the prior 500 days. It is intended to combine a rising price trend with a history of strong…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

The document describes a stock screen combining price amplitude, a market-concentration measure, and a 15-minute MACD histogram that is getting shorter. It interprets high amplitude as a way to find actively moving stocks, the concentration filter as a way…

EquitiesTechnical indicatorsMomentumRisk management
BigQuant

This research overview outlines a framework for constructing high-frequency equity factors from Level 2 market data. It recommends reducing tick or intraday observations into daily measures, then transforming those measures over time with operations such as…

EquitiesHigh-frequency tradingFactor investingStatistics
SuperMind

This Chinese-language post describes an equity screening rule that combines a daily high-low range threshold, five consecutive years of return on equity above 15%, and a KDJ indicator condition below 20. The intended combination is a technical filter…

China marketsEquitiesTechnical indicatorsFactor investing
SuperMind

This stock selection example combines three filters: turnover between three and twelve percent, outside volume greater than 1.3 times inside volume, and a positive institutional direction measure. The article frames turnover as a liquidity or activity…

China marketsEquitiesMarket microstructureStatistics
SuperMind

This Chinese stock screen selects listed shares with turnover rates between three and twelve percent, excludes Beijing-listed stocks, and keeps stock codes beginning with 60. The article describes these filters as a way to focus on relatively active shares…

China marketsEquitiesExecution
SuperMind

This stock selection example combines a daily price range filter with a calendar-year condition and a rising Commodity Channel Index (CCI) pattern. It first looks for a high-to-low range exceeding one percent of the previous close, restricts observations to…

China marketsEquitiesTechnical indicatorsVolatility
SuperMind

This document describes a stock screen intended to find possible trend changes. It looks for equities whose moving averages converge, using at least five averages as the selection condition, and also imposes a limit on the indicated pre-open gain. The…

EquitiesChina marketsTechnical indicatorsMean reversion