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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
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

4,613 documents

Machine Learning for Trading

The notebook builds prediction intervals around gradient boosting forecasts with split conformal prediction. It fits a model on an earlier training segment, measures absolute residuals on a later calibration segment, and uses a finite-sample order statistic…

Machine learningStatisticsRisk managementPosition sizing
Machine Learning for Trading

This notebook applies previously selected firm-characteristic predictions and a fixed portfolio configuration to a one-year holdout period. It makes no new choices about predictions, allocation, concentration, rebalancing, or transaction costs, preserving…

EquitiesFactor investingPosition sizingBacktesting
Machine Learning for Trading

This module defines a point-in-time simulation environment for executing a large sell order in crypto perpetual futures. Its observations combine remaining inventory and time with market volatility, premium index, relative volume, hour of day, and time to…

CryptoPerpetual futuresExecutionMarket microstructure
Machine Learning for Trading

This case study applies causal estimation to ETF momentum and asks whether its effect on forward returns varies with market volatility. It uses a continuous momentum treatment, a 21-day forward-return outcome, volatility and yield-curve controls, and a…

EquitiesUS marketsMomentumMachine learning
Machine Learning for Trading

The document explains how four market-impact models estimate the adverse per-share price move associated with an order: no impact, linear impact, square-root impact, and a configurable power law. It clarifies the sign convention, the roles of participation,…

ExecutionMarket microstructureBacktestingRisk management
Machine Learning for Trading

This notebook examines why two backtesting engines can produce different results from identical signals. It holds the strategy and tradable universe fixed, makes portfolio weights deterministic when predictions tie, and exposes execution settings such as…

BacktestingExecutionPosition sizingRisk management
Strategy library

This strategy combines dollar-cost averaging with a trailing take-profit exit. It adds to a long position when price falls by a configurable amount from the previous buy, subject to a maximum number of additions. Once price rises above the last buy price by…

CryptoFuturesMean reversionPosition sizing
Strategy library

ReinforcedSmoothScalp is a one-minute long-only scalping strategy that seeks frequent entries and small gains. It resamples price to a five-minute interval and uses a 50-period simple moving average there as a broad trend filter. On the trading timeframe,…

CryptoMean reversionTechnical indicatorsRisk management
Strategy library

This strategy identifies four reversal patterns: hammer and bullish engulfing for potential longs, and shooting star and bearish engulfing for potential shorts. It waits for price to cross the signal candle’s high or low before entering, rather than trading…

BreakoutTechnical indicatorsRisk managementPosition sizing
Strategy library

This strategy opens long positions at scheduled times within a daily trading window, adding entries step by step up to a configured maximum. Each entry receives its own take-profit and optional stop-loss, so positions can close separately. An optional…

FuturesPosition sizingRisk managementBacktesting
Strategy library

This intraday strategy uses the relationship between a 9-period and a 20-period exponential moving average to define trend direction. A bullish crossover arms long setups and a bearish crossover arms short setups. Afterward, the price must retest either EMA,…

Technical indicatorsTrend followingRisk managementPosition sizing
Strategy library

This hourly TSLA strategy enters long when a custom BlueWave oscillator and smoothed money flow are both positive and rising, while price remains above the 50-period and 200-period exponential moving averages. The entry condition is designed to align…

EquitiesUS marketsMomentumTechnical indicators
Strategy library

This source describes a multi-signal trading strategy that converts three indicator readings into directional positions. The RSI component goes long or short when the indicator crosses configurable levels around its midpoint; the CCI component uses positive…

Technical indicatorsMean reversionMomentumTrend following
Strategy library

The described strategy follows a fast and slow exponential moving average crossover, using the upward cross as a long entry signal. Its stated defaults are 20 and 50 periods. After entry, it places a profit target at 1.3 times entry price and a stop at 0.95…

FuturesCryptoTrend followingTechnical indicators
Strategy library

The visible portion describes a Pine strategy organized around order blocks, market structure, risk management, sessions, and a dashboard. Its configurable controls include geometric percentage sizing or fixed micro contracts, a per-trade risk setting, a…

Market microstructureRisk managementPosition sizingExecution
Strategy library

This BTC futures strategy combines fast and slow EMA direction with MACD crossovers and RSI thresholds to trigger long and short entries. It places a fixed stop 5% from entry, takes partial profit at 8%, and uses a second target initially set at 12% that is…

FuturesCryptoTrend followingTechnical indicators
Strategy library

This strategy combines RSI thresholds with the relative position of two EMAs. It signals a long when the 14-period RSI is below 40 while the 9-period EMA is above the 21-period EMA; it signals a short when RSI is above 60 while the fast EMA is below the slow…

Technical indicatorsTrend followingMomentumRisk management
Strategy library

This intraday strategy limits entries to a specified London session window on weekdays. It goes long after three consecutive rising candles and short after three consecutive falling candles. Entries are managed with percentage-based stop-loss and take-profit…

ForexBreakoutMomentumRisk management
Strategy library

This BTC futures swing strategy combines a 20-period EMA and 50-period SMA crossover with RSI confirmation. It permits a long entry when the averages cross upward and RSI is below 70, or a short entry on a downward cross when RSI is above 30. ATR is used to…

CryptoFuturesTrend followingTechnical indicators
Strategy library

This partial Pine Script describes a long-entry strategy that combines Bollinger Bands, three long-term simple moving averages, and RSI in a weighted oversold score. A close below the lower band contributes a point; trading below progressively longer…

Mean reversionTechnical indicatorsPosition sizingRisk management
Strategy library

This Bitcoin strategy maps price into ten risk bands between a 200-week moving-average floor and a logarithmically derived upper level. It uses the band location to scale monthly dollar-cost averaging: purchases increase as price moves into lower bands,…

CryptoFuturesPosition sizingRisk management
Strategy library

This trend following system uses a short and a long exponential moving average to determine entries and exits. A bullish crossover opens a long position when none is open, while a bearish crossover closes that position. The described setup uses a 10-minute…

Technical indicatorsTrend followingPosition sizingBacktesting
Strategy library

This strategy seeks breakouts during configurable London and US trading windows. A bullish signal occurs when a rising candle closes above the prior high; a bearish signal occurs when a falling candle closes below the prior low. After a signal, the source…

FuturesBreakoutPosition sizingExecution
Strategy library

The strategy uses VWAP as a reference price and places limit entries at offset bands around it. A move to the lower band can open a long position, while a move to the upper band can open a short position; the stated exit is a return toward the VWAP line.…

FuturesTechnical indicatorsMean reversionPosition sizing