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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

8,116 documents

NautilusTrader

This reference explains the fields used to describe a listed put or call on a non-crypto underlying. It covers contract identity, underlying asset, option type, strike, activation and expiration times, premium currency, price precision, minimum price…

OptionsDerivatives pricing
Amberdata research

This market report reviews crypto price action and options positioning during a sharp late June 2023 rally. It links the move to news about spot ETF filings and a new exchange, then describes rising Bitcoin volatility, a higher options term structure, and a…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This feature note describes a chart comparing an asset’s at-the-money implied volatility (ATM-IV) with its realized close-to-close log return. It uses the implied volatility observed at the start of the interval as an estimate of the expected daily move,…

OptionsVolatilityDerivatives pricing
BigQuant

The document discusses pricing path-dependent snowball structured notes by decomposing their payoff scenarios into exotic option components and valuing them with Monte Carlo simulation or partial differential equations. It also considers how equity index…

OptionsDerivatives pricingVolatilityRisk management
Amberdata research

This brief market recap highlights four observations about Bitcoin and Ether derivatives as of November 22, 2022: realized and implied volatility had fallen, the six-month historical volatility spread between ETH and BTC was described as supported, option…

CryptoOptionsVolatilityDerivatives pricing
BigQuant

This report frames next-day direction in China’s Wind All A-share index as a binary classification task. It trains a decision-tree-based AdaBoost model on 51 daily features drawn from several markets and asset classes, including repo rates, credit spreads,…

China marketsEquitiesMachine learningBacktesting
BigQuant

This summary compares two research reports on protecting portfolios during market stress: one published before a major volatility episode and another written afterward. It frames their comparison around how investors assess defensive strategies before a…

Risk managementOptionsMomentumFactor investing
BigQuant

This research summary describes a multi-factor approach to selecting Chinese convertible bonds. It treats each bond’s value as a combination of straight-bond value and embedded option value, and examines how bond returns relate to the underlying stock. The…

Fixed incomeOptionsFactor investingPortfolio construction
Amberdata research

This weekly market note examines how the XRP ruling and other headlines affected crypto prices, implied volatility, and options positioning. It contrasts a quiet macro calendar and subdued longer-term realized volatility with event-driven moves in the front…

CryptoOptionsVolatilityEvent-driven
Amberdata research

This market commentary reviews Bitcoin and Ethereum options positioning alongside activity in oSQTH for the week covered. It describes several reported structures: a put spread financed with calls, a put risk reversal, a short-dated straddle sale, call…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This newsletter connects a softer US inflation and labor market outlook with expectations for Federal Reserve rate cuts and possible support for crypto prices. It then frames Bitcoin’s decline in the context of German government sales and anticipated Mt. Gox…

CryptoOptionsVolatilityDerivatives pricing
vn.py community

This forum exchange addresses a connection failure encountered while following a VeighNa tutorial on retrieving option quotes through the CTP interface. The questioner has authorization for a futures broker’s test account and asks whether completing…

OptionsFuturesExecution
Amberdata research

This podcast recap discusses Bitcoin options-market conditions around the ETF narrative, including term structure, skew, and changes in inter-dealer flows. It also describes exchange structured products: Double-Win, a range-based payoff compared to a…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This market commentary links a risk-off episode to declines in stocks and crypto, stronger gold, increased volatility, and heavy leveraged liquidations. It compares perpetual futures with spot markets, arguing that forced selling and uneven order-book depth…

CryptoOptionsPerpetual futuresVolatility
Hummingbot docs

This connector guide explains how to prepare a Derive account for automated trading through Hummingbot. It covers connecting a wallet, depositing assets, registering a session key, creating a subaccount, and entering the wallet address, session key,…

CryptoPerpetual futuresOptionsTechnical indicators
BigQuant

The article surveys common sources of investment loss, including broad market movements, issuer default, illiquidity, interest-rate changes, inflation, geopolitical events, concentration, business problems, and legal or regulatory changes. It explains these…

Risk managementPortfolio constructionFixed incomeOptions
TqSdk

This Python module documents functions for calculating common technical indicators from market bars and options data. The visible functions include average true range, bias, Bollinger Bands, directional movement, KDJ, MACD, parabolic SAR, and Williams %R.…

Technical indicatorsFuturesOptionsVolatility
Amberdata research

This market commentary reviews BTC and ETH options conditions ahead of expected ETH ETF trading. It reports falling realized volatility and softer one-month implied volatility, alongside positive carry that may appeal to traders expecting range-bound prices.…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This market commentary links a stronger-than-expected U.S. jobs report and falling unemployment to reduced expectations for a large Federal Reserve rate cut. It discusses upcoming inflation releases as possible catalysts for further rate-market repricing,…

CryptoOptionsVolatilityEvent-driven
Amberdata research

This market commentary examines Bitcoin and Ether options alongside spot prices, macro events, and regulatory news as of April 23, 2023. It discusses dealer gamma, implied volatility, volatility risk premium, term structure, and trading flows. The author…

CryptoOptionsVolatilityDerivatives pricing
BigQuant

This Chinese-language article curates research papers and books on reinforcement learning (RL) in finance. Its examples span trading and market applications, Q-learning combined with Black–Scholes, option hedging and dynamic replication, portfolio…

Machine learningOptionsExecutionPortfolio construction
Amberdata research

This market commentary links Federal Reserve expectations and geopolitical events with moves in bonds, gold, equities, and crypto. It reports that markets were pricing a greater chance of the Federal Reserve holding rates, while gold continued rising amid…

CryptoOptionsVolatilityFutures
Amberdata research

The document introduces a charting feature for viewing how implied-volatility smiles have changed over recent time intervals and where current option pricing sits on those curves. The visualization is intended to help traders assess both the level of implied…

OptionsVolatilityDerivatives pricing
Amberdata research

This market recap reviews BTC and ETH options conditions around a period of rising crypto prices and an approaching halving. It compares realized and implied volatility, term structures, call and put skew, options activity, and dealer gamma. The commentary…

CryptoOptionsVolatilityDerivatives pricing