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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
Quantpedia
86 documents
TqSdk
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
Quantopian lectures
45 documents
Binance API docs
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 discussion investigates why Yahoo Finance showed a daily trading-volume figure that did not match the sum of its hourly figures for a Japanese-listed stock. The explanation is that the daily number represented volume on the primary exchange, while the…

EquitiesMarket microstructureExecution
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 discussion considers how to choose when to buy a required quantity of an asset whose price follows an Ornstein–Uhlenbeck mean-reverting process, given a finite deadline. One response frames this as an execution problem: wait for prices to move favorably…

Mean reversionExecutionStatisticsRisk management
Quant Q&A

The document explains how to construct periodic open, high, low, and close values from a stream of market prices. Its central rule is to choose one price series first—such as bids, asks, or last trades—and compute the bar from that series alone. For…

Market microstructureExecutionStatistics
Quant Q&A

The document examines whether a completed trade can have positive market impact. Its example describes an illiquid market where the displayed price is 100, while a buyer has hidden willingness to pay up to 105. A seller offers at 102, the buyer trades, and…

Market microstructureExecution
Quant Q&A

For puts with the same underlying and expiry, the displayed bid and ask quotes generally increase as strike prices rise. The question arose because some last-traded prices appeared to violate that pattern, leading the answers to distinguish current quotes…

OptionsDerivatives pricingMarket microstructureExecution
Quant Q&A

The document explains how a trading system can update position quantity, cost basis, average price, and realized and unrealized profit and loss incrementally as fills arrive. Under average-cost accounting, the update uses the prior position and cost, plus…

ExecutionRisk managementPosition sizing
Quant Q&A

The note describes two uses of algorithms by bond market makers. A system can maintain required bid and ask quotes across bonds that a desk may not actively want to trade, adjusting them as the best market quotes move. It can also generate indicative prices…

Fixed incomeMarket makingExecution
Quant Q&A

The discussion frames hedge selection as choosing weights on available instruments to reduce the combined portfolio’s PnL variance. A simple example shows that when matching instruments exist, the method should recover offsetting positions; with imperfect…

Machine learningRisk managementPortfolio constructionExecution
Quant Q&A

The discussion asks how to combine robust optimization, fixed transaction costs, and discrete portfolio constraints such as limits on the number of selected assets. It points to work on robust second-order cone formulations and a heuristic for portfolio…

Portfolio constructionRisk managementExecutionMarket microstructure
Quant Q&A

The document considers a funded equity collar for a shareholder seeking cash against an existing stock position. The proposed structure combines a margin loan secured by pledged shares, a purchased put, and a written call with a nearby strike. The bank would…

EquitiesOptionsRisk managementExecution
Quant Q&A

The note explains why fractional shares offered by brokers do not fully replace stock splits as a way to adjust a share’s trading price. On exchanges, orders generally trade in whole shares, while brokers can aggregate customers’ fractional orders to execute…

EquitiesMarket microstructureExecution
Quant Q&A

The document surveys commercial suites that combine market data, backtesting, event processing, and automated trading. It asks about leading vendors, practical tradeoffs, integration costs, customization, and typical users, but provides only a partial…

BacktestingExecutionMarket microstructure
Quant Q&A

The document compares the apparent cost of commission-free brokerage apps with flat-fee brokers. It explains that a zero commission does not make a trade costless: execution at a less favorable price can create an implicit cost through the bid–ask spread or…

EquitiesExecutionMarket microstructureUS markets
Quant Q&A

The discussion considers whether an investor can hedge an intraday position in a financial-sector fund such as XLF with an inverse leveraged fund such as FAZ. It explains that a nominal three-times inverse exposure could provide a close intraday offset if…

EquitiesRisk managementExecutionUS markets
Quant Q&A

The document explains how an incoming order that is large relative to the visible book interacts with resting orders. A market order generally consumes available liquidity across price levels until its requested size is filled or no executable liquidity…

Market microstructureExecution
Quant Q&A

The document surveys ways to measure market liquidity and explains why trading volume alone can be an incomplete proxy. Quote-based measures include the bid-ask spread, top-of-book size, and depth across the order book or venues; spreads indicate trading…

Market microstructureExecutionStatisticsRisk management
Quant Q&A

This discussion considers whether investors’ month-end trades tracking the Bloomberg Barclays Agency MBS Index can be anticipated. It explains that index replication in agency mortgage-backed securities often uses TBA contracts rather than the underlying…

Fixed incomeMarket microstructureExecution
Quant Q&A

The document addresses which option maturities to use when replicating a variance swap whose observation period runs from the next day through a later end date. It says the option strip used for static replication should expire on the same date as the…

OptionsVolatilityDerivatives pricingExecution
Quant Q&A

The document explains how to infer the bid and ask for the reciprocal of a foreign exchange quote. Given a bid and ask for AUD/USD, the implied USD/AUD bid is the reciprocal of the original ask, while the implied USD/AUD ask is the reciprocal of the original…

ForexExecutionMarket microstructure
Quant Q&A

The document explains how exchanges form prices from resting limit orders and incoming orders. A matching engine executes marketable orders against the best available quotes, while the best bid is the highest buying price and the best ask is the lowest…

Market microstructureExecutionEquitiesForex
Quant Q&A

The document explains what happens when a trader sells a futures contract after previously buying one. It clarifies that a closing sale offsets the trader’s existing long position, leaving the trader with no open position in that contract. The exchange…

FuturesExecution
Quant Q&A

The discussion concerns differences between futures option quotes shown in a broker's trading platform and those delivered through its Excel interface. A user reports that the displayed ES quote can diverge from the API feed and then align again after…

FuturesOptionsExecutionMarket microstructure