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
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

21,023 documents

Freqtrade docs

This guide outlines a notebook workflow for debugging and analyzing a Freqtrade strategy. It loads historical candles for a selected pair and timeframe, runs the strategy to inspect generated entry signals, and explains that signal counts do not equal…

BacktestingTechnical indicatorsStatisticsRisk management
ProRealCode

The document presents a ProRealCode implementation of John Ehlers’s Adaptive Cyber Cycle indicator, adapted from a TradingView version. It begins with a smoothed midpoint price series, derives a cycle component, and estimates cycle phase change using…

Technical indicatorsStatistics
BigQuant

The article describes a method for estimating consensus net profit from analyst forecasts and using that estimate to build equity selection signals. It weights forecasts by report recency and by each analyst’s prior adjusted forecast error, giving greater…

EquitiesFactor investingStatisticsBacktesting
MQL5 code base

MyRSI is presented as a variation of the relative strength index associated with John Ehlers. Its values use a range from -1 to 1, making the zero line a possible signal reference. This differs from conventional RSI’s scale and means familiar threshold…

Technical indicatorsStatistics
MQL5 code base

StoneAxe is described as a normalized oscillator that places the closing price within the recent high-to-low range. The calculation maps the close’s position between the period low and period high onto a scale from -100 to 100, with the range midpoint…

Technical indicatorsStatistics
MQL5 code base

This indicator description presents seven RSI calculation variants: standard RSI, Cutler’s RSI, Ehlers’ smoothed RSI, Harris’ RSI, Rapid RSI, RSX, and Slow RSI. It also supports fixed reference levels or floating levels, with the selected mode determined by…

Technical indicatorsStatistics
MQL5 code base

TrendManager is described as an indicator that compares two moving averages and treats the market as trending when their difference exceeds a trigger threshold. The document gives a configurable threshold expressed in chart points, but does not explain how…

Technical indicatorsTrend followingStatistics
SuperMind

The post outlines a study of autoregressive (AR) and mean-reversion (MR) models using CSI 300 prices and returns. Its stated aim is to show the modeling workflow, fit the models, make forecasts, and compare how the models perform relative to each other. This…

China marketsEquitiesStatistics
ProRealCode

The congestion index measures how widely closing prices have ranged over a chosen lookback period. It subtracts the lowest close from the highest close, divides that difference by the lowest close, and expresses the result as a percentage. A trader could use…

Technical indicatorsBreakoutStatistics
MQL5 code base

This excerpt introduces foundational MQL5 programming concepts for readers building trading programs. It covers data types, identifiers, variables, expressions, and operators, and explains that combining instructions establishes a program’s logic. It also…

EquitiesExecutionStatistics
SuperMind

This Chinese equity-screening post proposes selecting stocks with RSI below 65, three consecutive down sessions, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and no more than 100%. It combines a technical…

EquitiesChina marketsTechnical indicatorsMean reversion
MQL5 code base

Ultra Trend estimates market direction by calculating the slopes of moving averages with different periods. The indicator then derives a trend reading from those slopes. The described version uses a fast Zero Lag Moving Average for that calculation, with the…

Technical indicatorsTrend followingStatistics
MQL5 code base

The Projection Oscillator adapts Projection Bands into an oscillator displayed in a separate chart window. It uses a calculation period and user-set overbought and oversold levels to help interpret where the closing price lies within the projected band…

Technical indicatorsStatistics
MQL5 code base

The document describes an MT4 script that analyzes historical price data to estimate how much an asset typically moves across a chosen number of trading days. The resulting averages can be displayed as a column chart to compare more active days with quieter…

Technical indicatorsStatisticsBacktesting
MQL5 code base

This indicator estimates intraday buying or selling pressure by weighting volume according to where the close falls within the high-low range. It then displays the resulting intensity value as a histogram and calculates a simple moving average of that value…

Technical indicatorsMarket microstructureStatistics
backtesting.py

The tutorial demonstrates how to optimize a four-moving-average strategy and inspect how its parameter choices affect backtest results. Two averages define the prevailing trend, while price crossing separate entry and exit averages triggers trades. The…

EquitiesTechnical indicatorsBacktestingStatistics
Hummingbot docs

This research summary explains that style rotation depends on defining each style accurately before building a timing model. It distinguishes styles represented by current stock characteristics, such as size, value, reversal, and momentum, from styles…

EquitiesFactor investingMomentumMean reversion
BigQuant

This brief investment summary argues that the CSI 300 offered an attractive risk-reward profile in a pessimistic scenario. It compares valuation multiples based on different years’ net profits: 12 times using 2015 profits after the circuit-breaker episode,…

EquitiesChina marketsStatistics
BigQuant

This support discussion explains a factor-analysis failure caused by insufficient coverage of a derived price feature. The feature compares the close with the high-low range and then takes a one-period change. Although feature extraction returned data, the…

Factor investingStatisticsBacktesting
SuperMind

The proposed stock screen combines a positive MACD reading, a profitability-based company filter, and ranking by current auction trading activity, selecting five stocks. The accompanying Python example approximates the company-quality screen using recent…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

This brief indicator description identifies the RSI as having dynamic levels and lists its configurable inputs. The user can select which price series feeds the calculation, including close, open, high, low, median, typical, or weighted price. An RSI period…

Technical indicatorsStatistics
SuperMind

The post describes a stock screen using three conditions: price amplitude above a threshold, a positive weekly bar or momentum reading, and turnover between 2% and 9%. It explains these as a way to seek stocks showing movement and short-term strength while…

China marketsEquitiesTechnical indicatorsMomentum
ProRealCode

This indicator highlights candles whose volume is at least twice a 125-period Wilder average. When the threshold is met, it places a label near the candle low showing the rounded volume multiple. An optional setting colors high-volume bullish candles blue…

Technical indicatorsStatisticsMarket microstructure
SuperMind

This proposed China A-share screen combines three conditions: a 12-period RSI below 65, membership in the beverage and alcohol import-export industry, and previous-day actual turnover between 3% and 28%. The article presents turnover as a measure of market…

China marketsEquitiesTechnical indicatorsStatistics