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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

21,023 documents

MQL5 code base

This research summary explains a method for testing whether U.S. equity mutual fund managers adjust market exposure when broad stock misvaluation changes. It constructs a misvaluation measure from a long portfolio of repurchasing firms and a short portfolio…

EquitiesFactor investingStatisticsPortfolio construction
BigQuant

This research summary describes a multi-factor investment workflow that combines alpha forecasts, a risk model, transaction-cost estimates, portfolio optimization, and performance attribution. It argues that simple score-based selection or sector and…

EquitiesPortfolio constructionRisk managementStatistics
BigQuant

This brief Chinese-language support note explains a prediction-data problem traced to missing values in a rolling price-range factor. The example factor compares a short moving average of the high-low range with a longer moving average. According to the…

Machine learningStatisticsTechnical indicatorsBacktesting
BigQuant

This study examines whether price-to-earnings ratios, cyclically adjusted P/E (CAPE), and the bond-stock earnings yield measure (BSEYD) can signal major downturns in the Shanghai and Shenzhen composite indexes. It also describes return features in the two…

EquitiesChina marketsStatisticsBacktesting
Amberdata research

This article applies the stock-to-flow ratio to Bitcoin as a scarcity-based valuation approach. It defines stock as the existing supply and flow as new annual issuance, then estimates Bitcoin’s annual production from the change in supply over a year. Using…

CryptoStatisticsBacktesting
MQL5 code base

CCIBands extends the Commodity Channel Index (CCI) with two additional lines that mark high and low values. These boundaries help show where the indicator sits relative to its range, adding context to the usual CCI reading. The indicator also includes a…

Technical indicatorsStatistics
BigQuant

This discussion examines why published quantitative findings and attractive backtests may fail to reproduce or translate into tradable returns. It explains how publication incentives, selective reporting, repeated testing, flexible data choices, and…

StatisticsBacktestingRisk managementFactor investing
MQL5 code base

This indicator adapts MACD to changing price behavior by using Fractal Adaptive Moving Averages. FRAMA adjusts its smoothing factor according to the price series’ fractal dimension, aiming to respond to strong trends while slowing during consolidation. The…

Technical indicatorsTrend followingStatistics
MQL5 code base

The document discusses a limitation of the Relative Strength Index: as its calculation period grows, the series can become flatter and less useful for analysis. It says RSI is commonly treated as already normalized because it stays within a bounded range,…

Technical indicatorsStatisticsMomentum
BigQuant

The document explains how to construct factors grouped by Chinese stock market concepts when a built-in grouping expression does not recognize the concept field. For standard industry groupings, it gives a group-mean example using a level-two industry…

EquitiesFactor investingStatisticsChina markets
BigQuant

This brief introductory response defines quantitative investing as finding patterns in historical data, translating them into a model and strategy, and using software to execute trades according to the resulting rules. It highlights discipline as a benefit:…

StatisticsMachine learningBacktestingRisk management
ProRealCode

This indicator identifies potential divergences between closing prices and three measures: MACD, RSI, and the Money Flow Index. It compares recent local highs or lows in each indicator with price extremes over a configurable lookback window, then draws…

Technical indicatorsMomentumStatistics
MQL5 code base

The document describes a technical indicator that filters price data using a deviation measure that adjusts with the chosen filter size. Its purpose is to remove selected price changes and leave a smoother filtered price series. The text distinguishes this…

Technical indicatorsStatistics
BigQuant

A user reports a discrepancy between a trade’s recorded execution price and the stock’s historical prices on the same date after adjustment for corporate actions. The example contrasts a reported buy price with lower adjusted open and close values. The…

EquitiesBacktestingStatistics
Stratmill research code

The document describes an optimal transport measure that compares the empirical dependence between two data series with a chosen target copula. It first converts paired observations to ranked uniform values, then measures transport distances from that…

StatisticsMarket microstructure
MQL5 code base

Swing Shift is an oscillator that tracks moving-average slope relative to a configurable threshold. It calculates a normalized difference between the current moving average and an anchor value. When the slope crosses the positive threshold while the prior…

Technical indicatorsTrend followingStatistics
SuperMind

This proposed Chinese stock screen combines a turnover ratio between 3% and 12%, seven consecutive days of falling prices, and an auction-period price change greater than -2% and below 5%. The article presents these conditions as a way to identify stocks…

EquitiesChina marketsTechnical indicatorsStatistics
BigQuant

This opinion piece argues that retail traders should be cautious about relying on remembered successes and discretionary short-term trading habits as markets become more influenced by institutions and quantitative models. Its central practical message is to…

EquitiesChina marketsRisk managementStatistics
MQL5 code base

This document defines Trend Score as a cumulative count of directional price changes. With a fixed period, each bar contributes positive one when price rises, negative one when it falls, and zero when unchanged; summing these values gives a bounded measure…

Technical indicatorsTrend followingBreakoutStatistics
MQL5 code base

The document describes a technical indicator that fits a polynomial regression curve to prices over a selected span and presents the result as a histogram. Its adjustable inputs are the calculation period, the polynomial power, and the price series used in…

Technical indicatorsStatistics
MQL5 code base

Rocket RSI is presented as a variation on the classic relative strength index. It builds an RSI-like measure from accumulated up and down closes rather than averaged gains and losses, smooths momentum with a two-pole super smoother, and can apply a Fisher…

Technical indicatorsMomentumMean reversionStatistics
BigQuant

This document introduces the Campisi model as a framework for explaining the performance of pure bond funds. It describes decomposing a fund’s total return and excess return into four sources: income, government-bond effects, spread effects, and security…

Fixed incomePortfolio constructionStatistics
BigQuant

This article describes using recurrent neural networks to predict the direction of the next price change from high-frequency order-book data. The study uses data from Nasdaq stocks and keeps observations where prices change, reducing the input sequence. It…

EquitiesHigh-frequency tradingMachine learningMarket microstructure
BigQuant

This discussion raises a timing problem in backtests that use premarket processing. In the example, a signal is generated on one day and orders are submitted the next day; the author notes that historical data queried before trading may already include that…

BacktestingExecutionStatistics