Skip to content

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

5,922 documents

Robot Wealth

The article divides solo trading work into four roles: researching whether a market effect is real, engineering a tradable strategy, building a portfolio from strategies, and operating the resulting system. Each role calls for a different focus, from…

BacktestingPortfolio constructionExecutionRisk management
QuantStart

This article compares simple systematic strategies, such as indicator signals on liquid markets, with more advanced approaches that may use niche instruments, statistical analysis, and explicit portfolio construction. It frames the choice around an…

StatisticsBacktestingRisk managementPortfolio construction
Systematic trading blog (Rob Carver)

This opening installment considers how a trader with limited capital might allocate across futures when contracts cannot be traded fractionally. The author frames the challenge as a portfolio optimization problem: a small account cannot spread capital over…

FuturesPortfolio constructionPosition sizingRisk management
Systematic trading blog (Rob Carver)

The document explores whether interest-rate conditions can help tailor CTA allocations across fixed-income futures and trading rules. It proposes meta-prediction: group historical strategy returns by a regime variable, then compare performance across those…

FuturesFixed incomeMomentumCarry
Galaxy Research

The report reviews crypto and blockchain venture investment and fundraising in Q2 2025. It tracks capital and deal counts by investment stage, company category, geography, and founding year, and compares venture activity with bitcoin prices. It reports…

CryptoStatisticsSentimentUS markets
Deribit Insights

This market commentary argues that Bitcoin's rally from 25,000 to 38,000 was largely driven by expectations of US spot ETF approval. The author expected another attempt to break above 38,000, but suggested using strength to prepare for sideways or mildly…

CryptoSpot marketsEvent-drivenPortfolio construction
Cryptohopper blog

This guide presents ten broad principles for participating in cryptocurrency markets. It emphasizes limiting exposure to money an investor can afford to lose, building positions through scheduled dollar-cost averaging, researching token utility and project…

CryptoRisk managementPosition sizingPortfolio construction
vn.py

This guide explains how to run multi-contract strategies in VeighNa, from loading the module and creating strategy instances to initializing, starting, stopping, editing, and removing them. It describes the distinction between initialization and live…

FuturesPortfolio constructionExecutionTechnical indicators
Amberdata research

The report assesses Bitcoin and Ethereum performance in 2025 through monthly returns, six market regimes, drawdowns, rolling volatility, and BTC–ETH correlation. It argues that annual returns conceal large differences across regimes: Bitcoin finished the…

CryptoVolatilityRisk managementPortfolio construction
pysystemtrade

This system stage combines already scaled and capped forecasts from multiple trading rules for an instrument. It aligns rule weights with available forecasts, adjusts weights when forecasts are missing, carries weights forward across dates, smooths them with…

Portfolio constructionRisk management
Lumibot

This strategy uses a three-agent workflow to build a concentrated portfolio from a fixed list of large-company stocks. A research agent ranks up to five candidates for predictable operations, cash generation, and attractive pricing. A separate short-seller…

EquitiesPortfolio constructionRisk management
FinRL

This script describes an evaluation workflow for trained stock trading agents based on an ensemble reinforcement learning study. It loads trained A2C, DDPG, PPO, TD3, and SAC models, applies them to a stock trading environment, and records account values and…

EquitiesMachine learningBacktestingPortfolio construction
Awesome Systematic Trading

The document describes a monthly strategy that combines a portfolio of smart factors with a broad US equity market proxy. It uses five factor return series based on large US stocks. For each factor, it measures one-month and twelve-month momentum, ranks the…

EquitiesMomentumFactor investingPortfolio construction
Quant Q&A

The discussion explains why the choice between simple and logarithmic returns depends on the calculation. In a portfolio with fixed asset weights over a period, the portfolio’s simple return is the weighted sum of its assets’ simple returns. This…

Portfolio constructionStatisticsRisk management
Quant Q&A

The document poses a portfolio-combination question: how to estimate the Sharpe ratio of several strategies when only each strategy's expected return, standard deviation, Sharpe ratio, and trade count are available. It highlights that averaging standard…

StatisticsPortfolio construction
Quant Q&A

The document examines what the coefficient in a log-price cointegrating relation means for a pairs trade. It contrasts interpreting the coefficient as a share ratio with interpreting it as a ratio of market values, and explains why those interpretations lead…

EquitiesPairs tradingPortfolio constructionPosition sizing
Quant Q&A

The document explains how broker margin rules constrain portfolio weights, especially for dollar-neutral equity portfolios. It relates gross exposure—the sum of the absolute portfolio weights—to the capital required to carry long and short positions. For a…

EquitiesPortfolio constructionRisk managementPosition sizing
arXiv papers

The document questions the usual assumption that all assets share one continuous calendar clock. Markets instead operate asynchronously: order flow arrives through events, and the time between events can be random. It compares event-time, renewal,…

Market microstructureStatisticsRisk managementPortfolio construction