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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

This document outlines a stock-selection rule that excludes Beijing-listed shares, requires price amplitude above 1%, and selects stocks with positive institutional-flow readings. It identifies the flow measure as DDX and describes a positive value as…

EquitiesChina marketsSentimentTechnical indicators
BigQuant

This research note outlines a stock-selection strategy for constituents of the CSI 500 index. It uses the number of news items about each stock as a proxy for investor attention, drawing on news-volume data collected by web crawler from 2010 onward. Stocks…

EquitiesSentimentChina marketsBacktesting
SuperMind

This overview groups quantitative market indicators into four families: breadth, elasticity, depth, and concentration. Breadth measures participation across securities using trading volume, new-high versus new-low counts, and advancing versus declining…

EquitiesTechnical indicatorsMarket microstructureStatistics
SuperMind

This study turns Chinese analyst-report summaries into equity signals using a fine-tuned BERT sentiment model. It starts with a pretrained Chinese model, adapts it on labeled financial opinion text, and applies it to unlabeled report summaries.…

EquitiesMachine learningSentimentFactor investing
BigQuant

The article describes several ways quantitative trading may shape Chinese A-share activity. It presents broad index direction as a dominant signal, with overnight futures and macro news used to anticipate the market and influence broad buying or selling. It…

China marketsEquitiesSentimentMomentum
SuperMind

This post outlines a Chinese equity screen requiring RSI below 65, seven consecutive down sessions, and a prior-day 9:15 auction match price at the limit-down level. Its final stated rule also includes a market-cap band of 5–10 billion yuan. The post…

EquitiesChina marketsMean reversionTechnical indicators
SuperMind

This stock screening idea selects shares with a daily price range above one, large-order net volume above 0.05 for at least three consecutive days, and excludes Beijing-listed A-shares. The article presents the conditions as a way to find active market…

China marketsEquitiesTechnical indicatorsSentiment
SuperMind

This document describes a Chinese equity screen that selects stocks with a 14-period RSI below 65, greater displayed buy-side than sell-side volume, and codes beginning with 60. It presents these conditions as a way to combine a technical indicator, an order…

EquitiesTechnical indicatorsSentimentRisk management
Amberdata research

The document compares free and paid crypto options scanners for professional trading teams. It explains that scanners consolidate activity across exchanges and that richer tools can report net volume and positioning, delta-based butterfly measures, block and…

CryptoOptionsVolatilitySentiment
SuperMind

This note outlines a China A-share selection rule combining price range, large-order activity, and buying pressure during the opening auction. Its formula also requires the close to exceed a prior moving-average reference, sets a minimum intraday range…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This post presents a short-term stock screen built around price below 12, elevated intraday amplitude, and large-order net buying or trading activity. Its formula reference uses a high-price change condition, volume above twice its five-day average, and a…

EquitiesChina marketsTechnical indicatorsSentiment
Kraken Learn

Bored Ape Yacht Club is an Ethereum NFT collection whose tokens depict distinct characters assembled from combinations of visual traits. The document describes how rarity can shape collector interest and how ownership also grants access to online and…

CryptoSpot marketsSentiment
SuperMind

This note proposes screening Chinese stocks associated with the metaverse theme using two additional conditions: a positive institutional-flow measure and greater displayed volume at the best bid than at the best ask. The stated rationale is to combine…

China marketsEquitiesMarket microstructureSentiment
SuperMind

This A-share selection idea filters for turnover between 3% and 12%, at least one limit-up event during the preceding 25 days, and a three-session price pattern. The article interprets moderate turnover as a liquidity filter, a recent limit-up as a sign of…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This stock-selection example screens for companies associated with the metaverse, positive institutional-flow readings, and a closing price above the prior day’s low. It presents the conditions as a way to combine an industry theme, an investor-flow signal,…

EquitiesTechnical indicatorsSentimentChina markets
SuperMind

This stock-screening idea selects Shanghai-listed shares whose codes begin with 60, whose turnover rate falls between 3% and 12%, and whose large-order net flow remains above 0.05 for at least three consecutive days. The stated rationale is that positive…

EquitiesChina marketsSentimentMomentum
SuperMind

The article defines market sentiment as participants’ collective outlook, which may be optimistic, pessimistic, or neutral and can be shaped by economic releases, company results, politics, news, and social discussion. It introduces sentiment analysis as a…

SentimentMachine learningEvent-drivenMomentum
BigQuant

This article argues that during Chinese sector rallies, a highly visible limit-up leader may serve as an attention and sentiment anchor while larger positions are accumulated or exited across less prominent related stocks. It describes a sequence in which…

EquitiesChina marketsSentimentMarket microstructure
SuperMind

This Chinese equity screen combines membership in a metaverse-related category with an opening-session price gain below six percent and a 15-minute MACD condition described as a shortening negative histogram. The intended rationale is to focus on a named…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

This Chinese equity screening rule combines a relative strength index below 65, a condition based on price change multiplied by net volume from very large orders, and more than two limit-up days within ten days. The post presents these as signals for…

EquitiesTechnical indicatorsSentimentMomentum
SuperMind

This Chinese-language post outlines a daily A-share stock screen combining three conditions: MACD above zero, share price below 12 yuan, and afternoon net inflows from large orders. It says the screen is run before 10 a.m. each trading day. The rationale is…

China marketsEquitiesTechnical indicatorsSentiment
Amberdata research

This market commentary links the week’s U.S. data calendar to expected crypto volatility, focusing on the Federal Reserve Beige Book, PCE inflation, and a scheduled FOMC meeting. It argues that PCE is the most likely near-term volatility catalyst, while the…

CryptoOptionsVolatilityEvent-driven
SuperMind

This A-share selection idea filters stocks in the metaverse concept group by two opening-auction conditions: the quoted gain at 9:25 must be below 6%, and net buying attributed to major participants must be positive. The post frames positive auction buying…

EquitiesChina marketsSentimentMarket microstructure