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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
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
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

79,386 documents

BigQuant

This report compares AdaBoost, gradient boosting decision trees, and XGBoost as tools for selecting Chinese equities from factor data. Its workflow covers feature and label preparation, preprocessing, in-sample fitting, cross-validation, and out-of-sample…

Machine learningEquitiesFactor investingBacktesting
MQL5 code base

The document briefly introduces r_Gator as an analogue of the Alligator technical indicator, with the stated aim of reducing signal lag. It notes that the indicator was first implemented in MQL4 and published in 2008. No formula, parameter settings, chart,…

Technical indicatorsTrend following
BigQuant

This note shows how to construct a simple stock relative-return factor using a precomputed Chinese equity dataset. It identifies one field as each stock’s daily return and another as the CSI 300 index return, then defines relative return as the stock return…

EquitiesChina marketsFactor investingStatistics
SuperMind

This Chinese A-share screening idea combines three filters: daily price amplitude above a threshold, a minimum time since listing, and a MACD condition above the indicator’s zero axis. The article explains that amplitude is calculated from the day’s high and…

China marketsEquitiesTechnical indicatorsMomentum
OctoBot

This product guide explains a redesigned strategy interface with two parts: a viewer for examining and comparing strategies, and a creator for configuring new tests. The viewer presents performance metrics, behavior over time, and individual trade details.…

CryptoBacktestingPortfolio constructionExecution
SuperMind

This post outlines a Chinese stock screen for companies classified in the metaverse sector. It limits eligible stocks to those with circulating shares at or below 5.5 billion and excludes stocks that reached the upper price limit on the prior trading day. It…

EquitiesChina marketsMomentumRisk management
SuperMind

This note describes a Chinese A-share screening rule for Shenzhen Main Board stocks. It combines daily amplitude above 1%, a reversal or engulfing-style signal, and positive price-to-earnings and price-to-book ratios below 29.01 and 3.11, respectively. The…

EquitiesChina marketsTechnical indicatorsMean reversion
BigQuant

This troubleshooting note addresses errors that arise after adding a rolling-training module to an AI strategy for convertible bonds. It points to a revised notebook and identifies two implementation changes associated with the fix. First, the rolling…

Machine learningBacktestingFixed incomeChina markets
MQL5 code base

This indicator description combines the Williams %R oscillator with Bollinger Band boundaries to define overbought and oversold areas. The band thresholds are intended to adapt to the oscillator’s behavior, rather than relying only on fixed levels. The…

Technical indicatorsForexMean reversionVolatility
FMZ live strategies

This live-robot dashboard records a crypto spot arbitrage system trading BTC/USDT across Gate and KuCoin, alongside a wider set of monitored assets. Its logs show paired buys and sells on the two venues, with the direction varying by trade. The displayed…

CryptoArbitrageSpot marketsExecution
BigQuant

This study applies a factor-timing framework from a 2019 paper to China A-share data. It parameterizes factor weights using external variables and compares two approaches based on where the information enters: a time-series model and a cross-sectional model.…

EquitiesFactor investingStatisticsPortfolio construction
SuperMind

This post describes a Chinese equity selection screen with three filters: price amplitude above 1%, a ten-day price gain greater than zero but below 35%, and circulating market capitalization between 5 billion and 10 billion yuan. Its accompanying Python…

EquitiesChina marketsMomentumTechnical indicators
BigQuant

This short forum post asks how to export a backtest’s daily returns to a CSV file and where to place a suggested calculation in the BigQuant workflow. The proposed approach reads a performance DataFrame, adds one to the cumulative algorithm return, computes…

BacktestingStatistics
SuperMind

This post describes a stock screen requiring a daily price range greater than 1%, a trading date in 2021, and float market capitalization above 10 billion yuan. It presents these conditions as a way to identify higher-volatility shares while limiting the…

EquitiesVolatilityStatistics
MQL5 code base

This Chinese-language post describes an equity screening rule using RSI below 65, a three-candle pattern described as three consecutive down candles, and prior-day turnover above 8%. It frames RSI and the candle sequence as signs of weakness, while high…

EquitiesTechnical indicatorsSentiment
ProRealCode

This note presents a third-generation moving average attributed to Dr. Manfred G. Dürschner. It calculates a short-period average, then averages that result over a longer period, and combines the two with a coefficient derived from their relative lengths.…

Technical indicatorsStatistics
SuperMind

This Chinese equity selection rule filters stocks by trading activity, prior-day leaderboard appearance, and the latest daily price change. It seeks names with turnover between 3% and 12%, a positive leaderboard flag on the preceding day, and a daily return…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

This Expert Advisor uses the AFIRMA autoregressive finite impulse response moving average indicator to generate trade signals. It checks for a change in the indicator’s direction when a bar closes, then forms a signal. The document notes that the indicator…

ForexTechnical indicatorsBacktestingExecution
vn.py community

This short forum exchange addresses a Python import error that appeared after upgrading VeighNa. A user reports that strategies which previously worked now fail because `AccountData` cannot be imported from the CTA strategy package. The reply identifies the…

Execution
BigQuant

This report evaluates the Shanghai 180 index and the Hua An Shanghai 180 ETF. It describes an index weighted heavily toward financial companies and food and beverage firms, with large, liquid constituents. The report characterizes its recent one-, three-,…

EquitiesChina marketsVolatilityStatistics
MQL5 code base

This Expert Advisor combines ADX, CCI, RVI, and Williams %R indicators with a martingale sizing approach. Its suggested tuning sequence first optimizes the main signal and ADX settings with the WPR strategy disabled, then tunes WPR separately, and finally…

ForexTechnical indicatorsRisk managementBacktesting
MQL5 code base

This indicator description defines alert conditions using Bollinger Bands and price envelopes together. A buy alert is triggered when a bullish candle opens and closes below both lower bands. A sell alert requires a bearish candle to open and close above…

Technical indicatorsMean reversionVolatility
MQL5 code base

This MetaTrader 5 Expert Advisor description outlines a breakout scalping system that trades only when a set of filters align. It uses fast and slow exponential moving averages to define direction, an ATR-based threshold for trend strength, price location…

BreakoutTechnical indicatorsRisk managementPosition sizing
SuperMind

This Chinese stock-screening post describes a three-part selection rule: rank stocks by volume ratio and keep the top 100, require weekly MACD to be above zero, and exclude stocks whose gain at 9:25 is 6% or more. The author interprets the filters as…

EquitiesTechnical indicatorsMomentum