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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
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

12,303 documents

Amberdata research

The newsletter uses Bitcoin’s options market as a benchmark for judging whether Ether volatility is expensive. It considers macroeconomic conditions, Bitcoin’s recent trading range, realized volatility, and the probability of reaching a higher year-end…

CryptoOptionsVolatilityDerivatives pricing
ProRealCode

The document describes a trend indicator that combines a modified On-Balance Volume series with Supertrend levels and a volatility-based adjustment. OBV supplies the input used to make the trend calculation more responsive, while a volatility factor changes…

Technical indicatorsTrend followingVolatilityCrypto
Amberdata research

This weekly market commentary reviews Bitcoin and Ether derivatives through realized and implied volatility, volatility term structure, skew, and relative value. It reports realized volatility in the 40s while implied volatility declined toward it, reducing…

CryptoOptionsVolatilityDerivatives pricing
MQL5 code base

This short indicator description explains Bollinger Bands %B as a measure of where price sits relative to the upper band, middle line, and lower band. Values above one indicate price is beyond the upper band, while one marks the upper band itself. Values…

Technical indicatorsVolatility
BigQuant

This research summary compares a basic reversal factor based on roughly one month of returns with volume-weighted high-frequency and structured reversal factors. The structured version incorporates both momentum and reversal behavior in high-frequency data.…

EquitiesMean reversionMomentumFactor investing
Amberdata research

This overview compares how USDC, USDT, and DAI seek to maintain a dollar peg. It describes fiat reserves and issuer redemption for USDC and USDT, and over-collateralized crypto vaults and liquidation rules for DAI. The TerraUSD collapse illustrates the…

CryptoDeFiVolatility
MQL5 code base

This MetaTrader 5 expert advisor trades signals from the XBullsBearsEyes_Vol indicator. It enters when a bar closes after breaking an overbought or oversold level. The two signal levels are assigned separate magic numbers and position sizes, with the…

ForexVolatilityBreakoutPosition sizing
ProRealCode

The Relative Volatility Index (RVI) estimates whether volatility is associated with rising or falling prices. It calculates price standard deviation over a chosen period, assigns that volatility to an upward or downward component based on the close-to-close…

Technical indicatorsVolatilityTrend following
SuperMind

This Chinese A-share screening idea selects stocks with daily amplitude above 1%, excludes Beijing-listed shares, and requires a limit-up event within the prior 25 days. The document presents the rule as a way to focus on volatile stocks with recent strong…

EquitiesChina marketsVolatilityBreakout
SuperMind

The document proposes a Chinese equity screen combining a daily trading range above one percent, a closing price of 18.5 yuan, and a recent three-session limit-up pattern. It frames the price and streak as signs of market attention and short-term upward…

EquitiesChina marketsMomentumVolatility
ProRealCode

This indicator note describes the Sell Relative Strength Index, also called the sell gravitation index, attributed to Howard Wand and featured in a February 2019 TASC issue. For each bar in a configurable lookback, it divides the candle body’s open-to-close…

Technical indicatorsVolatilityRisk management
ProRealCode

This document presents a simplified implementation of the Jurik RSX indicator and states that it is equivalent to the original. The calculation applies repeated exponential smoothing stages to close-to-close price changes and to their absolute values, then…

Technical indicatorsMomentumVolatility
SuperMind

This post describes a Chinese equity screen that selects stocks with daily amplitude above 1, codes beginning with 60, market capitalization below 10 billion yuan, and positive net profit. It also suggests sorting by a five-day moving average. The author…

EquitiesChina marketsVolatilityFactor investing
Amberdata research

This report installment reviews Bitcoin ownership and activity through on-chain measures, including the Gini coefficient, address and supply distributions, coin liveliness, HODL measures, UTXO age buckets, miner flows, and ETF allocations. It describes a…

CryptoOn-chain dataStatisticsVolatility
SuperMind

This post presents a short-term Chinese stock screen based on a daily price range of at least 1%, relative volume between 1.5 and 6, and exclusion of stocks that hit the upper price limit the previous day. Its stated rationale is to find actively traded…

EquitiesChina marketsTechnical indicatorsVolatility
BigQuant

This post describes a research exercise using a supplied quantitative template to examine three short-horizon stock factors: five-day momentum, five-day reversal, and five-day volatility. The universe is described as stocks priced between zero and two yuan.…

China marketsEquitiesMomentumMean reversion
Amberdata research

This analysis studies Bitcoin options from April 2019 through December 2022, describing how volatility pricing changed across quiet markets, rallies, sharp selloffs, and the 2022 bear market. It examines the at-the-money implied volatility term structure,…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock screen combines three conditions: daily amplitude above 1, at least one daily gain of 10% or more during the previous 25 trading days, and displayed first-level buy volume greater than sell volume. The document explains these as signals of price…

EquitiesMomentumVolatilityMarket microstructure
SuperMind

The document describes a daily stock screen applied after the market opens. It selects shares whose five-period amplitude measure exceeds 1, whose change in a proxy for institutional trading volume is nonzero, and whose KDJ K value is below 20. The rationale…

EquitiesTechnical indicatorsMean reversionVolatility
BigQuant

This factor-replication note divides stocks into two behavioral groups. “Team” stocks are described as low in both volatility and turnover: after rising, they are expected to attract continuation expectations, become overbought, and then retreat. “Coin”…

EquitiesMean reversionFactor investingVolatility
SuperMind

This post describes a Chinese equity screening rule that combines price movement, stock status, a five-session limit-up approach, and prior-day trading value. It selects stocks with amplitude above 1, excludes ST-designated stocks, applies the named…

EquitiesBreakoutChina marketsVolatility
SuperMind

This stock-selection rule combines three filters: daily amplitude above 1, at least two limit-up sessions within the prior 500 days, and a closing price below 12. The article frames the price threshold as a way to focus on lower-priced shares and the…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This post presents a Chinese equity screen combining daily price amplitude, a stock code beginning with 60, and a measure described as today’s control ratio above a threshold. It frames larger amplitude as a sign of higher volatility and the control ratio as…

China marketsEquitiesTechnical indicatorsVolatility