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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

9,660 documents

Quant Q&A

The document considers a hypothetical market in which stock prices can vary continuously, asking whether traders would keep improving the best bid and offer until a trade occurs. The response points out that real order books operate through discrete events,…

Market microstructureExecution
Quant Q&A

The document explains how incoming market orders are matched against resting limit orders. Exchanges generally prioritize the best available price, then apply venue-specific tie-break rules. The examples include time priority (FIFO), pro-rata allocation…

Market microstructureExecutionFuturesOptions
Quant Q&A

The discussion explains that a machine learning alpha signal can enter a stochastic control problem if it is given a temporal model that supports planning. One simple approach is to represent known time variation in trading opportunities and incorporate it…

Machine learningExecutionMarket microstructureStatistics
Quant Q&A

The document outlines how an investment bank can earn revenue from structured notes, including notes with embedded calls or autocall features. When a bank sells a note, it takes the other side of the client’s market view. It generally hedges exposures it…

OptionsDerivatives pricingRisk managementExecution
Quant Q&A

The document asks which time zone determines the trade date and value date in an FX transaction when dates are transmitted without a time-zone label. This matters for converting a date into a deadline for reconciling exposure, especially when the relevant…

ForexExecutionMarket microstructure
Quant Q&A

The document defines a supervised-learning target for limit order book data using the mid-price, calculated from the best ask and best bid. Each book update is treated as an observation, and the target records whether the mid-price rises, falls, or stays…

High-frequency tradingMarket microstructureMachine learningExecution
Quant Q&A

The discussion explains why Sharpe and Sortino ratios are usually not the main operating measures for passive ETF managers. Since these funds aim to track an index, their risk-adjusted returns largely reflect the index itself, leaving limited scope for…

Portfolio constructionRisk managementExecutionMarket microstructure
Quant Q&A

The document describes a proposed way to evaluate a multi-asset portfolio using weekly returns and a time-varying matrix of portfolio weights. The intended test samples start dates, measures performance over a one-year period, rebalances at regular…

BacktestingPortfolio constructionPosition sizingExecution
Quant Q&A

The discussion compares R with C++ and Python for quantitative research, data analysis, and production software. Contributors describe R as productive for exploratory analysis, statistical modeling, visualization, and working with established packages. They…

StatisticsMachine learningBacktestingExecution
Quant Q&A

The document raises an execution problem: a displayed best offer or bid disappears after a trader sends a market order to trade against it, potentially causing slippage. The trader wonders whether the quote was deceptive and asks how to identify or avoid…

ExecutionMarket microstructureRisk management
Quant Q&A

The discussion asks why retail investors may face minimum sizes when buying Treasury Inflation-Protected Securities. The response points to issuer-set minimum denominations in municipal securities, which have historically served investor-targeting and…

Fixed incomeExecutionMarket microstructure
Quant Q&A

The document asks how S&P 500 ETFs such as SPY and VOO trade when an index constituent changes, using Tesla’s addition as an example. It raises questions about whether managers rely on banks, accumulate shares before the effective date, or adjust creation…

EquitiesExecutionMarket microstructurePortfolio construction
Quant Q&A

The document describes a cryptocurrency market-making question about estimating a reference price for an Avellaneda–Stoikov style inventory-control strategy. The author proposes adjusting the initial price by cumulative signed market-order volume multiplied…

CryptoMarket makingMarket microstructureExecution
Quant Q&A

The document asks why investors generally cannot trade one listed stock directly for another, as they might exchange currencies or cryptocurrencies. It distinguishes stock-for-stock consideration in corporate actions, such as mergers, from ordinary trading,…

EquitiesMarket microstructureExecution
Quant Q&A

The document explains why stock prices can change when an exchange’s regular session is closed. New information can alter expectations about a company’s value or the conditions affecting it, so investors may revise the prices they are willing to trade at.…

EquitiesMarket microstructureExecution
Quant Q&A

The document asks how to quantify the price impact of trading ETFs over the counter. It contrasts a common participation-rate impact model with the possibility that ETF impact depends on how closely the market price tracks net asset value (NAV). If market…

EquitiesExecutionMarket microstructureMarket making
Quant Q&A

The question proposes estimating aggregate market-maker profit from quoted spreads multiplied by traded quantity in highly liquid options data. The response explains why this spread-based calculation is incomplete: it does not capture losses or gains from…

OptionsMarket makingMarket microstructureExecution
Quant Q&A

The document examines the costs of maintaining an equitized Euro Stoxx 50 exposure by rolling quarterly futures into the next liquid contract. It asks whether reported increases in index futures holding costs are plausible and what components could explain…

FuturesExecutionEquities
Quant Q&A

The document asks how to combine several dollar-neutral portfolios using nonnegative blend weights that sum to one while minimizing total turnover. The answer recommends expressing absolute-value constraints through nonnegative slack variables. A position is…

Portfolio constructionExecutionBacktesting
Quant Q&A

The document explains why spread cost depends on how an order interacts with the book. A market taker who buys at the ask or sells at the bid pays for immediate execution relative to a reference midpoint; a round trip across the quotes incurs the full…

Market microstructureExecutionMarket making
Quant Q&A

The document explains how to interpret announcements that a company will replace another in the S&P 500 after a specified close. For index return calculations, the outgoing company contributes through the stated effective close, while the incoming company is…

EquitiesUS marketsEvent-drivenExecution
Quant Q&A

In quote-driven markets, transaction prices can alternate between the bid and ask even when the underlying value is unchanged. This bid-ask bounce adds short-term fluctuations to observed trade prices alongside genuine price changes driven by supply and…

Market microstructureExecutionStatisticsEquities
Quant Q&A

A stop-market order becomes a market order when its trigger is reached, so a gap through the stop price can lead to a fill at the next available price rather than at the trigger. The example describes a sell stop set above a sharply lower opening price,…

ExecutionRisk managementEquitiesForex