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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 discusses what mathematical preparation high-frequency trading may require. One answer emphasizes applied tools such as linear algebra, statistics, time-series analysis, optimization, and sometimes machine learning, while noting that practical…

High-frequency tradingStatisticsMachine learningMarket microstructure
Quant Q&A

The document explains how to build a simplified exchange execution simulator for backtesting. It recommends using historical order book snapshots or updates to estimate fills: a market order consumes available depth until its requested quantity is filled,…

ExecutionMarket microstructureBacktestingEquities
Quant Q&A

The document asks whether VWAP and TWAP can be combined into a more general benchmark, suggesting an exponentially decayed volume-weighted price as one possible construction. The answer reframes the problem: TWAP can be viewed as VWAP after changing the time…

ExecutionMarket microstructureStatistics
Quant Q&A

The document describes a strategy using 30-second bars on E-mini S&P 500 futures that performed well in backtests and walk-forward tests but lost in live simulation because small execution-price differences erased its edge. The question asks whether…

FuturesExecutionMarket microstructureBacktesting
Quant Q&A

The document examines an apparent mean-reverting basket built from several foreign-exchange rates. The proposed process fits a linear regression to estimate hedge ratios, forms a spread, then applies an augmented Dickey–Fuller test. The reported significance…

ForexPairs tradingMean reversionBacktesting
Quant Q&A

The document raises a terminology question about liquidity rebates: whether they go to any trader placing a limit order or specifically to a market maker. It contrasts a general description of limit-order traders as liquidity providers with readings that…

Market microstructureExecutionMarket making
Quant Q&A

The document answers whether a trader can obtain a low-cost, raw NASDAQ TotalView-ITCH real-time feed. Its response says that a basic single-port feed without redistribution rights costs more than the stated budget, while historical data also carries a…

EquitiesMarket microstructureExecutionUS markets
Quant Q&A

This answer distinguishes designing execution methods from monitoring individual trades. It argues that quants can analyze strategies, test them, and work with programmers to implement execution algorithms, while traders or managers typically oversee live…

High-frequency tradingExecutionMarket microstructureRisk management
Quant Q&A

The document introduces tick imbalance bars, which group market ticks until the cumulative signed tick count crosses a threshold based on its expected magnitude. Tick direction is assigned by the tick rule: price upticks are buys, downticks are sells, and…

Market microstructureExecutionStatistics
Quant Q&A

The discussion explains possible routes to real-time forex data over FIX and why access may be difficult to obtain cheaply. It describes FX as an interbank market where a firm typically connects through chosen banks, while noting that banks may offer FIX for…

ForexExecutionMarket microstructure
Quant Q&A

The document describes a workflow for obtaining stock price data, turning timestamped records into a Pandas DataFrame, and saving the results. The intended application is to compare American depositary receipts with their ordinary-share counterparts,…

EquitiesForexHigh-frequency tradingExecution
Quant Q&A

The document examines a claim about how much an insider’s private information is reflected in price in Kyle’s single-auction model. It lays out the normal-value setup, the insider’s order rule, noise trading, and the market maker’s price rule, then questions…

Market microstructureStatisticsExecution
Quant Q&A

The question defines market impact for a market order as the price difference between the first and last shares executed. It observes that, if the order book were static, the visible sell-side depth would indicate the last price reached by a buy order. The…

ExecutionMarket microstructureStatistics
Quant Q&A

The document describes a cross-exchange futures pairs strategy involving products whose prices are expected to remain close. The trader enters one leg with a limit order and the other with a market order, aiming for price neutrality. The strategy’s signal is…

FuturesPairs tradingMean reversionMarket making
Quant Q&A

The document explains how to take a short position in a synthetic instrument that can have a negative price, using spreads as examples. It lists calendar spreads, butterflies, and double butterflies, then gives a January–February calendar spread: the long…

FuturesDerivatives pricingExecution
Quant Q&A

The question asks whether limited capital can produce a larger payoff by requiring several stocks to meet a return threshold, rather than holding equal investments in each. The response proposes a different approach: if expected price moves occur at…

EquitiesEvent-drivenExecution
Quant Q&A

The document describes a calibration problem in the Guéant–Lehalle–Fernandez-Tapia market-making model. The author estimates bid- and ask-side order-arrival intensities using the last traded price as a reference, updating it at short intervals, and separates…

Market makingMarket microstructureVolatilityStatistics
Quant Q&A

The document explains that the signed difference between an order’s average execution price and its arrival mid-price is usually treated as implementation shortfall. It presents an approximate model with a spread-related term and a market-impact term that…

ExecutionMarket microstructureVolatilityStatistics
Quant Q&A

The document describes pinging: sending small orders into a market to infer whether larger resting orders may be present. A quick fill is presented as a possible signal that deeper liquidity is behind the displayed or encountered order. The original question…

High-frequency tradingMarket microstructureExecution
Quant Q&A

The document discusses fitting the arrival-rate parameters in the Avellaneda–Stoikov market-making model when observed fill rates do not appear exponential in spread. The author compares empirical spread buckets with candidate curves, including a…

Market makingHigh-frequency tradingMarket microstructureStatistics
Quant Q&A

The document discusses whether FIX Simple Binary Encoding can reduce the development effort or bandwidth costs of high-frequency trading connections compared with proprietary exchange protocols. One response stresses that firms generally must use the…

High-frequency tradingExecutionMarket microstructure
Quant Q&A

The discussion explains why a high-frequency backtest’s latency assumption should reflect both message timing and the strategy’s sensitivity to event ordering. For spread-crossing or arbitrage strategies, it suggests modeling latency as variable, potentially…

High-frequency tradingBacktestingExecutionMarket microstructure
Quant Q&A

The discussion asks whether trade and order-book data can reveal when a large order was split into smaller executions. It distinguishes identifying one participant’s activity from grouping executions caused by a single marketable order. Order identifiers do…

Market microstructureExecutionHigh-frequency tradingEquities
Quant Q&A

This discussion collects risk management topics relevant to automated trading, with particular attention to high-frequency systems. It names drawdowns, runs of losses, empirical loss distributions, confidence intervals, value at risk, slippage, liquidity,…

Risk managementHigh-frequency tradingExecutionMarket microstructure