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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
WonderTrader
14 documents
Alphalens
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 examines why exchange market data is sold rather than made freely available, including whether public access would improve transparency and whether historical tick data could be released without charge. The responses frame exchange data as both…

Market microstructureExecution
Quant Q&A

Deep bids and asks can serve several purposes beyond immediate execution. Orders near the inside may preserve queue priority, while orders placed far away can potentially capture extreme price moves caused by algorithmic failures or manual entry mistakes.…

Market microstructureMarket makingExecution
Quant Q&A

The document explains how to inspect market data carried in FIX/FAST over UDP. It points to a native C++ decoder based on QuickFAST and describes adapting a sample program to read the captured data. Another option is a Windows FAST codec, with a small…

Market microstructureExecution
Quant Q&A

The document examines how to quote an FX swap when the near and far legs have different notionals. It presents a proposed shortcut based on net spot exposure and far-leg swap points, then compares it with pricing each leg separately. A worked EUR/USD example…

ForexDerivatives pricingExecution
Quant Q&A

This question frames a market-microstructure research problem: whether intraday adverse selection on a futures or options contract changes systematically as that contract approaches expiry. The focus is the instrument itself, rather than adverse selection in…

FuturesOptionsMarket microstructureExecution
Quant Q&A

The document describes a way to size orders across a geometric price grid so that the average execution price approaches a chosen target. It starts with equally sized orders, whose average price differs from the target, then adjusts each order’s weight…

Grid tradingPosition sizingExecution
Quant Q&A

The document compares approaches for calculating American-option implied volatility repeatedly in a production setting. It discusses closed-form approximations, including Barone-Adesi–Whaley, Roll-Geske-Whaley, Ju–Zhong, and Bjerksund–Stensland, while…

OptionsDerivatives pricingVolatilityExecution
Quant Q&A

The document explains how dollar bars can be used in a machine-learning workflow despite their irregular time spacing. A bar retains the familiar structure of a time bar, such as open, high, low, and close, so these values can be supplied as model features.…

Machine learningBacktestingExecutionMarket microstructure
Quant Q&A

The document examines the assumption that a small order has negligible influence on market observations and price dynamics. That assumption can make historical backtests easier because the recorded order book or other market data are left unchanged by…

Market microstructureExecutionBacktestingHigh-frequency trading
Quant Q&A

The document explains why an institutional customer might use an executing broker even when it already has a prime brokerage relationship. Prime brokers provide a broader package of services and can execute trades, while executing brokers may focus on…

ExecutionMarket microstructureEquities
Quant Q&A

The document raises the problem of hedging a large fixed-rate bond issuance swap. A corporate issuer pays fixed on its bond and receives fixed in a swap to obtain floating-rate exposure; the bank on the other side must manage the resulting interest-rate…

Fixed incomeRisk managementExecutionMarket microstructure
Quant Q&A

The document asks why traders use leverage if it does not improve a strategy’s risk-to-return ratio. Its answer distinguishes changing a ratio from scaling the amounts represented by that ratio: leverage increases both gains and losses, allowing a trader to…

Risk managementPosition sizingExecution
Quant Q&A

The document describes the OCC-style 21-character format for exchange-traded option symbols. It breaks the descriptor into a seven-character root, a six-digit expiration date, a one-character call or put marker, and an eight-character strike field. It…

OptionsUS marketsExecution
Quant Q&A

The question asks whether a CME futures order book consists of aggregated stop and limit orders, using a hypothetical book to illustrate how consuming displayed offers can change the cost of executing a buy order. It also asks how the spread could narrow…

FuturesMarket microstructureExecution
Quant Q&A

The document describes a one-minute foreign-exchange backtest that chooses a trade direction using the next bar’s close. Because that information is unavailable at entry time, the apparent advantage is a look-ahead bias rather than a usable signal. It also…

ForexBacktestingRisk managementExecution
Quant Q&A

The document discusses ways to backtest a daily signal that indicates buying, selling, or holding an equity position. It names R packages for strategy testing and portfolio analysis, while noting that a simple strategy can also be modeled with return and…

BacktestingEquitiesExecutionRisk management
Quant Q&A

The document outlines end-of-day statistics that can be computed for each ticker after a market closes. These include price and size summaries for bids and asks, spreads, executed volume, volume share, VWAP, execution counts, and intervals between trades. It…

ExecutionMarket microstructureStatisticsEquities
Quant Q&A

The document discusses timestamp reliability in free historical data from Gain Capital, especially for combining non-FX instruments or multiple feeds in a backtest. One respondent reports that observations were correctly ordered within individual CSV files…

Market microstructureBacktestingExecutionForex
Quant Q&A

The document frames a practical question about pricing resting buy and sell limit orders in a market making strategy for liquid futures. It asks which microstructure signals should influence quotes and raises portfolio valuation as a related concern. The…

FuturesMarket makingMarket microstructureExecution
Quant Q&A

The discussion explains that pegged orders do not necessarily retain first-in-queue priority when prices move. Queue handling depends on the exchange’s order type and matching rules; traders should check venue documentation, especially for time priority and…

Market microstructureExecutionHigh-frequency trading
Quant Q&A

This discussion considers whether quasi-Monte Carlo (QMC) can help price path-dependent derivatives and how to speed up Monte Carlo simulations. It explains that an option price is an expectation over risk-neutral paths, so QMC can in principle be used to…

OptionsDerivatives pricingStatisticsExecution
Quant Q&A

The document discusses how to estimate the coefficient in a square-root model of equity market impact. Suggested approaches include regressing realized price moves against order size relative to volume, checking a log-log plot for square-root scaling, and…

EquitiesExecutionMarket microstructureStatistics
Quant Q&A

The document challenges the idea that a minimum viable holding period can be derived from transaction costs independently of a strategy. Trading costs depend on how a strategy trades: for example, momentum may demand buying after prices have risen, while…

ExecutionMarket microstructureMean reversionMomentum
Quant Q&A

The document explains how a long option’s gamma profit and loss relates to realized volatility versus the implied volatility used to price it. Under the stated continuous hedging formula, the gamma component is positive when realized variance exceeds implied…

OptionsVolatilityDerivatives pricingExecution