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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

9,797 documents

WonderTrader

The example sketches a Python environment that connects a CTA backtesting engine to an agent-like training loop. It initializes a backtest, subscribes a strategy to five-minute bars, starts asynchronous execution, and advances the engine one step at a time.…

FuturesBacktestingMachine learning
ProRealCode

This post adapts the DeMarker oscillator into an on-chart display of possible reversal points. The indicator compares averaged upward high changes with averaged downward low changes and scales the result to a range from zero to one hundred. In the chart…

Technical indicatorsMean reversionFutures
SuperMind

These reading notes explain how futures can offset exposure to changes in commodity prices, exchange rates, or other market variables. A short hedge suits a party that benefits when an asset price rises and loses when it falls, such as a producer planning a…

FuturesRisk managementCommoditiesForex
vn.py community

This forum thread concerns a futures simulation account that connects successfully but receives no market data. A respondent suggests that the user may not have connected to the trading server, which is used to retrieve contract information. Another…

FuturesExecutionMarket microstructure
FMZ forum

This article explains how to make the lookback length in a range-breakout strategy vary with volatility. A fixed N-day breakout may enter quickly during strong trends but can produce repeated signals in sideways markets. The proposed adjustment compares a…

FuturesBreakoutTrend followingVolatility
vn.py community

This Chinese-language forum post asks how to import tick data into vn.py for backtesting when the graphical import interface appears to support only minute-level or coarser data. The author considers loading records into the database with custom code and…

FuturesBacktestingMarket microstructure
Stratmill research code

This example builds a BTCUSDT futures market-making strategy whose fair price is estimated from a spot reference price plus a smoothed spot–futures basis. It resamples spot and futures book-ticker mid-prices, carries observations forward, and calculates a…

CryptoFuturesMarket makingMean reversion
FMZ forum

This tutorial introduces the M Language used in a trading platform to write indicators and trading logic for commodity futures and cryptocurrency contracts. It explains scalar and sequence data, numeric, string, and Boolean values, variable naming, and…

FuturesCryptoTechnical indicatorsPosition sizing
vn.py community

This brief forum exchange clarifies directional order terminology in a trading interface. A buy-to-close order is described as an order whose direction is long and which closes a short position. Conversely, an order to open short corresponds to closing a…

ExecutionFutures
FMZ forum

This overview presents ten intraday breakout concepts. They use reference levels drawn from prior-session highs and lows, the opening price, an initial post-open range, recent consolidation, average price, or measures of historical and intraday ATR. In each…

BreakoutVolatilityTechnical indicatorsFutures
vn.py

This guide explains how to construct, monitor, and trade synthetic spreads in the VeighNa SpreadTrading module. A spread can combine several contract legs using a formula, including pricing legs that are not traded, which supports relationships involving…

FuturesCommoditiesArbitragePairs trading
vn.py community

This community exchange discusses a VeighNa live-trading strategy that uses imported local one-minute bars. The user asks whether a futures-style symbol such as rb2501 is recognized, reports an initialization error indicating that a data service is not…

FuturesExecution
FMZ forum

This essay argues that a trading system only helps when a trader can follow it and its demands fit the trader’s goals, temperament, and market. It outlines four recurring price structures—triangular consolidations, directional channels, ranges, and expanding…

FuturesTrend followingTechnical indicatorsRisk management
OctoBot

This guide explains a dollar-cost averaging trading mode for placing repeat entries and managing the resulting positions. Entries can be triggered on a schedule or when an evaluator produces a new maximum signal, defined as a value of -1 or 1. The guide says…

CryptoSpot marketsFuturesExecution
Lumibot

This FAQ describes LumiBot, a Python framework for backtesting and live algorithmic trading across several asset classes and brokers. It outlines the shared strategy workflow, data-source requirements, and common operations such as handling fills, tracking…

BacktestingMachine learningEquitiesOptions
BigQuant

This report summary compares cross-sectional, market-neutral commodity futures strategies based on inventory deviation and historical momentum. The inventory signal favors commodities with inventories below their own trend and shorts those above trend. It is…

FuturesCommoditiesMomentumTrend following
BigQuant

This overview outlines a quantitative workflow: collect and clean data, develop a strategy, manage risk, backtest on historical data, and automate execution. It then sketches strategies for Chinese equities and futures, including Turtle-style breakouts,…

EquitiesFuturesPairs tradingTechnical indicators
vn.py community

This forum exchange documents a connection problem between VeighNa's CTP interface and a Guangfa Futures simulation system. The user reports running a newer CTP interface build than the simulation system's stated version; connections to another simulation…

FuturesExecution
vn.py community

This forum exchange explains why recorded market data may not appear in VeighNa's data manager. It raises several possible causes: an invalid or mistyped contract symbol, recording ticks rather than bars, a delay before buffered data is written, or a lack of…

FuturesExecution
ProRealCode

This crude oil strategy uses 15-minute bars to combine a five-bar average of candle fullness with a moving average oscillator built from five- and 50-period averages. Candle fullness is defined as the close-to-open move divided by the candle’s high-low…

FuturesCommoditiesMean reversionTechnical indicators
TqSdk

This report utility converts daily account snapshots and trade records into tables, then calculates summary statistics for simulated futures accounts or stock accounts. For both account types it derives daily profit and returns, cumulative profit and loss…

BacktestingStatisticsRisk managementFutures
TqSdk

The document explains how to enable TqSdk’s browser-based chart interface by setting the API’s web GUI option. It describes using an automatically assigned local address or supplying a fixed address, then illustrates a live setup that subscribes to a futures…

FuturesBacktestingTechnical indicators
vn.py community

This brief forum exchange addresses a VeighNa user who connected to SimNow but received a message that no data service was available. A reply points out that the contract-query success message had not appeared before the module was started, and advises…

FuturesExecution