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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 describes a way to calculate minute returns when a price table contains rows only for minutes with trades. It recommends building a complete minute-by-minute time grid, placing observed prices at their timestamps, and carrying the last available…

EquitiesStatisticsExecutionMarket microstructure
Quant Q&A

The document asks whether signed net volume could predict asset performance in a way that resembles the information carried by returns. It distinguishes ordinary gross volume from net volume, defined as buyer-initiated volume minus seller-initiated volume.…

Market microstructureExecutionTechnical indicatorsBacktesting
Quant Q&A

The document discusses how to assess a cryptocurrency portfolio rebalancing strategy based on mean reversion, especially when frequent trading costs overwhelm attractive backtest results. Its example compares hourly and daily backtests under different fee…

CryptoMean reversionPortfolio constructionBacktesting
Quant Q&A

The note explains the effect of the isInArrears setting on floating-rate coupons in a QuantLib IborLeg. When enabled, the coupon’s fixing date is based on the accrual period’s end date, adjusted backward by the index’s fixing days and calendar rules. When…

Fixed incomeDerivatives pricingExecution
Quant Q&A

The document clarifies that “tick data” can refer to different market event streams. Trade ticks record executions, typically with price, quantity, and time; bid/ask updates capture changes in quoted prices and sizes; order book or market depth data can…

Market microstructureExecutionHigh-frequency tradingFutures
Quant Q&A

The document shows how to calculate a running net amount for a short-selling backtest when positions are added over time. The proposed recurrence updates the previous net amount by the next period's short-sale price change, then adds the value of any new…

BacktestingEquitiesPosition sizingExecution
Quant Q&A

The document compares storing market bars in separate arrays by field with storing each bar as an object. The column-oriented option keeps open, high, low, close, and volume values in separate arrays. One answer recommends this layout for time-series…

BacktestingExecutionMarket microstructure
Quant Q&A

The discussion explains Nasdaq Sell Imbalance-Only orders, which are limit orders intended to provide liquidity against orders participating in the closing auction. The cited description says sell IO orders execute only at or below the closing-time bid or…

EquitiesExecutionMarket microstructureHigh-frequency trading
Quant Q&A

The document poses a practical question about deriving an executable B/C price from two markets, A/B and A/C, on the same exchange. The proposed route is to buy A with B and then sell A for C, with the achievable price depending on the desired quantity of C.…

Market microstructureExecutionArbitrageCrypto
Quant Q&A

The document raises an apparent mismatch in NASDAQ ITCH data: an ask order is added at a limit of ten dollars, yet an executed-with-price message reports a fill one cent lower. It highlights a microstructure and data-interpretation question about how…

EquitiesMarket microstructureExecution
Quant Q&A

The document considers a two-period market with a risk-free asset and a stock whose future price can move along several scenarios. It asks whether short selling creates an arbitrage when each stock trade incurs a transaction cost proportional to its volume.…

ArbitrageEquitiesExecutionRisk management
Quant Q&A

This document is a curated reading list spanning factor investing, trading and execution, volatility estimation, derivatives pricing, and commodity futures. It names influential papers and briefly describes their contributions, including multifactor asset…

Factor investingExecutionVolatilityDerivatives pricing
Quant Q&A

The discussion addresses measuring latency between a trading server and liquidity providers when their FIX SendingTime values differ from the local clock by around tens of milliseconds, despite the local server using SNTP. The central caution is that a…

ForexExecutionMarket microstructureHigh-frequency trading
Quant Q&A

The discussion outlines how exchange market data licensing can depend on whether data is historical or real time, how it is delivered, and how it is used. Professional users, firms redistributing data, and users of non-display applications may face…

Market microstructureExecutionUS markets
Quant Q&A

The document explains a practical approach to solving a stochastic Hamilton–Jacobi–Bellman equation for a trading control problem. It separates the equation into an optimization over the control and the remaining terms that describe the value function’s…

Market makingExecutionStatisticsRisk management
Quant Q&A

The document corrects the claim that futures markets have no bid–ask spread. It explains how bids and offers at different prices form a spread in the central order book: after orders at the same price trade, a buyer may need to pay the next offer while a…

FuturesMarket microstructureExecution
Quant Q&A

The document asks whether Google or Yahoo Finance streams can provide every price change during the trading day. The replies describe polling quote pages or APIs at short intervals and detecting unchanged prices, including an approach that periodically reads…

EquitiesHigh-frequency tradingMarket microstructureExecution
Quant Q&A

The document concerns a value-function integro-differential equation from a high-frequency trading model with limit and market orders. The question asks how to solve it numerically when the equation couples multiple market states and includes optimization…

High-frequency tradingMarket microstructureExecutionStatistics
Quant Q&A

The document distinguishes two practical components of trading costs: broker commissions and slippage. Commissions are described as charges per share, while slippage reflects execution prices that differ from the market and depends on trading volume, order…

ExecutionMarket microstructureBacktesting
Quant Q&A

The document explains how exchanges’ minimum price increments determine whether a bid and ask can match. Prices are discrete at the instrument’s tick size, so orders are entered at permitted price levels rather than at arbitrary decimal values. A buyer’s bid…

Market microstructureExecution
Quant Q&A

The document explains why a delta-hedged option position is not necessarily a source of trading profit. In an idealized model, a perfectly hedged portfolio earns only the risk-free rate. A dealer may earn revenue by selling an option above its theoretical…

OptionsDerivatives pricingVolatilityExecution
Quant Q&A

The document presents a short-sale backtest example and asks why an equity calculation differs from a return estimate based on the ratio of the mean price to the close. The trader sells short using a quantity determined by dividing available capital by the…

BacktestingEquitiesExecutionRisk management
Quant Q&A

The answer argues that historical tick data should be evaluated for integrity because vendors using the same exchange feeds can still deliver materially different records. It identifies packet loss and session recovery behavior, parser errors, lossy…

Market microstructureExecutionBacktestingHigh-frequency trading
Quant Q&A

The document considers how an order gateway can retain sent and received FIX messages for audit without adding substantial latency to trading. One approach is to pass messages to a dedicated logging thread through inter-thread communication, allowing disk…

ExecutionMarket microstructureRisk management