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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

BigQuant

This practitioner report describes experiments using a deep neural network to select stocks for a rapid rotation strategy. The model labels stocks by their subsequent return over a short holding interval, divides outcomes into ranked classes, and uses a…

EquitiesMachine learningHigh-frequency tradingBacktesting
MQL5 code base

This document describes an automated trading system based on Fractals and Alligator indicators, with settings for take profit, stop loss, trailing exits, and break-even adjustments. It says the system is intended for daily charts on major forex pairs and…

ForexEquitiesTechnical indicatorsRisk management
MQL5 code base

The described expert advisor begins by opening equal, minimal-sized long and short positions, each with predefined take-profit and stop-loss levels. When one position reaches its profit target, it closes; the losing side is enlarged at price intervals, with…

ForexRisk managementPosition sizingBacktesting
MQL5 code base

This document describes a versioned template for trading multiple currency pairs, with moving averages offered as a sample entry logic. It says the entry logic can be changed, so the moving-average example is a starting point rather than a fixed strategy.…

ForexTechnical indicatorsPosition sizingRisk management
BigQuant

This article presents a discretionary approach to rotating from an established leading stock or theme into a newer one. It watches for signs of a theme gaining breadth, such as multiple limit-up stocks, rising sector performance, and an increasing count of…

EquitiesChina marketsMomentumPosition sizing
vn.py community

The post asks how to translate the Turtle Trading system’s N measure into contract size. Its proposed calculation uses average true range over a chosen risk window, then divides one percent of risk capital by ATR multiplied by the assumed price tick and…

FuturesPosition sizingRisk managementTechnical indicators
FMZ forum

This article describes a portfolio component for an event-driven backtester. A portfolio receives signal events, produces order events, and updates positions and holdings from fill events. The NaivePortfolio example tracks each symbol’s quantity, cash,…

BacktestingEquitiesPosition sizingRisk management
MQL5 code base

This document describes an automated strategy that enters when price breaks the high or low of a prior candle on a selected timeframe, from one minute through one month. The user can set an offset from that candle’s extreme and optionally apply…

FuturesBreakoutTechnical indicatorsRisk management
MQL5 code base

This document describes a simple forex tool for estimating how much a one-pip or one-point price move is worth in the trader’s deposit currency. The user supplies the intended lot size, and the calculator reports the value for the currency pair displayed on…

ForexPosition sizingRisk management
BigQuant

The article argues that widely used price-based stop rules can cluster orders around obvious levels, where sudden moves may trigger many exits. It recommends shifting attention from a fixed loss percentage on each position to a preset total loss budget, with…

Risk managementPosition sizingEquities
MQL5 code base

This MetaTrader expert advisor uses the Average Directional Movement Index to generate trading signals. Its two main indicator settings are the ADX smoothing period and an ADX level. The advisor can place stop-loss and take-profit orders, and trailing of…

ForexTechnical indicatorsRisk managementPosition sizing
FMZ forum

The article explains why a strategy can make money without winning more often than a coin toss. It contrasts high-win-rate approaches, which seek frequent small gains, with high reward-to-risk approaches, which tolerate more losing trades in pursuit of…

StatisticsRisk managementPosition sizingBacktesting
MQL5 code base

This expert advisor combines Renko-style price boxes with fractal levels. It calculates box formation in pips, then enters when price reaches a level associated with a fractal. The post says the boxes are calculated rather than displayed on the chart and…

ForexEquitiesTechnical indicatorsPosition sizing
BigQuant

This excerpt argues that risk control and position sizing deserve priority alongside stock selection and timing. Its proposed framework smooths risk decisions with a moving-average tracking system and calculates a daily score from market or stock…

Risk managementPosition sizingTrend followingTechnical indicators
MQL5 code base

OverHedgeV2 is described as an expert advisor that manages a group of positions using aggregate and per-position profit thresholds. It closes positions opened by the advisor when the group reaches a total profit target, subject to a condition that no…

ForexTrend followingGrid tradingPosition sizing
MQL5 code base

The document describes an automated trading tool that takes a user-selected long or short direction, waits for a setup based on volume and price levels, and places trades. Its level and length settings shape the pullback it seeks and how extensively it…

ForexPosition sizingRisk managementExecution
MQL5 code base

This document outlines a way to hedge exposure to a dollar index using currency pairs associated with its constituent currencies. It lists component weights for the euro, yen, pound, Canadian dollar, Swedish krona, and Swiss franc, then maps those weights to…

ForexRisk managementPosition sizing
MQL5 code base

This expert advisor trades intersections between an RSI line and a moving average of RSI. A crossover below the midpoint generates a buy signal, while one above it generates a sell signal. Before entry, the advisor checks the distance from the nearest…

Technical indicatorsMean reversionPosition sizingRisk management
MQL5 code base

This brief description explains an expert advisor that acts on signals from a custom VIDYA N Bars Borders indicator. Before placing a signal-based trade, it checks current profit; when that profit is negative, it increases the trade lot according to a…

Technical indicatorsPosition sizingRisk managementForex
BigQuant

This example describes a daily, long-only futures strategy using a 10-period average crossing a 30-period average to generate entry and exit signals. A 120-period moving average acts as a trend filter: the strategy opens a position after an upward crossover…

FuturesTrend followingTechnical indicatorsBacktesting
BigQuant

The document outlines a workflow for building equity strategies that adapt their stock-selection logic to market conditions. It proposes measuring market sentiment with signals such as the number of limit-up stocks and average returns, then adding industry…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This post is a satirical warning about trusting impressive quantitative strategy claims and backtest curves. It points readers toward shared deep-learning strategy code, but supplies no description of the model, training data, signals, or validation process.…

BacktestingRisk managementPosition sizing
vn.py community

This VeighNa CTA example implements a two-sided grid that begins with equal long and short positions after its bar manager has initialized. It checks each completed 15-minute bar against a moving reference price, using a fixed distance between grid levels.…

FuturesGrid tradingPosition sizingExecution
SuperMind

This stock screen selects companies classified in the metaverse industry whose opening price is near the 10-day moving average and whose circulating share count is no more than 5.5 billion. The article presents both a crossover-style indicator condition and…

EquitiesChina marketsTechnical indicatorsPosition sizing