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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

16,761 documents

Quant Q&A

The discussion identifies potential benchmarks for US corporate and Treasury bond strategies over a historical daily sample. It distinguishes an investable exchange-traded fund from the index it tracks: the fund’s price history begins later, while the…

Fixed incomeBacktestingUS markets
Quant Q&A

The document seeks a study comparing an idealized market-timing strategy with buy-and-hold. The question describes a rule that buys after a market trough between record highs and sells at a new high, with the concern that long periods out of the market may…

BacktestingEquities
Quant Q&A

The document presents a validation question for a machine-learning portfolio strategy evaluated out of time against a strong benchmark. Its custom rolling metric reflects portfolio value and additional state variables such as inventory and time. The observed…

Machine learningBacktestingStatisticsPortfolio construction
Quant Q&A

The document clarifies how to obtain the stochastic differential for a process defined as the sum of an ordinary time integral and an Itô integral. Rather than differentiating with respect to the stochastic state or Brownian motion, it treats the integral…

StatisticsBacktesting
Quant Q&A

The document asks how to handle bonds that mature while backtesting a fixed-income portfolio strategy, particularly when trying to reproduce a published study. It focuses on how a maturing bond contributes to returns and how the portfolio should account for…

Fixed incomeBacktestingPortfolio construction
Quant Q&A

The discussion compares two ways to estimate annual return skewness and kurtosis from a long series of daily continuously compounded returns. One approach is to aggregate daily returns into annual returns and calculate the statistics from those annual…

StatisticsRisk managementBacktesting
Quant Q&A

The document raises a backtesting question: how to report annual performance for a strategy evaluated on hourly open, high, low, and close data. The author has code that replays different portions of the historical series and calculates total return and…

BacktestingStatisticsRisk management
Quant Q&A

The document explains when a European call price from a Heston model can be represented by a Black–Scholes implied volatility. It states that the Heston asset-price and variance processes do not generally have explicit pathwise solutions, though Fourier…

OptionsVolatilityDerivatives pricingBacktesting
Quant Q&A

The document explains why geometric Brownian motion parameters can be confusing: arithmetic returns and log returns are calculated differently, and the same distinction affects how a price process is modeled. A price path that falls and then recovers can…

StatisticsVolatilityBacktesting
Quant Q&A

The document discusses whether a stock backtest can assume execution at daily opening and closing prices. It describes market-on-open and market-on-close orders as ways to target auction prices, while noting that traders must submit orders before the final…

EquitiesBacktestingExecutionMarket microstructure
Quant Q&A

The document asks how to evaluate predictions of asset returns when matching the sign of each forecast to the realized return matters more than explaining return magnitude. It gives a small example where ordinary least squares has low explanatory power,…

StatisticsMachine learningBacktesting
Quant Q&A

The discussion compares factor-based portfolio construction with mean-variance optimization. Factor models can forecast expected returns and represent covariance risk; portfolio constraints can also control exposure to factors, sectors, or individual…

Portfolio constructionFactor investingRisk managementStatistics
Quant Q&A

The document investigates why an American call’s market ask price cannot be reconciled with an implied volatility calculation using RQuantLib, while Yahoo Finance reports a volatility estimate. The author compares the market quote with model prices and…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The document addresses how to represent short-sale constraints in a backtest. Its proposed control is to include a borrowing cost for short positions, since live shorting generally requires shares to be borrowed through a broker. The cost can be included in…

EquitiesBacktestingExecutionRisk management
Quant Q&A

The document defines a European barrier call whose payoff depends on the asset finishing above the strike and staying above a lower barrier at specified observation times. It asks how to estimate its discounted risk-neutral value by Monte Carlo simulation…

OptionsDerivatives pricingBacktestingStatistics
Quant Q&A

The document compares database options for storing large financial tick datasets and aggregating them into open, high, low, and close bars. It reports an initial test in which InfluxDB was slower than MySQL for one-minute bar creation on a dataset of around…

Market microstructureExecutionBacktestingStatistics
Quant Q&A

The document addresses whether the Sharpe ratio should use discrete returns or continuously compounded returns. Its answer distinguishes the context: discrete returns are customary for client reporting, while the choice generally has little impact in a…

StatisticsBacktestingPortfolio construction
Quant Q&A

The document asks how to compare long-only commodity futures roll strategies using historical contracts and ratio back-adjusted price series. The questioner adjusts earlier prices at each roll, then estimates returns from changes in adjusted prices while…

FuturesCommoditiesBacktestingExecution
Quant Q&A

The document evaluates a simple intraday rule: buy instruments at the open and sell when price rises by one tick. It explains that the rule is incomplete unless it specifies how to handle positions that never reach the target, including whether to hold them,…

ExecutionBacktestingRisk managementEquities
Quant Q&A

The document describes a planned empirical study of cross-sectional stock momentum using OSEAX constituents over a historical sample. Its proposed strategy ranks assets by past performance over a selected horizon, buys the strongest group, and shorts the…

EquitiesMomentumBacktesting
Quant Q&A

The document discusses how to design trading systems that use both historical market data and live feeds. One approach is to expose a common interface so strategies can reuse the same logic in both settings, reducing implementation differences. The accepted…

BacktestingExecutionMarket microstructureRisk management
Quant Q&A

The author describes an hourly forex classification pipeline using fractional differentiation, CUSUM event sampling, technical features, and XGBoost. Reported test accuracy rises substantially in some configurations, especially when labels are based on…

ForexMachine learningBacktestingStatistics
Quant Q&A

A beginner with programming and mathematics experience asks how to build a basic system for viewing market data and placing trades, with both simulated and live modes. The responses discuss broker access, demo and paper accounts, data costs, APIs, and…

ForexEquitiesExecutionBacktesting
Quant Q&A

The discussion surveys possible ways to obtain historical daily quotes across VIX option strikes and expirations. One response says reliable public data may be unavailable and cautions that analysis may also require the corresponding VIX futures history,…

OptionsVolatilityDerivatives pricingBacktesting