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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

195 documents

Robot Wealth

This article describes techniques for reducing overfitting in feed-forward neural networks used to forecast market direction. It outlines L1 and L2 regularization, which penalize large model weights, and dropout, which randomly disables units during…

Machine learningForexBacktestingRisk management
Robot Wealth

The article explains why backtests are needed to assess trading rules and why simulated performance is only a guide to live results. A useful simulation should reflect the intended market and broker conditions, use data at an appropriate level of detail, and…

BacktestingStatisticsRisk management
Robot Wealth

This article frames alpha as an opportunity created when traders transact at disadvantageous prices, and emphasizes understanding why they do so. Reasons include limited information or behavioral biases, binding risk or mandate constraints, and non-profit…

Event-drivenPortfolio constructionRisk management
Robot Wealth

This essay argues that traders should begin with practical problems and seek reading when they encounter a knowledge gap, rather than treating book consumption as a substitute for research or trading. It recommends focusing on developing an edge and managing…

StatisticsDerivatives pricingMarket microstructure
Robot Wealth

This tutorial introduces dplyr workflows for manipulating daily stock-price observations. It explains how to filter rows for one or several tickers, reorder observations by date or trading volume, and select specific columns. It also demonstrates chaining…

EquitiesStatistics
Robot Wealth

The article introduces rsims, an R package for fast portfolio backtests that emphasizes translating target weights into trades while accounting for costs and constraints. It describes a threshold rule: trade toward a target only when the current weight moves…

BacktestingExecutionPortfolio constructionRisk management
Robot Wealth

The article outlines three practical sources of trading hypotheses. Traders can learn from other market participants who appear to have profitable approaches, while adapting ideas to smaller niches or constraints that may not suit large asset managers. It…

Multi-assetCryptoStatistics
Robot Wealth

The article explains options as expiring bets whose fair value is the probability-weighted payoff. It illustrates the idea with a soccer match modeled as separate Poisson goal processes for the home and away teams. Expected goals imply probabilities for home…

OptionsDerivatives pricingStatistics
Robot Wealth

Tesla’s addition to the S&P 500 creates predictable index-tracking demand, but the article argues that this flow may already be reflected in prices by the time a trade seems obvious. It reviews research on index additions: earlier work found most excess…

EquitiesEvent-drivenUS marketsMarket microstructure
Robot Wealth

The document argues that binary rules, such as taking a position based only on whether price is above a moving average, discard information and conceal how signal strength relates to future returns. For a crypto trend example, it replaces the on/off…

CryptoTrend followingTechnical indicatorsStatistics
Robot Wealth

The document explores whether currency prices can form stationary spreads suitable for mean-reversion analysis. It estimates a two-currency spread using ordinary least squares, then tests the residual with an augmented Dickey-Fuller procedure. It also…

ForexMean reversionPairs tradingStatistics
Robot Wealth

A no-trade region places a buffer around a strategy’s target position. The portfolio is left alone while its current holding remains inside the buffer, and a trade is made only after it moves beyond the boundary. With minimum commissions, the example rule…

ExecutionPortfolio constructionBacktestingRisk management
Robot Wealth

Rolling estimates such as 30-day volatility share most of their underlying observations from one day to the next. A naive comparison of adjacent estimates can therefore appear highly persistent even when much of that relationship is mechanically caused by…

StatisticsVolatilityBacktesting
Robot Wealth

This article curates books, papers, and course materials that the author found useful for learning algorithmic and quantitative trading. The recommendations are grouped into practical trading, foundational statistics and time series, machine learning,…

StatisticsMachine learningBacktestingRisk management
Robot Wealth

This course page presents a framework for systematic trading centered on identifying a plausible edge before building and evaluating a strategy. It argues that a strong backtest alone does not establish that a strategy is sound, and recommends formulating a…

StatisticsBacktestingRisk managementEquities
Robot Wealth

This article uses simulated cryptocurrency price paths to explore how often a leveraged trend strategy might need rebalancing to manage drawdowns. The author builds a geometric Brownian motion simulator with autocorrelated returns and random jumps, using a…

CryptoTrend followingRisk managementPosition sizing
Robot Wealth

The document explains how UVXY’s daily leverage target and maturity maintenance lead to recurring portfolio rebalancing, and uses spreadsheet models to examine two trades: shorting UVXY with periodic rebalancing, and shorting a basket of UVXY and an inverse…

VolatilityPosition sizingRisk managementBacktesting
Robot Wealth

The document outlines an experiment for studying how training-window length and predicted class-probability thresholds affect a financial prediction strategy. It constructs directional labels from returns and uses lagged returns and volatility measures as…

Machine learningForexStatisticsBacktesting
Robot Wealth

The document offers practical guidelines for trading equity options, emphasizing that the many contracts available on one underlying tend to have thinner liquidity and wider spreads than the underlying stock. It recommends using options when the trading…

OptionsExecutionMarket microstructureVolatility
Robot Wealth

The document presents statistical arbitrage as a broader portfolio problem than trading matched pairs. It ranks assets by expected cheapness or expensiveness, then builds long and short positions intended to capture relative value convergence while…

ArbitrageMean reversionPortfolio constructionRisk management
Robot Wealth

This article advises traders with small accounts to begin with comparatively simple, forgiving strategies that support consistent process-building and skill development. It cautions that niche, high-capacity-constrained opportunities may offer attractive…

Multi-assetCarryRisk managementPortfolio construction
Robot Wealth

This essay argues that systematic traders should begin with market observation and an explanation of why a possible edge exists, rather than searching broadly across indicators and parameters for a profitable backtest. Repeated experimentation can produce…

BacktestingStatisticsMachine learning
Robot Wealth

This analysis revisits whether SPY’s returns accrue mainly overnight or during regular trading hours. It calculates intraday returns from each session’s open to close and overnight returns from the prior close to the next open, then compares their cumulative…

EquitiesUS marketsStatisticsRisk management
Robot Wealth

This tutorial combines a Kalman filter written in R with a simple pairs trading system in Zorro. The filter updates a hedge ratio as new prices arrive, estimates the spread prediction error, and calculates its uncertainty. The trading logic uses that…

Pairs tradingMean reversionStatisticsBacktesting