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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

3,736 documents

Kraken Learn

Band Protocol is described as a blockchain service that brings external data to decentralized applications. Validators collect and verify information requested by applications, then relay it through the protocol’s blockchain so transactions can be publicly…

CryptoDeFiOn-chain dataRisk management
Amberdata research

A discussion of research on digital asset managers and hedge funds describes growing institutional interest in crypto, including dedicated strategies, senior staffing, and plans to develop trading approaches and investment products. The report summary notes…

CryptoMarket microstructureOn-chain dataVolatility
Amberdata research

The article summarizes research comparing cryptocurrency data providers and argues that raw data gains value from the context and presentation built around it. It distinguishes on-chain and off-chain sources, and describes how providers may differentiate…

CryptoMarket microstructureExecutionOn-chain data
Amberdata research

The article explains how tokenization can represent fractional claims on real-world assets such as real estate, commodities, collectibles, private credit, equities, and intellectual property. A custodian or other trusted entity holds the underlying asset…

CryptoDeFiOn-chain dataMulti-asset
Amberdata research

The document outlines ways institutional investors can use blockchain data to study digital asset activity. Aggregated wallet balances, transactions, network fundamentals, and cross-chain flows can help teams monitor portfolio exposure, protocol adoption,…

CryptoOn-chain dataDeFiRisk management
Amberdata research

The document argues that combining blockchain activity data with options and volatility data may help traders identify crypto opportunities and build hedges. It describes comparing on-chain transaction flows with realized volatility, as well as examining…

CryptoOptionsOn-chain dataVolatility
Amberdata research

The document describes Amberdata joining Pyth as a first-party publisher of real-time cryptocurrency prices. Pyth is presented as an oracle network that brings off-chain market data onto blockchains for decentralized applications, initially on Solana. The…

CryptoOn-chain dataDeFi
Amberdata research

The document describes Amberdata Beacons, an on-chain data feed service built with API3’s Airnode technology and announced for ETHDenver 2022. Each Beacon is continuously updated and uses a single first-party oracle: the data provider publishes its own…

CryptoDeFiOn-chain data
Amberdata research

The report examines Bitcoin supply age bands and wallet balance cohorts to describe a possible transfer of coins during a correction. It explains how HODL waves track time since coins last moved, then compares changes among younger and older supply bands…

CryptoOn-chain dataMarket microstructure
Amberdata research

This market snapshot combines macro data with crypto spot, derivatives, liquidity, positioning, ETF, stablecoin, and DeFi lending indicators. It interprets recent long liquidations as a clearing of positions built during an earlier short squeeze, while…

CryptoPerpetual futuresMarket microstructureOn-chain data
Amberdata research

The snapshot combines price and volatility data with spot and derivatives volume, open interest, funding, order-book depth, ETF flows, stablecoin supply, and DeFi lending measures. It interprets those indicators against tariff and geopolitical headlines,…

CryptoPerpetual futuresVolatilityMarket microstructure
Hyperliquid docs

The document outlines the historical datasets available for Hyperliquid and how advanced users can retrieve them from public cloud storage. Market data includes level-two order book snapshots, while asset context files are stored separately. The archive is…

CryptoMarket microstructureBacktestingOn-chain data
Amberdata research

The document surveys indicators intended to help assess potential market tops and bottoms in Bitcoin and Ethereum. It describes moving averages as possible trend and support or resistance references, and compares market capitalization with realized…

CryptoTechnical indicatorsOn-chain dataSentiment
SuperMind

The article explains that Ethereum’s mempool holds transactions awaiting inclusion in a block, and that fees and maximal extractable value can influence transaction priority. It distinguishes real-time pending-transaction data from historical records and…

CryptoOn-chain dataExecutionMarket microstructure
Hyperliquid docs

The document explains two Hyperliquid aligned quote asset specifications. AQAv1 links a stablecoin’s onchain supply to protocol revenue sharing and offers trading incentives when the asset is used for eligible spot pairs or HIP-3 perpetual markets. Its…

CryptoOn-chain dataSpot marketsPerpetual futures
Amberdata research

The interview describes Titan’s approach to spot swaps on Solana: gather quotes from on-chain venues and other aggregators, then route trades among those sources with the aim of improving price and limiting slippage. It explains that the system evaluates…

CryptoDeFiOn-chain dataExecution
Cryptohopper blog

This guide describes a qualitative process for assessing cryptocurrencies as long-term investments. It distinguishes coins, which generally operate on their own blockchains, from tokens, which are issued on existing chains and depend on the intended…

CryptoOn-chain dataRisk management
Amberdata research

This market snapshot reviews how tariff news, Treasury yields, inflation, and employment data shaped crypto trading conditions. It describes an initial decline in Bitcoin, Ethereum, and Solana followed by a rebound as bond markets stabilized, while warning…

CryptoSentimentOn-chain dataPerpetual futures
Amberdata research

The document explains the two main parts of a blockchain block and how they work together. A header holds identifying and validation information, including the prior block’s hash, protocol version, timestamp, mining target, nonce, and Merkle root. The body…

CryptoOn-chain data
Amberdata research

This overview distinguishes price-based market data from blockchain activity data and describes metrics that may help frame digital-asset valuation. Market capitalization is token supply multiplied by price, while trading volume is used as a rough gauge of…

CryptoOn-chain dataDeFiStatistics
Amberdata research

Ethereum transaction inputs and event logs store values in compact encoded forms. Applications commonly rely on a contract’s ABI to map that data to function names, argument types, and readable values. Maintaining ABI files becomes difficult when an…

CryptoDeFiOn-chain dataExecution
Amberdata research

This market snapshot combines derivatives positioning, funding, order books, ETF flows, stablecoin activity, and macroeconomic data to assess crypto market conditions. It interprets BTC and ETH's unusually low 30-day correlation as a reason to question…

CryptoPerpetual futuresMarket microstructureOn-chain data
Amberdata research

This weekly snapshot reviews crypto market conditions from March 19 to 26, 2024. It links Bitcoin’s recovery after an inflation-driven dip to persistent ETF demand and pre-halving accumulation, while noting uncertainty about demand after the halving and…

CryptoOn-chain dataDeFiSpot markets
Amberdata research

The document introduces analytics for stablecoin lending and borrowing across Aave, Compound, and MakerDAO on Ethereum, Arbitrum, Optimism, and Avalanche. It describes hourly and daily historical measures, including deposits, borrowing, interest earned,…

DeFiCryptoOn-chain dataRisk management