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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
Quantopian lectures
45 documents
Binance API docs
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

9,660 documents

Quant Q&A

The document frames predatory trading as a contest between a trader attempting to force liquidation and a targeted trader who may be solvent and able to draw on reserves or credit to maintain a position. It contrasts this situation with models centered on…

Market microstructureRisk managementExecution
Quant Q&A

The document explains that a useful forecast target depends on the market-taking task. For a large order, a short-horizon mid-price forecast can help time execution. For a simple single-exchange strategy, the relevant question is whether prices will cross…

High-frequency tradingExecutionMarket microstructureArbitrage
Quant Q&A

The document explores how to build a trading system from traditional chart patterns and machine learning. It raises choices about classification targets, whether patterns should be labels or inputs, and whether a model can identify patterns directly from…

Machine learningTechnical indicatorsBacktestingExecution
Quant Q&A

The document explains why Level II equity market data does not have one universal update schedule. The cadence depends on the exchange and the particular data product. Some feeds publish aggregated book information on a fixed interval, while many products…

EquitiesMarket microstructureExecution
Quant Q&A

The discussion asks how to choose the number of historical candles used to estimate a spread z-score in a crypto perpetual swap pairs strategy. The question notes that different pairs appear to perform best with different window lengths in both backtests and…

CryptoPairs tradingPerpetual futuresBacktesting
Quant Q&A

The document explores modifying a depth-weighted midpoint so that distant quotes with little chance of execution contribute less. The proposed approach is to weight bid and ask levels by the probability that prices reach those levels, estimated from…

Market microstructureExecutionStatisticsVolatility
Quant Q&A

The document describes a liquidity-risk measure for a long-only equity portfolio: estimate how many days it would take to sell each holding. Under ordinary conditions, the measure can use average daily volume and an assumed participation rate. To represent…

EquitiesRisk managementExecutionMarket microstructure
Quant Q&A

A one-year-forward 2-year versus 5-year Treasury steepener can be built from bonds with settlement in one year or expressed through forward-starting interest rate swaps. For bonds, the examples construct forward exposures by combining securities that mature…

Fixed incomeFuturesCarryExecution
Quant Q&A

This exchange addresses a market data session that stopped receiving snapshots after a broker reported missing client heartbeats. The key diagnostic is that client heartbeats and server initiated test requests are distinct messages with different expected…

ExecutionMarket microstructureHigh-frequency trading
Quant Q&A

The discussion challenges the inference that widespread retail losses show short term prices are predictable. A trader’s profitability depends on more than whether prices move up or down: transaction costs such as spreads and commissions can create negative…

StatisticsRisk managementExecutionMarket microstructure
Quant Q&A

The document examines a proposed foreign exchange carry trade based on differences between brokers that accrue rollover interest continuously and those that apply it at a daily cutoff. The proposed trade briefly holds a high-yield currency position through…

ForexCarryArbitrageExecution
Quant Q&A

The document explains why a self-financing trading strategy is modeled as predictable, or previsible, while asset prices and portfolio value remain adapted. The key timing idea is that holdings for the next interval must be chosen using information available…

StatisticsExecutionMarket microstructure
Quant Q&A

The document explains how a binary strategy signal becomes a sequence of trading orders in a simple moving-average backtest. The signal represents the desired position: zero means holding no shares, while one means holding a share. Taking the signal's first…

BacktestingEquitiesTechnical indicatorsExecution
Quant Q&A

The document describes a forex market-making bot that places offers around the mid price and refreshes them at regular intervals. In the market described, thin order books can cause sharp mid-price jumps after a large order; the moves are said to last…

ForexMarket makingVolatilityExecution
Quant Q&A

The document clarifies the meaning of an intermarket sweep order (ISO) in the context of U.S. equity market rules. It distinguishes an ISO from an order that is automatically routed to other venues when it encounters better displayed prices. Instead,…

EquitiesExecutionMarket microstructure
Quant Q&A

The document explains how German-style leveraged certificates with a stop-loss knockout relate to products known as turbo warrants. The answer groups these instruments with mini futures and notes that issuers may use labels such as turbo certificates, short…

Derivatives pricingRisk managementExecution
Quant Q&A

Level 1 market data shows the best bid and ask, their displayed sizes, and sometimes the latest trade price and size. The document explains why changes in displayed bid or ask quantities cannot be treated as traded volume: a size change may reflect…

Market microstructureExecutionStatistics
Quant Q&A

The document explains why a trader might choose a contract for difference rather than buy shares directly. A CFD provides exposure to changes in an underlying stock’s price without ownership of the stock. Because the trader posts margin rather than paying…

EquitiesDerivatives pricingRisk managementExecution
Quant Q&A

The document considers how to simulate an order book for testing strategies that submit market and limit orders. It recommends beginning with a simplifying assumption: the simulated strategy’s orders are small enough not to alter the price path. This can…

BacktestingMarket microstructureExecutionStatistics
Quant Q&A

The discussion examines whether top-of-book queue sizes help predict the direction and timing of the next price move. The questioner implements a Markovian limit order book model and finds that empirical probabilities conditioned on bid and ask size are…

Market microstructureStatisticsExecutionHigh-frequency trading
Quant Q&A

The document asks what defines a package trade in rates markets, whether a package must be DV01-neutral, why hedge funds request one, and why it may be hard to price. Its example is a set of instruments traded together to target exposure around a particular…

Fixed incomeDerivatives pricingExecution
Quant Q&A

The document explains the Roll model, which estimates the bid-ask spread from the negative autocovariance of consecutive high-frequency price changes. The negative relationship arises when trades alternate between the bid and ask: transaction prices move…

Market microstructureStatisticsHigh-frequency tradingExecution
Quant Q&A

The document explains that novating a non-deliverable forward does not necessarily change its risk-free forward mark to market. The effect depends on how the trading desk separates the contract’s market value from adjustments for counterparty exposure,…

ForexDerivatives pricingRisk managementExecution
Quant Q&A

The document explores whether some constraints in high-frequency trading apply broadly, even to firms with substantial spending on hardware, software, and co-location. The response discusses data-center scale, venue fees, processor hardware, co-location, and…

High-frequency tradingMarket microstructureExecution