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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
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 documents

TqSdk

The strategy models a refining spread using crude oil, fuel oil, and a third petroleum product in a 3:2:1 weighting. It calculates the spread as the weighted value of the two product legs minus the weighted crude leg, then compares the current spread with…

FuturesCommoditiesMean reversionArbitrage
TqSdk

This script describes a three-leg futures strategy that treats hog value minus weighted corn and soybean meal costs as a proxy for livestock feeding profitability. It estimates the spread’s mean and standard deviation from daily bars, calculates a z-score,…

FuturesCommoditiesMean reversionArbitrage
TqSdk

This futures strategy tracks the crush spread formed from soybean, soybean meal, and soybean oil contracts. It weights the three contract prices using an approximate processing ratio, computes the spread as the combined meal and oil value less the soybean…

FuturesCommoditiesMean reversionArbitrage
TqSdk

This documentation page indexes a sequence of option-use examples for a trading SDK. The topics move from retrieving live option quotes and screening contracts to classifying options as in the money, at the money, or out of the money. Further examples cover…

OptionsDerivatives pricingVolatilityArbitrage
TqSdk

This page is an index of complete strategy examples intended as starting points for adaptation in TqSdk. It groups examples into classic strategies, trend approaches, arbitrage, mean reversion, and algorithmic execution. Named examples include dual moving…

FuturesTrend followingArbitrageMean reversion