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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

4,510 documents

SuperMind

The proposed A-share screen selects stocks classified in the metaverse industry with circulating share capital no greater than 5.5 billion shares, then ranks candidates by the product of percentage price change and net volume from exceptionally large orders.…

China marketsEquitiesMomentumSentiment
Cryptohopper blog

This overview describes meme coins as cryptocurrencies whose popularity often depends on humor, online communities, and attention rather than a distinct practical use. It gives examples including Dogecoin, Shiba Inu, Pepe, and Bonk, and notes that tokens may…

CryptoVolatilitySentimentRisk management
SuperMind

This document describes a short-term Chinese A-share screening rule combining a 14-period RSI below 65, year-over-year growth in parent-company net profit above 20% and up to 100%, and a positive signal formed from price change and large-order net inflow.…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This weekly market report organizes several indicators of Chinese equity liquidity by sector: ETF subscriptions and redemptions, northbound investor flows, estimated allocations from pending and newly raised equity funds, company buybacks, and…

EquitiesChina marketsStatisticsSentiment
SuperMind

The document outlines a Chinese equity screening idea combining three conditions: a market capitalization below 10 billion yuan, no reported losses, and a daily increase in holdings above 5%, alongside large net buying in the afternoon. It interprets the…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This Chinese stock-screening post combines three conditions: RSI below 65, external-market volume divided by internal-market volume above 1.3, and appearance on the previous day’s broker leaderboard. It describes the screen as a way to identify shares with…

EquitiesTechnical indicatorsChina marketsSentiment
SuperMind

This stock-selection screen combines price movement, trading-flow, and prior-day price conditions. It selects shares with amplitude above 1, large-order net volume above 0.05 for at least three consecutive days, and a close above the previous day’s low. The…

EquitiesTechnical indicatorsMarket microstructureSentiment
SuperMind

This Chinese stock-selection post combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and an upward-sloping 30-week moving average. It frames the screen as a way to…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock-selection screen combines yesterday’s exchange leaderboard data, a ranking by reported capital flow intensity, and a limit on the current session’s opening gain. It first identifies stocks appearing on the prior day’s trading leaderboard, orders…

China marketsEquitiesMomentumSentiment
SuperMind

The document proposes a Chinese A-share screening rule for companies classified in the metaverse industry. It looks for stocks listed on the prior day’s Dragon-Tiger list and with a closing price lower on each of the preceding seven sessions. The rationale…

EquitiesChina marketsMean reversionTechnical indicators
SuperMind

The document describes an A-share stock screen combining a 14-period RSI below 65, an estimated outer-to-inner trading volume ratio above 1.3, daily amplitude above 1%, and trailing price-to-earnings below 30. It explains the intended rationale: use RSI and…

EquitiesTechnical indicatorsSentimentRisk management
SuperMind

This stock screen combines three conditions: association with the metaverse theme, positive net buying by major participants during the opening auction, and revenue in 2021 more than 1.1 times its 2018 level. The post presents the combination as a way to…

EquitiesChina marketsSentimentEvent-driven
SuperMind

This A-share selection rule first screens for turnover between 3% and 12%, market capitalization below 10 billion yuan, and companies described as having no losses. It then ranks qualifying shares by the day’s auction amount and proposes investing in the top…

EquitiesChina marketsExecutionSentiment
Amberdata research

The article explains how Bitcoin ETF inflows and outflows may relate to market liquidity, price pressure, and investor sentiment. Inflows can add buying demand and are often read as bullish, while outflows can reduce liquidity and accompany profit-taking or…

CryptoSentimentOn-chain dataRisk management
SuperMind

This Chinese equity-screening proposal selects stocks with a positive but limited 10-day return, a signal described as major-player control on the previous day, and today’s increase in holdings above 5%. The article interprets the return range as evidence of…

EquitiesMomentumSentimentRisk management
SuperMind

This stock screen combines three conditions: price amplitude above a threshold, positive institutional-flow activity, and a K value below a threshold from the KDJ indicator. The accompanying examples calculate amplitude from the high, low, and open, sum…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This stock-selection approach ranks shares using two measures: net capital flow and net large-order flow. Each measure is calculated over a period by taking net inflows less outflows and dividing by free-float market capitalization. Higher values are…

EquitiesChina marketsSentimentFactor investing
BigQuant

This July 2020 market note attributes the bull market to falling risk-free rates and increased allocations to equities. It argues that a more diverse investor base may reduce the chance of a sudden collapse, while rising participation and short-term…

China marketsEquitiesFactor investingVolatility
Amberdata research

The document explains six Bitcoin indicators used to interpret investor sentiment and supply behavior: realized price, net unrealized profit/loss (NUPL), coins held or presumed lost, monthly long-term-holder position change, liquid versus illiquid supply,…

CryptoOn-chain dataSentimentRisk management
SuperMind

This Chinese stock-screening strategy selects shares with turnover between 3% and 12%, a positive product of price change and large-order net buying, and at least one limit-up event in the recent month. The article presents these filters as a combination of…

EquitiesChina marketsMomentumSentiment
SuperMind

This proposed Chinese equity screen selects stocks associated with the metaverse theme, filters for positive net buying attributed to large traders during the opening auction, and restricts the universe to codes beginning with 60, generally Shanghai-listed…

EquitiesChina marketsMarket microstructureSentiment
SuperMind

The proposed Chinese equity screen combines three conditions: price amplitude above 1, institutional participation above 30% over the prior 15 days, and an auction-period price change between -2% and 5%. The post describes amplitude and institutional…

EquitiesChina marketsTechnical indicatorsSentiment