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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

1,116 documents

Quant Q&A

The document asks whether Visual Basic can handle an order-routing calculation budget of about one millisecond, with much greater time expected for communication to and from exchanges. The replies distinguish modern Visual Basic .NET from older Visual Basic…

ExecutionHigh-frequency tradingMarket microstructure
Quant Q&A

The document explains how to interpret the sample count in the two-scale realized variance estimator (TSRV) and why the estimate can be negative. It treats n as the number of intraday observations over the interval being studied, rather than as a fixed count…

High-frequency tradingVolatilityStatisticsRisk management
Quant Q&A

This note discusses selecting the tuning parameters for the Two-Scale Realized Volatility estimator. It describes setting the lag parameter to one in the cited extension for dependent noise, and choosing the subsampling parameter as a constant times the…

VolatilityStatisticsHigh-frequency trading
Quant Q&A

The discussion examines how market-data latency affects order decisions and claims about market efficiency. When order book updates arrive faster than a non-colocated trader can receive information and send an order, the displayed book may no longer reflect…

Market microstructureHigh-frequency tradingExecutionBacktesting
Quant Q&A

The document lists potential sources for historical foreign exchange tick data, including TrueFX, Dukascopy, TickStory Lite, and HistData.com. It presents Dukascopy as an option for downloading hourly data files, either through a website or direct scripted…

ForexHigh-frequency tradingMarket microstructureExecution
Quant Q&A

The document introduces pre-averaging as a way to address microstructure noise in high-frequency observations of an underlying price process. It defines a statistic as a weighted sum of consecutive price increments, with weights obtained by evaluating a…

High-frequency tradingStatisticsMarket microstructure
Quant Q&A

The document asks whether exchanges match orders continuously or at scheduled times. Its answer says there is no universal rule across all venues, but describes major developed-market exchanges as generally using continuous-time matching. In that setting, an…

ExecutionMarket microstructureHigh-frequency trading
Quant Q&A

The document asks how to measure “viscosity” in financial time series and considers whether extremes in a simple close-to-close price-change divided by volume measure could represent low or high ease of movement. The replies distinguish this elementary…

Market microstructureHigh-frequency tradingTechnical indicatorsStatistics
Quant Q&A

The document explains how to search academic work on strategies that exploit knowledge of clustered orders. It distinguishes stop orders, which are not publicly displayed, from visible limit orders in the order book. For visible liquidity and imbalances, it…

Market microstructureHigh-frequency tradingMean reversionExecution
Quant Q&A

The document proposes estimating equilibrium exchange rates across three traded asset pairs without simulating arbitrage trades through every order book. It formulates a constrained optimization that minimizes the volume-weighted squared deviations between…

ArbitrageMarket microstructureHigh-frequency tradingStatistics
Quant Q&A

The answer explains why published deep learning results in trading are relatively scarce and why performance depends on the market and available data. It argues that rich equity data, including news and company information, may support more complex models,…

Machine learningEquitiesFixed incomeHigh-frequency trading
Quant Q&A

The document challenges a claim that a high-frequency trading bot can detect a large cryptocurrency order, infer its hidden maximum price, buy available coins first, and resell them at that limit. The answers explain that a marketable order generally…

CryptoHigh-frequency tradingMarket microstructureExecution
Quant Q&A

The discussion distinguishes short holding periods from true high-frequency trading. It describes HFT as requiring rapid market-data processing and order execution, often on microsecond timescales, while commenters report that Interactive Brokers’ API…

High-frequency tradingExecutionMarket microstructureEquities
Quant Q&A

The document discusses a three-class LSTM model for predicting financial trends from three time series. The question compares reported accuracy in a cited study with a lower result from an initial implementation and asks about model choices. The response…

Machine learningForexHigh-frequency tradingBacktesting
Quant Q&A

The document addresses a measurement problem for high-frequency trading: a return-based Sharpe ratio can be hard to define when the amount of capital deployed is unclear. The question considers whether posted margin can serve as the capital base or whether a…

High-frequency tradingStatisticsRisk management
Quant Q&A

The document asks how to classify the direction of option trades using tick-level trade and quote data. The proposed workflow is to align trade records with contemporaneous call and put quote panels by option symbol and timestamp, then compare each trade…

OptionsMarket microstructureHigh-frequency tradingVolatility
Quant Q&A

The document offers interview questions for candidates evaluating a quantitative trading group, especially when moving from academia into industry. Suggested topics include the markets traded, how research ideas become production models, constraints on…

High-frequency tradingRisk managementMachine learning
Quant Q&A

The document considers vendors for global equity trade bars at intraday frequencies, with the goal of researching short-horizon market patterns and using live data to trade resulting strategies. It identifies historical coverage, a real-time feed, and access…

EquitiesHigh-frequency tradingMarket microstructureExecution
Quant Q&A

The document points readers seeking current research on foreign-exchange market microstructure toward high-frequency trading studies. It argues that faster trading has changed how participants trade, how markets are organized, and how liquidity and price…

ForexHigh-frequency tradingMarket microstructure
Quant Q&A

The document explains “getting picked off” as an informal market microstructure term rather than a condition with a universal empirical definition. In high frequency trading and market making, it often refers to a faster, better informed participant trading…

Market microstructureHigh-frequency tradingMarket makingExecution
Quant Q&A

The document explains an expectation used in a limit-order-book model with an underlying stock-price process driven by Brownian motion. It focuses on how to transform an exponential utility expression involving the terminal price into a form that can be…

StatisticsMarket microstructureHigh-frequency trading
Quant Q&A

The document surveys the search for public measurements of electronic FX liquidity-provider response times, especially the far tail of last-look hold-time distributions during volatility spikes. It describes existing sources as incomplete: an older TCA study…

ForexMarket microstructureStatisticsHigh-frequency trading
Quant Q&A

The document compares options for asynchronous, non-blocking TCP and UDP networking in C++, framed around low-latency and real-time development. It notes that standard networking support was expected in C++17 and presents Boost as a way to abstract…

High-frequency tradingExecutionMarket microstructure
Quant Q&A

The document explains the microprice, a weighted average of the best bid and ask that gives greater influence to the side with less displayed volume. With more size at the bid, the resulting estimate moves above the ordinary midpoint. The discussion…

Market microstructureHigh-frequency tradingStatistics