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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

175 documents

vn.py community

This brief forum exchange answers whether VeighNa, also known as vn.py, requires Tushare as the sole source of historical A-share data for backtesting. The response says the framework supports multiple data services and points readers to its documentation…

China marketsEquitiesBacktesting
vn.py community

This brief forum exchange answers a question about where log messages go during a backtest when using the BacktestingEngine. The questioner observes that the engine stores messages in a logs collection and asks how to access them. The reply says the messages…

Backtesting
vn.py community

This forum post raises implementation questions about historical data warm-up in VeighNa portfolio strategies. The author considers a strategy whose longest signal period is 20 days and asks whether an ArrayManager size of 25 is sufficient, and whether that…

BacktestingTechnical indicatorsExecution
vn.py community

This forum question examines why changing the initialization length of a trading system’s ArrayManager can materially alter a backtest. The strategy uses RSI generated through TA-Lib, and the author suspects that the indicator’s path dependence makes its…

BacktestingTechnical indicatorsRisk managementStatistics
vn.py community

A forum exchange clarifies whether a strategy can retrieve tick data for futures product indices or weighted continuous contracts, using iron ore and an example continuous symbol. The reply explains that symbols ending in a continuous-contract convention are…

FuturesMarket microstructureBacktesting
vn.py community

This release overview describes VeighNa 4.0 and its new vnpy.alpha module for developing machine-learning, multi-factor strategies. The module is organized around feature datasets, model training, strategy research, workflow management, and example…

Machine learningFactor investingEquitiesBacktesting
vn.py community

This forum post reports a VeighNa CTA backtest that reaches the historical-data loading stage but loads zero records. The script then completes initialization and replay with no trades, before result calculation fails because the daily results table lacks a…

FuturesBacktesting
vn.py community

The discussion describes a rolling-window backtest in which parameters are optimized on a sequence of historical months and then applied to the next month. As the test advances, the training window shifts forward by one month, so each new period is evaluated…

BacktestingStatistics
vn.py community

A short forum exchange asks how to obtain roughly two decades of historical futures and options data at hourly, daily, weekly, and monthly frequencies for backtesting. One reply says that such data must be purchased, particularly minute-level data. The…

FuturesOptionsBacktesting
vn.py community

This overview explains vn.py as a modular framework for automated trading. The MainEngine coordinates gateways, applications, databases, and data services, while the EventEngine routes market, order, and other messages to subscribed components. A typical…

ExecutionMarket microstructureBacktestingRisk management
vn.py community

This event outline describes a quantitative study of option spread strategies, with a focus on gold options. Topics include straddles and strangles, bull and bear spreads, butterfly spreads, and put-call parity. It proposes examining the structure of these…

OptionsCommoditiesBacktestingVolatility
vn.py community

The post asks why Alpha158 labels use different forward-return horizons in two implementations. It compares a label spanning the close at T+1 to the close at T+3 with a Qlib label spanning T+1 to T+2, then relates those choices to China’s T+1 stock-trading…

China marketsEquitiesBacktestingMachine learning
vn.py community

This forum exchange concerns changing a Turtle-style CTA strategy from a fixed number of contracts to dynamically calculated trade size based on risk. A user reports editing the strategy code through a backtest interface but seeing results continue to use…

FuturesBacktestingPosition sizing
vn.py community

The discussion addresses adding five- and fifteen-minute intervals to VN.py version 3.4.0 for backtesting. One reply suggests that when the source data is already stored at those resolutions, importing and selecting it as one-minute data can work because…

BacktestingExecutionFutures
vn.py community

This brief VeighNa forum exchange asks how to adjust bar construction for the morning futures market break from 10:15 to 10:30. A respondent explains that the BarGenerator currently divides data according to timestamps and asks which kind of bar the user…

FuturesBacktesting
vn.py community

The post raises a futures backtesting issue: unusually large drawdowns may coincide with price gaps when the lead contract changes. The author wants to identify roll dates and avoid trading on those dates, but the post does not provide a method for detecting…

FuturesBacktestingRisk management
vn.py community

This guide describes a workflow for moving historical daily futures bars from Ricequant into a local VeighNa database backed by MongoDB. It first uses Ricequant’s research environment to retrieve listed futures contracts and daily price fields over a chosen…

FuturesBacktesting
vn.py community

The forum exchange addresses whether a backtest for Shanghai Futures Exchange instruments needs to distinguish between closing a position opened the same day and closing one opened earlier. The question comes from a trader analyzing fill prices in a trade…

FuturesBacktestingExecution
vn.py community

This article walks through a deliberately random directional strategy for dYdX. It selects long or short entries with equal probability, uses fixed profit and loss thresholds to exit, and increases the next order size after a loss while resetting size after…

CryptoFuturesBacktestingRisk management
vn.py community

This forum exchange clarifies how VeighNa’s CTA strategy state file is used during initialization. A strategy first derives variable values from historical data and indicators, then reads saved JSON data to overwrite corresponding strategy variables.…

FuturesBacktestingStatistics
vn.py community

This short forum exchange describes a backtesting issue in VeighNa: several built-in strategies reportedly generated many trades that closed at a price of zero when using data from the Wind Python API configured through VN Station. A respondent suggests that…

BacktestingExecution
vn.py community

This Chinese research summary examines whether intraday data can support sector rotation signals, focusing on realized skewness and the share of volatility attributable to downside moves. It describes constructing industry level factors inspired by high…

China marketsEquitiesHigh-frequency tradingVolatility
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
vn.py community

A forum user reports an integer overflow error while backtesting options with a trading platform’s OptionStrategy module. The problem reportedly occurred only for CSI 300 ETF options and on two specific dates. The user traced the error to loading the…

OptionsBacktesting