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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

4,510 documents

Amberdata research

This weekly options commentary links a rally in risk assets and a more dovish interest-rate outlook to bullish sentiment in Bitcoin and Ethereum. It reviews macroeconomic catalysts, spot performance, implied volatility, options skew, and reported trading…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock-screening idea selects companies in the metaverse theme whose circulating market value exceeds 10 billion yuan and that appeared on the prior day’s trading leaderboard. It combines a thematic filter and a size threshold with recent trading…

EquitiesChina marketsSentimentTechnical indicators
SuperMind

This Chinese stock-screening note proposes selecting shares with an amplitude above a stated threshold, rising lows, and inclusion in the previous day’s top-trader activity rankings. It frames the ranking data as a way to identify market attention and pairs…

China marketsEquitiesTechnical indicatorsSentiment
SuperMind

This Chinese stock selection proposal combines daily price movement, a reversal pattern, institutional net buying and company size. It first screens for an intraday high-low range above 1%, then looks for a reversal, evidence that large holders crossed above…

EquitiesTechnical indicatorsSentimentChina markets
SuperMind

This A-share screening idea combines a momentum-style technical filter with an estimate of buying versus selling pressure. It selects stocks with a 14-period RSI below 65 and an external-to-internal volume ratio above 1.3, then ranks qualifying names by a…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

This research summary examines whether institutional trading before earnings announcements contributes to mispricing and post-earnings announcement drift (PEAD). It measures abnormal institutional demand before announcements and relates it to subsequent…

EquitiesEvent-drivenSentimentStatistics
SuperMind

This Chinese equity screening idea combines a relative strength index below 65, a condition based on the product of price change and net buying by very large orders, and a circulating share count no greater than 5.5 billion. It aims to identify smaller-float…

EquitiesTechnical indicatorsSentimentChina markets
Amberdata research

The newsletter links inflation trends, expected Federal Reserve rate cuts, precious metals, and crypto prices to possible options trades. Its author argues that regulatory uncertainty could weigh more on Ethereum than Bitcoin, making ETH call selling…

CryptoOptionsVolatilityEvent-driven
SuperMind

This stock-selection idea combines daily range greater than 1%, an afternoon large-order net inflow condition, and a three-candle reversal pattern called a morning star. The article describes the pattern as a large bearish candle, a smaller candle, then a…

EquitiesTechnical indicatorsSentimentRisk management
Amberdata research

The document outlines three ways to turn blockchain data into potential crypto trading signals: exchange flows, large wallet transfers, and network activity. It suggests treating rising inflows to decentralized exchange pools as possible selling pressure and…

CryptoOn-chain dataBreakoutSentiment
SuperMind

This stock selection rule looks for shares with daily turnover between 3% and 12%, displayed best-bid volume greater than best-ask volume, and a listing on that day's Dragon-Tiger list. Together, these filters target actively traded stocks with visible…

EquitiesChina marketsMarket microstructureSentiment
BigQuant

This Chinese-language overview surveys Microsoft Research Asia’s published work on applying artificial intelligence to quantitative investing since 2017. It says the research spans stock selection, risk models, algorithmic trading, data augmentation,…

Machine learningEquitiesStatisticsSentiment
SuperMind

This stock-screening idea combines a daily amplitude filter, a positive weekly MACD condition, and buying activity in large or extra-large orders during the opening auction. The stated rationale is that amplitude and weekly MACD help identify active shares…

EquitiesChina marketsTechnical indicatorsMomentum
Amberdata research

This report surveys on-chain and market measures used to study Bitcoin’s price cycles, investor sentiment, network usage, and miner behavior. It explains moving averages and the Pi Cycle indicator as trend or cycle gauges, and describes realized…

CryptoOn-chain dataTechnical indicatorsSentiment
SuperMind

This stock-screening example selects shares using three conditions: a stated price-range threshold, positive institutional fund flow, and a control-ratio threshold. The accompanying examples describe deriving a range measure from daily prices, aggregating…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

The proposed stock screen selects shares with MACD above zero, ranks them by attention from highest to lowest, and requires that they be in a strong upward move. The selection is intended to run after each trading day’s close. The document gives the standard…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

The document describes a Chinese equity selection rule combining price movement and large-order net flows. It screens for stocks with an amplitude above 1, a closing price below 20, and positive large-order net volume for at least three consecutive days. It…

EquitiesChina marketsTechnical indicatorsSentiment
BigQuant

This essay contrasts three broad approaches to investing through Warren Buffett, George Soros, and James Simons. It describes Soros’s reflexivity framework, in which investor beliefs can move prices and price changes can then reinforce those beliefs. Buffett…

Multi-assetSentimentStatisticsMachine learning
SuperMind

This note describes a Chinese A-share stock screen that selects companies in the metaverse sector appearing on the previous day’s Dragon-Tiger list, then filters for a 14-period RSI below 65. It presents the list appearance as a market-attention signal and…

China marketsEquitiesTechnical indicatorsSentiment
BigQuant

This research summary examines why analyst earnings forecasts can vary widely and how that dispersion relates to subsequent stock returns. It focuses on the possibility that companies delay disclosing bad news, leaving analysts with incomplete information…

EquitiesStatisticsSentiment
SuperMind

This stock-selection idea combines daily price amplitude above 1, afternoon large-order net inflow, and an appearance on the prior day’s trading list. The article treats amplitude as a measure of price movement, afternoon order flow as a possible sign of…

EquitiesTechnical indicatorsSentimentRisk management