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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

OctoBot

This introductory article explains how rapid price rises fueled by investor enthusiasm can develop into cryptocurrency bubbles and sharp declines. It identifies new investor inflows, fear of missing out, media attention, and imitation of other buyers as…

CryptoVolatilitySentimentRisk management
MQL5 code base

This brief description presents an indicator that uses Average True Range as a reference for placing stop losses. It draws two bands at equal distances from a moving average, making the bands a volatility-based guide around a baseline. The text also proposes…

Technical indicatorsVolatilityRisk managementBreakout
MQL5 code base

The document describes two strategies using an adaptive baseline and volatility bands. For momentum breakouts, it calls for a candle close beyond an outer band and a baseline color indicating the same direction; the trade is held until the baseline changes…

ForexCryptoTrend followingMean reversion
SuperMind

The proposed equity screen combines intraday range, Bollinger Band position, and a specific opening-time price-change condition. It looks for stocks whose range exceeds its recent average, whose close lies between the middle and upper Bollinger Bands, and…

EquitiesChina marketsTechnical indicatorsVolatility
MQL5 code base

This MetaTrader 5 indicator combines pivot-based swing analysis with Fibonacci retracements. It labels swing points as higher highs, higher lows, lower highs, or lower lows, and classifies breaks as continuation events (BOS) or possible reversals (CHoCH).…

Technical indicatorsBreakoutVolatilityRisk management
Amberdata research

This mid-week recap summarizes derivatives conditions in Bitcoin and Ether as of April 21, 2023. It reports stable Bitcoin 10-day realized volatility in the low 30s while attention shifted toward Ether, and describes term structures for both assets as moving…

CryptoOptionsVolatilityDerivatives pricing
MQL5 code base

This brief description introduces Rj_SlidingRange as a technical indicator whose operation is similar to Bollinger Bands and Envelopes. It identifies the indicator’s original author and notes that it was first implemented in MQL4 and published in 2012. The…

Technical indicatorsVolatility
MQL5 code base

Corrected Average, also called Optimal Moving Average, is a smoothed indicator intended to avoid following price for small deviations that may produce false trend signals. It starts with a moving average of the selected applied price, using a configurable…

Technical indicatorsVolatilityTrend following
MQL5 code base

AverageChangeCandle is a chart indicator designed to display price impulse and give a visual sense of market volatility. It calculates changes for the open, high, low, and close price series and presents those four measurements together as a candlestick…

Technical indicatorsVolatilityMomentum
MQL5 code base

This document describes a semaphore signal indicator built around the XCCX_StDev oscillator. Its configurable mode selects among five signal rules: oscillator levels alone, deviation thresholds alone, both conditions together, or the combined conditions…

Technical indicatorsVolatilityTrend following
ProRealCode

The Damiani Volameter is presented as a filter for identifying whether market conditions are trending or ranging. It compares a volatility meter with a threshold: the document says a green line above the black line indicates a trend, while the reverse…

Technical indicatorsVolatilityTrend followingMean reversion
ProRealCode

The SP Indicator combines a smoothed moving-average line with volatility-based upper and lower bands. Candle colors indicate whether price is above, below, or between the bands: these states are presented as bullish, bearish, or neutral conditions. Optional…

Technical indicatorsTrend followingVolatilityBreakout
MQL5 code base

The document introduces a higher-timeframe version of the FineTuningMA_StDev indicator for MetaTrader 5. A timeframe input lets the user select the chart period from which the indicator operates, with a four-hour period shown as the default. The stated setup…

Technical indicatorsVolatility
SuperMind

This post describes a stock selection screen for Chinese equities. It selects stocks with a daily high-low range above a threshold, positive afternoon large-order net inflow, and exclusion of the STAR Market. It treats a wide range as a sign of greater price…

EquitiesVolatilityMarket microstructureTechnical indicators
Amberdata research

The document reviews crypto market conditions ahead of the Bitcoin halving and discusses how macroeconomic pressure may affect sentiment and options pricing. It points to higher Treasury yields and a stronger dollar as headwinds while noting that implied…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

The webinar summary addresses how to estimate option values in newer crypto markets where liquid options data may be sparse or absent. It describes Amberdata’s approach as using liquid equity options as a reference for generating implied volatility surfaces,…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This Chinese stock-selection method seeks volatile shares that have recently shown strong price movement. Its initial rules look for daily high-low range greater than a 20-period ATR, a single-day move of at least 10% within the past 25 trading days, and a…

EquitiesVolatilityMomentumTechnical indicators
SuperMind

The proposed screen selects stocks with amplitude above one, a prior-day signal described as main-force control, and at least one daily gain of 10% or more during the previous 25 trading days. It combines a volatility condition with a recent large-move…

EquitiesChina marketsMomentumVolatility
SuperMind

This screening rule selects Shanghai-listed stocks with a daily high-low range above 1% of the previous close, then sorts them by an individual-stock popularity measure. The article interprets the range threshold as a way to find more volatile names and…

EquitiesChina marketsVolatilitySentiment
SuperMind

This post proposes an A-share screen using amplitude above 1, a share price of 18.5 yuan, and an outside-to-inside trading-volume ratio above 1.3. It treats amplitude as a volatility filter, the price cutoff as a price-level constraint, and the volume ratio…

EquitiesTechnical indicatorsVolatilityChina markets
Amberdata research

This podcast recap discusses Bitcoin’s volatility and derivatives market conditions around a sharp price decline and subsequent stabilization. It introduces implied volatility and volatility compression, and describes a reported contrast between elevated…

CryptoVolatilityOptionsDerivatives pricing
MQL5 code base

This research summary examines the low idiosyncratic volatility effect in China’s A-share market. It estimates volatility from the annualized standard deviation of residuals in CAPM, Fama–French three-factor, and Carhart four-factor regressions fitted to the…

China marketsEquitiesFactor investingVolatility
ProRealCode

The document describes an approximation of a curvature trend indicator using an exponential moving average as its central trend line and average true range to scale upper and lower bands. The bands begin at a chosen ATR multiple from the moving average, then…

Technical indicatorsTrend followingVolatility
SuperMind

This A-share screening proposal selects stocks with daily amplitude above 1%, at least two limit-up sessions in the prior 500 days, and a gain below 6% at 9:25. It treats amplitude and prior limit-ups as signs of volatility and market attention, while the…

China marketsEquitiesTechnical indicatorsVolatility