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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 stock selection rule combines three daily filters: turnover between 3% and 12%, the product of daily price change and large-order net flow above zero, and the closing price above its five-day moving average. A further code and exchange filter narrows…

EquitiesChina marketsMomentumTechnical indicators
BigQuant

The document describes a buy-sentiment factor built by distinguishing aggressive purchases, which execute against sell orders already on the book, from passive purchases, which wait as limit orders for incoming sells. It argues that finer-grained market data…

EquitiesSentimentMarket microstructureFactor investing
SuperMind

This A-share stock screen combines a relative strength index below 65 with an external-to-internal trade volume ratio above 1.3 and a positive institutional-flow measure. It presents the indicators as a way to combine a technical condition with trading…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This Chinese stock-selection proposal screens for turnover between the stated bounds and greater displayed buying volume than selling volume at the best quote. It then looks for a positive price change during the auction and aggregate buying by large and…

EquitiesMarket microstructureSentimentExecution
SuperMind

This post presents a Chinese stock selection rule combining turnover, displayed order-book quantities, and prior-day price-limit behavior. It keeps stocks with turnover between 3% and 12%, where first-level buy quantity exceeds first-level sell quantity, and…

EquitiesMarket microstructureSentimentChina markets
Amberdata research

The article explains call/put skew as the difference in implied volatility between comparable options. Higher call implied volatility is interpreted as stronger demand for upside exposure, while higher put implied volatility suggests greater demand for…

CryptoOptionsVolatilitySentiment
SuperMind

This Chinese equity-screening post combines a 14-period RSI threshold below 65, a three-day candlestick condition, and a measure intended to capture price movement alongside very large order flow. Its example formulas and Python sketch also restrict the…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

The document proposes screening Chinese equities in the metaverse theme for positive institutional-flow readings and relative volume between 1.5 and 6 times a five-day average. Its stated logic aims to focus on thematic stocks with buying interest and…

EquitiesChina marketsMomentumSentiment
SuperMind

This Chinese-language post describes an equity screen combining a 14-period RSI below 65, a three-session candle condition, and positive net buying attributed to major participants during the opening auction. The stated rationale is to find shares that have…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese-language post describes an equity screening idea that combines price movement, a morning-star pattern associated with a named stock, and positive large-order net flow over consecutive sessions. The intended rationale is to find stocks with…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

This research note describes a tactical asset allocation method that converts the tone of company and macroeconomic news into a slower-moving signal. News sentiment scores are aggregated weekly, then filtered with a two-sided cumulative sum (CUSUM) procedure…

Multi-assetSentimentMomentumPortfolio construction
SuperMind

The document outlines a daily screening idea for Chinese stocks associated with the metaverse theme. It selects stocks with a newly bullish KDJ crossover, ranks candidates by individual stock popularity, and proposes choosing the more popular names.…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This research summary examines whether internet search attention can help anticipate rotations between Chinese large-cap and small-cap equity indices. It treats search-index changes related to the two market styles as a proxy for investor sentiment,…

EquitiesChina marketsSentimentPortfolio construction
SuperMind

The document describes a simple momentum test on constituents of China’s Growth Enterprise Market index. It buys a stock at the next day’s open after a limit-up day, with parameters that can be changed to study different indices and holding periods. The…

China marketsEquitiesMomentumBacktesting
Amberdata research

This market snapshot reviews crypto developments alongside indicators of institutional and trader positioning. It discusses exchange security after a major exchange hack, a USDC refund mechanism, proposed crypto investment products, US policy changes, and…

CryptoFuturesSentimentMarket microstructure
SuperMind

The post describes a Chinese equity screen combining three conditions: membership in the metaverse industry, positive institutional flow, and a same-day bullish candlestick pattern named after the stock Kute Intelligent. It presents the pattern as a possible…

EquitiesTechnical indicatorsSentimentChina markets
Lumibot

This guide outlines six compact trading bot demos, each built around a single AI agent using plain-language instructions and built-in data tools. The examples include discretionary stock selection, market news, news sentiment, trend following, a…

Machine learningBacktestingTrend followingMomentum
SuperMind

This proposed Chinese equity screen targets stocks classified in the metaverse theme that have a positive return and large-order net volume above 0.05 for at least three consecutive days. The article explains the flow measure as a possible indication of…

EquitiesMomentumMarket microstructureSentiment
Amberdata research

This market newsletter presents a bullish Ethereum thesis against a backdrop of expected US inflation releases and possible changes in Federal Reserve rate-cut expectations. It frames ETH as a higher-beta technology and web3 exposure, while describing…

CryptoOptionsFuturesVolatility
SuperMind

This stock-selection proposal combines a relative-strength index filter with price movement, large-order net inflows, and rising stochastic-style KDJ readings. The stated screen requires RSI below 65, a positive product of percentage price change and a…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This stock screen combines an RSI reading below 65, a condition based on multiplying the daily percentage change by a measure of net inflow from very large orders, and an opening price change between negative two and positive five percent. The accompanying…

EquitiesTechnical indicatorsMomentumSentiment
Amberdata research

This market snapshot reviews digital-asset developments around early January 2024, including conflicting reports about spot Bitcoin ETF decisions, a lending-protocol exploit, and Solana’s recovery. It interprets reported spot trading activity, decentralized…

CryptoSpot marketsDeFiOn-chain data
SuperMind

The document outlines a daily post-close stock screen that combines a positive MACD reading, amplitude above 1, and ranking by individual-stock interest or popularity. It presents the standard MACD components based on exponential moving averages and defines…

EquitiesChina marketsMomentumTechnical indicators