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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 proposed stock-selection approach ranks shares by a measure of capital activity and favors those whose closing price is above the five-day moving average, with the historical screen restricted to 2021. The article describes turnover and trading volume…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This stock screen selects companies classified in the metaverse theme, with circulating market value above 10 billion yuan and at least one limit-up day in the preceding 25 trading days. The stated rationale is that a recent sharp price rise may identify…

China marketsEquitiesMomentumBreakout
SuperMind

This proposed Chinese stock screen excludes Beijing-listed stocks and selects for an intraday range above 1%, alongside a condition combining price change with net trading volume attributed to very large orders. The stated threshold for that combined measure…

EquitiesChina marketsMarket microstructureTechnical indicators
SuperMind

This Chinese A-share screening proposal combines three conditions: an intraday range greater than one, return on equity above 15% in each of five consecutive years, and a stated daily maximum decline between 4% and 5%. The explanation interprets the range as…

EquitiesChina marketsFactor investingMean reversion
SuperMind

This note describes a daily A-share selection rule using price amplitude of at least 1, turnover between 2% and 9%, and a ranking by today’s auction amount, with the top five stocks selected. Its stated aim is to combine a measure of price movement with…

EquitiesChina marketsTechnical indicatorsExecution
SuperMind

This note proposes an A-share stock screen combining amplitude above 1, a nonempty outstanding convertible-bond name field, and an industry-related concentration condition. It describes ranking qualifying stocks by average daily trading value. The stated…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This note describes a short-term A-share screen combining price amplitude above 1, a rounded or arc-shaped price pattern, and first-level bid volume greater than ask volume. The stated rationale is that amplitude may indicate trading activity, the rounded…

EquitiesTechnical indicatorsMarket microstructureChina markets
SuperMind

This technical analysis note proposes measuring how closely two candlestick sequences resemble one another. It describes candles as summaries of open, high, low, and close prices over a chosen time period, then defines a similarity score as the average of…

EquitiesTechnical indicatorsStatisticsChina markets
SuperMind

This stock screen selects shares with a turnover ratio between 3% and 12%, a previous-day Dragon-Tiger List appearance, and previous-day trading value above 60 million yuan. The article presents these conditions as a way to find actively traded stocks that…

EquitiesChina marketsTechnical indicatorsRisk management
MQL5 code base

This document describes a chart indicator that marks a set of named candlestick formations: bullish and bearish hammers, bullish and bearish engulfing patterns, dark cloud cover, a bullish dark cloud variant, a bearish cloud gap, and a doji. The patterns are…

Technical indicatorsEquities
SuperMind

This post proposes screening stocks by daily price amplitude, relative trading volume, and the alignment of several moving averages. Its stated conditions are amplitude of at least 1%, a volume ratio between 1.5 and 6, and a requirement that the close remain…

EquitiesTechnical indicatorsMarket microstructureChina markets
SuperMind

This post outlines a Chinese stock-selection screen that pairs seven consecutive down days with a shrinking negative MACD histogram on a 15-minute chart and a reported increase in holdings above 5%. The setup looks for possible short-term rebounds after…

EquitiesTechnical indicatorsMean reversionMomentum
SuperMind

This Chinese-language post describes a short-term stock screen using three conditions: a shrinking MACD histogram on a 15-minute chart, a price below 12, and a reported increase in holdings above 5%. It interprets the inflow measure as possible buying…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This post proposes a short-term stock screen combining volatility, share float, and the opening price's proximity to a 10-day moving average. It selects stocks with amplitude above 1, a circulating share count no greater than 5.5 billion, and an opening…

EquitiesTechnical indicatorsVolatilityRisk management
SuperMind

This post describes a stock selection screen using four conditions: amplitude above 1, current trading volume above 10,000 lots, a higher opening price, and company size above 200 million. The rationale combines price movement and trading activity with a…

EquitiesTechnical indicatorsStatisticsRisk management
SuperMind

This post presents a Chinese equity screening rule based on price range, listing history, and a measure labeled the ratio of external to internal trading volume. It selects stocks with amplitude above 1, more than one year since listing, and an…

EquitiesTechnical indicatorsMarket microstructureRisk management
SuperMind

This Chinese-language post proposes a stock screen for companies classified in the metaverse theme. It ranks candidates by the day’s auction amount, keeps the top five, and requires the high–low range to exceed one percent of the previous close. The author…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

The document proposes a Chinese equity screen for the metaverse industry. It combines stocks ranked among the top five by current-day auction turnover with a prior-session condition described as the 9:15 matched price being at the daily limit down. It gives…

EquitiesChina marketsEvent-drivenBacktesting
SuperMind

This article describes an application of autoregressive models to financial time series, using CSI 300 prices and returns as the study data. It presents the topic as a walkthrough of the modeling process, covering fitting and forecasting with an AR model.…

EquitiesStatistics
SuperMind

This stock-screening approach ranks securities using trading activity reported in China’s Dragon-Tiger List, ordering names by buy and sell amounts to identify stocks attracting substantial market attention. The post presents a simple data-processing example…

EquitiesChina marketsSentimentMarket microstructure
SuperMind

This stock-selection idea builds a candidate pool from shares with a daily high-low range greater than one percent, at least one limit-up event in the prior 25 days, and a limit-up event within the past month. The post interprets range as a sign of…

EquitiesChina marketsVolatilityBreakout
SuperMind

This proposed China A-share screen combines three conditions: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and at least one limit-up event within the past month. The rationale is to focus…

EquitiesChina marketsMomentumBreakout
SuperMind

The document outlines a Chinese A-share screening rule that selects stocks with a daily high-low range of at least one percent, relative volume between 1.5 and 6 times its five-day average, and a nonempty outstanding convertible-bond name field. It…

EquitiesChina marketsTechnical indicatorsStatistics