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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

SuperMind

This stock selection approach combines three filters: a price-range threshold, a bullish crossover of the five-week and ten-week moving averages, and a minimum time since listing. The post explains the crossover and trading-range conditions as technical…

EquitiesTechnical indicatorsBacktestingMachine learning
ProRealCode

This ProRealTime indicator is designed for price-action charting with few overlays. It calculates Fibonacci retracement levels from the current session's high and low, changes their orientation according to whether price is behaving bullishly or bearishly,…

Technical indicatorsEquitiesFutures
SuperMind

This post describes a short-term screen for main-board Chinese stocks. It selects shares with an intraday high-low range above a threshold, a high large-order net-flow ranking, and a daily gain above a threshold, then ranks candidates by market…

EquitiesMomentumTechnical indicatorsChina markets
SuperMind

This Chinese stock-screening proposal selects shares with a daily high-low range greater than 1 that had three consecutive limit-up sessions as of the previous day, while excluding the STAR Market. The article interprets the range as a sign of volatility and…

EquitiesChina marketsMomentum
SuperMind

This stock-screening recipe combines a daily high-low range greater than 1, prior-day actual turnover between 3% and 28%, and a MACD reading below zero from two days earlier. The article frames the lagged MACD condition as a way to identify stocks that may…

EquitiesChina marketsTechnical indicators
SuperMind

This Chinese stock-screening example combines three filters: the 20-day moving average must exceed the 120-day average, the 14-period RSI must be below 65, and candidates are ordered by a measure of stock popularity or trading heat. The stated rationale is…

EquitiesChina marketsTechnical indicators
SuperMind

The document outlines a stock screen combining a daily high-low range threshold, return on equity above a stated level for five consecutive years, and a selected company characteristic. It presents the range as a way to identify stocks with price movement…

EquitiesFactor investingTechnical indicatorsBacktesting
SuperMind

The document describes a Chinese equity screening rule that places stocks in a candidate pool when their high-to-low price range exceeds 1%, the trading year is 2021, and company scale is at least 200 million. It gives example implementations in a charting…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This stock selection approach combines three filters: a 14-period RSI below 65, best bid volume greater than best ask volume, and at least two limit-up sessions in a 500-day lookback. The article frames these conditions as a way to find shares with prior…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

The post proposes screening Shanghai-listed A-shares using an RSI below 65 and an external-to-internal trading volume ratio above 1.3. Its example also filters out stocks whose current price change is at or below negative 3 percent. The stated rationale is…

China marketsEquitiesMean reversionTechnical indicators
BigQuant

This guide describes participation in a Chinese A-share quantitative challenge with factor discovery and end-to-end modeling tracks. Both target future 30-minute VWAP returns using minute bars and order book snapshots. For the factor track, submissions…

China marketsEquitiesFactor investingBacktesting
SuperMind

This Chinese stock-screening note describes a momentum-oriented rule for the metaverse industry: select stocks that had a limit-up event within the prior 25 days and whose high is at a two-day high. It says to run the screen before 10 a.m. and trade the…

China marketsEquitiesMomentumBreakout
SuperMind

This A-share screening proposal places stocks in a candidate pool when they meet three technical conditions: daily amplitude above a stated threshold, a newly formed KDJ crossover, and at least five coincident moving averages. The post explains these filters…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese A-share screening proposal combines daily price range, weekly MACD, a non-ST restriction, and a five-pen limit-up pattern. It describes selecting stocks before 10 a.m. and gives formula and Python examples intended to express the conditions. The…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This study note explains how to build a directed stock network from news coverage: a stock named in a headline is treated as a lead, while stocks mentioned in the article body are followers. Edge weights count their co-occurrences over a rolling window. The…

EquitiesSentimentStatisticsFactor investing
SuperMind

This Chinese stock-selection proposal combines three filters: RSI below 65, a positive relationship between percentage price change and net buying by very large orders, and a weekly close crossing above its 30-week moving average. The intended effect is to…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese equity screen first filters for robot-related stocks with circulating market capitalization below 10 billion yuan and turnover between 3% and 12%. It then applies a 15-minute MACD condition intended to identify a shortening negative histogram,…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese stock-screening idea combines a metaverse-sector filter with a long-term price trend condition and a MACD signal. It selects metaverse stocks whose price is above the 250-day moving average and whose DEA is rising. The document presents the…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese-language post presents a stock screen limited to the metaverse sector. It requires the closing price to be above its five-day moving average and applies two prior-day comparisons among the five-, ten-, and twenty-day averages. The post describes…

EquitiesTechnical indicatorsMomentum
SuperMind

This Chinese-language post describes a stock selection screen combining a 14-period RSI below 65, three consecutive down candles, and an arc-shaped price pattern. It frames the candle sequence and RSI filter as signals of short-term weakness, while…

EquitiesTechnical indicatorsBacktesting
SuperMind

This Chinese-market stock selection approach combines several daily filters: RSI below 65, a gain above 1%, and a positive day-over-day change in the KDJ indicator’s K value. It further focuses on main-board listings and describes controls involving…

China marketsEquitiesTechnical indicatorsMomentum
MQL5 code base

This screener searches symbols or selected asset categories for instruments whose current prices have fallen below recent closing-price peaks. Users can set a lookback period, with a 90-day default, and a drawdown threshold. The intended use is to surface…

Technical indicatorsMean reversionEquitiesForex
SuperMind

This note describes an equity screen that combines a 3%–12% turnover range, an engulfing-style reversal condition, and a rising DEA value from the MACD indicator. Its stated selection logic ranks qualifying stocks by market capitalization. The article also…

EquitiesTechnical indicatorsMomentumChina markets