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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

195 documents

Robot Wealth

This short reflection argues that machine-learning and statistical methods are tools for analysis, not trading edges by themselves. It offers questions for assessing whether a discovered effect has a plausible structural, economic, financial, or behavioral…

StatisticsMachine learningRisk managementPosition sizing
Robot Wealth

The article explains how to express trading signals as expected returns, giving a common scale for comparing features and combining them with risk estimates and trading costs. Its example uses Binance perpetual futures and considers carry, short-term…

CryptoPerpetual futuresCarryMomentum
Robot Wealth

This review describes Zorro as a platform for implementing, testing, optimizing, and executing systematic strategies. It argues that researchers can use an established framework to iterate on hypotheses, adapt existing strategies to new instruments, and…

BacktestingExecutionStatisticsMachine learning
Robot Wealth

This article outlines a way to assess whether a strategy’s backtest results stand out from outcomes generated by chance. It proposes constructing randomized strategies that match the original strategy’s simulation period, trade count, direction, and average…

BacktestingStatisticsForex
Robot Wealth

This course overview describes a research framework for systematic trading, emphasizing that a profitable backtest does not by itself establish a durable strategy. It recommends understanding market participants and the structural reasons an edge might…

BacktestingStatisticsRisk managementMulti-asset
Robot Wealth

The article argues that a trading business needs a plausible, explainable source of returns rather than relying on discretionary chart reading or feeding features into a machine-learning model without a clear rationale. It frames durable edges as…

Market makingCarryFuturesCrypto
Robot Wealth

This review surveys the research topics covered in Euan Sinclair’s book on positional option trading. It highlights potential sources of returns involving the implied volatility forward curve, cross-sectional equity option returns linked to fundamental…

OptionsVolatilityEvent-drivenFactor investing
Robot Wealth

The article explains how sample averages tend to approach their underlying population averages as observations accumulate. A restaurant-rating simulation illustrates that small samples can vary widely, while larger groups of reviews give a more stable…

StatisticsBacktestingRisk management
Robot Wealth

This article introduces a conversation with Kris Abdelmessih, drawing on his experience as an options market maker in New York trading pits and later building a commodity-options business for a hedge fund. It previews discussion of differences between…

OptionsMarket microstructureDerivatives pricingBacktesting
Robot Wealth

The article outlines a process for developing trading ideas that considers both potential returns and practical constraints. It recommends browsing academic research for useful observations, learning from experienced traders’ anecdotes, revisiting…

StatisticsOptionsMarket microstructureBacktesting
Robot Wealth

The article presents two R approaches for simulating geometric Brownian motion price paths. A nested-loop version generates one random shock at a time for each path and time step. A vectorized version draws the shocks in a matrix, applies the per-step growth…

StatisticsBacktestingOptionsDerivatives pricing
Robot Wealth

The article examines momentum as a way to time exposure to a diversified risk-premia strategy. It describes measuring each asset’s trailing six-month return, ranking assets, and rotating into the top four with weights inversely related to their volatility…

MomentumFactor investingPortfolio constructionRisk management
Robot Wealth

This article presents a machine learning workflow for exploring candidate predictors in a simple trading system. It discusses data mining bias, feature construction, preprocessing, removing correlated inputs, and several selection methods, including maximal…

Machine learningStatisticsBacktestingTechnical indicators
Robot Wealth

This essay argues that systematic traders should investigate a market effect before building elaborate backtests, optimized rules, or machine learning systems. It recommends forming small, falsifiable hypotheses and using direct, data-efficient analysis such…

StatisticsBacktestingPortfolio constructionRisk management
Robot Wealth

The document describes cross-sectional signals for ranking equity options by potential volatility mispricing. It outlines value, company size, idiosyncratic volatility, beta convexity, implied volatility term structure, the implied versus realized volatility…

OptionsEquitiesVolatilityFactor investing
Robot Wealth

This introductory guide explains an algorithmic trading system as a chain of connected tasks: obtaining market data, analyzing it, checking trade conditions, executing orders, managing risk, and maintaining portfolios, records, and post-trade analysis. It…

ExecutionRisk managementMarket microstructureBacktesting
Robot Wealth

This short essay argues that independent traders should learn from the ideas behind institutional strategies without copying their implementations. It points to statistical arbitrage opportunities that can arise when supply and demand are uneven or when…

ArbitragePairs tradingFuturesCrypto
Robot Wealth

The article describes a three-part approach to equity statistical arbitrage for independent traders. First, rank related stock pairs using measures of historical mean-reversion returns and consistency of convergence, then retain economically sensible…

EquitiesArbitragePairs tradingMean reversion
Robot Wealth

This article frames trading as the management of positions rather than a sequence of individually realized trades. Buying and selling exchange cash for assets; profit and loss arise as the value of the held exposure changes. The practical process is to…

Portfolio constructionRisk managementExecution
Robot Wealth

The article discusses two proposed crypto trading signals. The retail-flow factor uses order-book data to distinguish retail from institutional activity and treats unusually strong retail participation as a contrarian signal. The author reports a near-linear…

CryptoSentimentCarryPerpetual futures
Robot Wealth

This article introduces several ways to assess whether an exchange-rate series may suit a mean-reversion strategy. It explains the Augmented Dickey-Fuller test as a check for a unit root, the Hurst exponent as an indicator of trending or reverting behavior,…

ForexMean reversionStatisticsTechnical indicators
Robot Wealth

The article argues that a trading edge can come from understanding what other participants believe, what motivates them and how their behavior affects prices. Instead of accepting familiar market claims as causal truths, it recommends asking whether the…

StatisticsSentimentRisk management
Robot Wealth

The article introduces expected value as a way to assess uncertain bets. Its simple dice-game example asks a risk-neutral player to list possible outcomes, assign each a probability and payout, multiply probability by payout, and sum the results. That…

StatisticsDerivatives pricingRisk managementOptions
Robot Wealth

This introduction defines an option as a contract giving its holder a right, without an obligation, to trade an underlying asset at a specified strike price by an expiration date. It distinguishes calls, which grant the right to buy, from puts, which grant…

OptionsDerivatives pricingEquitiesFutures