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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

6 documents

Quantpedia

The document describes a monthly cross-sectional strategy across 22 commodity futures. It calculates each contract’s skewness over the prior 12 months, buys three commodities with the lowest skewness, and shorts three with the highest, using equal weights…

CommoditiesFuturesFactor investingStatistics
Quantpedia

The document describes a monthly market-timing approach that uses crude oil returns to forecast equity returns. It estimates a regression of equity returns on monthly oil returns, updates the model each month with the latest observation, and compares the…

CommoditiesEquitiesStatistics
Quantpedia

The document describes a cross-sectional commodity futures strategy based on return asymmetry. It defines an IE measure as the difference between the counts of unusually large positive and negative daily returns, using a rolling 260-day window. At each month…

CommoditiesFuturesFactor investingVolatility
Quantpedia

The document describes a monthly long-short strategy that ranks commodity futures by their past 12-month performance, buys the strongest quintile, and sells the weakest. The cited research finds profitable continuation strategies and reports an average…

CommoditiesFuturesMomentumFactor investing
Quantpedia

The document describes a futures spread strategy based on the price difference between WTI and Brent crude oil. It explains that the oils differ in composition and production and transport characteristics, while temporary shocks may cause their price spread…

FuturesCommoditiesMean reversionPairs trading
Quantpedia

This document explains a cross-sectional commodity carry strategy that ranks futures by roll returns, buys the strongest contracts, and shorts the weakest. Its simple monthly example equally weights the top and bottom quintiles and holds the positions for…

CommoditiesFuturesCarryFactor investing