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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

10 documents

vn.py community

This event outline describes a quantitative study of option spread strategies, with a focus on gold options. Topics include straddles and strangles, bull and bear spreads, butterfly spreads, and put-call parity. It proposes examining the structure of these…

OptionsCommoditiesBacktestingVolatility
vn.py community

This Chinese research summary examines whether intraday data can support sector rotation signals, focusing on realized skewness and the share of volatility attributable to downside moves. It describes constructing industry level factors inspired by high…

China marketsEquitiesHigh-frequency tradingVolatility
vn.py community

The forum post addresses why the Average True Range calculated in VeighNa may differ substantially from the value shown in TradingView. It proposes checking several potential causes: differences in the ATR formula or smoothing method, discrepancies in the…

Technical indicatorsVolatilityStatistics
vn.py community

A VeighNa community exchange distinguishes the roles of two option modules in version 3.9.3. It describes the open-source OptionMaster as intended for semi-automatic volatility trading, while the Elite edition's OptionStrategy module is designed for fully…

OptionsVolatility
vn.py community

This forum post discusses a multi-timeframe CuatroStrategy implementation. Its five-minute handler updates a bar manager, waits for both five- and fifteen-minute data managers to initialize, then uses RSI and Bollinger Bands to place stop entry orders in the…

EquitiesTechnical indicatorsTrend followingVolatility
vn.py community

This article outlines the engineering challenges of researching and backtesting systematic options strategies. Because listed contracts change over time, a historical test needs an accurate record of which contracts were available on each date. The described…

OptionsBacktestingVolatilityExecution
vn.py community

This event outline introduces options volatility trading through pricing theory, portfolio profit and loss, and the role of delta hedging. It distinguishes historical volatility, implied volatility as reflected in option time value, and realized volatility…

OptionsVolatilityDerivatives pricingRisk management
vn.py community

A brief Chinese-language forum exchange addresses how to obtain real-time VIX data when a trading interface does not provide it. The questioner says the strategy requires live VIX values and asks about manually subscribing through a data service. A…

VolatilityOptionsExecution
vn.py community

This short example demonstrates adding three technical-analysis series to closing-price data: a linear regression value over a 14-period window, a time-series forecast over the same window, and a standard deviation over five periods. It also shows plotting…

Technical indicatorsVolatilityStatistics
vn.py community

A forum post reports a numerical problem when calculating implied volatility for deep out-of-the-money December put options on a ChiNext ETF. The author says the issue appeared while using an option pricing module for European stock options and processing a…

OptionsDerivatives pricingVolatilityStatistics