Skip to content

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
WonderTrader
14 documents
Alphalens
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,303 documents

ProRealCode

This indicator pairs ATR-based SuperTrend regime changes with a relative-volume confirmation filter. It estimates buying and selling volume from each bar’s close within its high-low range, then compares a fast EMA of each side’s volume with a slower EMA…

Technical indicatorsTrend followingVolatilityBacktesting
FMZ forum

This introduction explains technical analysis as the study of an asset’s price history and chart behavior to inform trading decisions. It presents charts as a visual way to inspect past prices, current direction, movement variability, and signs of market…

Technical indicatorsStatisticsVolatility
FMZ forum

The article introduces financial time series as sequential observations modeled as realizations of stochastic processes. It identifies trends, seasonal variation, and serial dependence as recurring features, with volatility clustering and commodity…

StatisticsVolatilityMachine learning
MQL5 code base

This document describes an ATR-based technical indicator that allows users to choose among multiple smoothing algorithms and shift the plotted values horizontally. In addition to common moving-average methods—simple, exponential, smoothed, and linearly…

Technical indicatorsVolatility
SuperMind

This article introduces Bollinger Bands as a volatility-based technical indicator built around a moving average. It describes the middle band as an N-day average of closing prices and the upper and lower bands as that average plus or minus a multiple of the…

EquitiesTechnical indicatorsVolatilityMean reversion
BigQuant

The article explains Bollinger Bands as a moving average surrounded by upper and lower bands set two standard deviations away. It also introduces band width as a way to identify volatility contraction, or a squeeze, which may precede a breakout but does not…

Technical indicatorsVolatilityMean reversionBreakout
MQL5 code base

The document describes a market indicator inspired by Edgar Peters’s work and based on the Bollerslev GARCH model. It presents the indicator as a way to track changing volatility: its value rises when market volatility is high. The author also suggests that…

VolatilityTechnical indicatorsStatistics
MQL5 code base

The Flat indicator is described as a tool for measuring market volatility and displaying conditions through colored dots. Red dots mark strong trends, gray dots mark weak trends, and blue dots indicate moderate trends. Its inputs include a smoothing period…

Technical indicatorsVolatilityTrend following
MQL5 code base

This indicator combines a variable moving average with a display of trend direction and strength. It can round the latest value and channel levels to a chosen number of digits, and places colored dots on the moving average to show the trend. The description…

Technical indicatorsVolatilityTrend following
SuperMind

The document describes a Chinese equity screening rule that places stocks in a candidate pool when their high-to-low price range exceeds 1%, the trading year is 2021, and company scale is at least 200 million. It gives example implementations in a charting…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This document presents a simple stock screen that selects shares with a daily high-low range above 1%, a price below 20, and a closing price below 12. It provides a formula and a Python sketch; the Python version also sorts selected stocks by trading volume.…

EquitiesChina marketsTechnical indicatorsVolatility
MQL5 code base

The Thrust Bar indicator marks bullish or bearish candles whose bodies exceed a configurable size threshold. It offers two calculation modes: compare the candle body with a multiple of the average true range, or compare it with a fixed number of points. In…

Technical indicatorsVolatility
Amberdata research

This brief market recap describes conditions in Bitcoin and Ether derivatives as of February 8, 2023. It tracks realized volatility, futures or options term structure, skew, and observed option flows. The reported picture is declining realized volatility, a…

CryptoOptionsVolatilityDerivatives pricing
ProRealCode

The document presents a price range detector that tests three nested lookback windows and selects the longest window satisfying a set of structural filters. These include volatility compression ranked against the instrument’s own history, repeated closes…

Technical indicatorsStatisticsVolatilityBreakout
MQL5 code base

This short note describes an indicator that draws Bollinger Bands calculated on a user-selected timeframe. It uses a section-based drawing style, which the document identifies as a common way to render Zigzag-like lines. The timeframe is configurable through…

Technical indicatorsVolatility
SuperMind

This Chinese stock-screening example combines three signals: daily price amplitude above one, positive institutional net flows summed over five days, and a rule-based arc-top or arc-bottom pattern. It describes the pattern checks using recent highs and lows…

EquitiesChina marketsTechnical indicatorsVolatility
Amberdata research

This market recap reviews BTC and ETH options after a sharp spot recovery. It discusses realized and implied volatility, term structures, volatility carry, call and put skew, relative value between the assets, option flows, and dealer gamma. The commentary…

CryptoOptionsVolatilityDerivatives pricing
MQL5 code base

The document describes an indicator for marking periods when prices move within a range. It offers two ways to define the range: a fixed point threshold or a threshold that changes with average true range (ATR) multiplied by a user-set factor. ATR is the…

Technical indicatorsVolatilityBreakout
ProRealCode

This indicator overlays simple moving averages and standard deviation bands from slower time frames onto a faster chart. It supports monthly, weekly, daily, hourly, and minute inputs, with configurable averaging periods and deviation multipliers. For hourly…

Technical indicatorsVolatility
MQL5 code base

This description outlines an automated breakout approach using price range, moving averages, and Keltner channels. A long entry requires price to break above the channel, a candle to meet a specified minimum length, and price to be above a moving average.…

BreakoutVolatilityTechnical indicatorsExecution
MQL5 code base

This note explains a variation of the Rahul Mohindar oscillator as a histogram with signal pointers. Its inputs are three EMA periods and an applied price. The calculation first builds a swing-trading value by comparing the applied price with an average…

Technical indicatorsMomentumVolatility
MQL5 code base

Average Change is described as an indicator for assessing the force of a financial asset’s price movement. It is intended to show price impulse and provide an indication of market volatility. The note attributes the indicator to MT-Coder and says it uses…

Technical indicatorsMomentumVolatility