Lumaktaw papunta sa nilalaman

Library ng kaalaman

Mga buod at mahahalagang ideyang isinulat ng research agent ng Stratmill tungkol sa mga aklat, papel, artikulo at code na binasa ng aming mga AI agent. May link sa orihinal sa bawat pahina.

Quant Q&A
20,364 na dokumento
SuperMind
12,226 na dokumento
OKX Learn
8,431 na dokumento
Strategy library
7,910 na dokumento
MQL5 code base
7,090 na dokumento
BigQuant
3,481 na dokumento
Bitget Academy
3,298 na dokumento
MQL5 articles
3,012 na dokumento
TradingView scripts
1,976 na dokumento
ProRealCode
1,507 na dokumento
Deribit Insights
1,232 na dokumento
Machine Learning for Trading
1,124 na dokumento
arXiv papers
1,033 na dokumento
Amberdata research
766 na dokumento
FMZ forum
682 na dokumento
FMZ digest
662 na dokumento
vn.py community
560 na dokumento
QuantInsti blog
511 na dokumento
Galaxy Research
340 na dokumento
QuantStart
246 na dokumento
Stratmill research code
219 na dokumento
Robot Wealth
195 na dokumento
NautilusTrader
191 na dokumento
Hummingbot docs
181 na dokumento
Paradigm research
175 na dokumento
Lumibot
164 na dokumento
Kraken Learn
163 na dokumento
Library ng mga kurso sa quant
157 na dokumento
OctoBot
152 na dokumento
Cryptohopper blog
144 na dokumento
Systematic trading blog (Rob Carver)
132 na dokumento
Qlib
116 na dokumento
Quantpedia
86 na dokumento
TqSdk
86 na dokumento
Hyperliquid docs
79 na dokumento
Freqtrade
68 na dokumento
Hudson & Thames
62 na dokumento
Awesome Systematic Trading
61 na dokumento
backtrader
54 na dokumento
vn.py
50 na dokumento
Mga lecture ng Quantopian
45 na dokumento
Binance API docs
45 na dokumento
FMZ guides
38 na dokumento
pysystemtrade
34 na dokumento
Freqtrade docs
32 na dokumento
quant-trading
31 na dokumento
FinRL
28 na dokumento
Zipline
22 na dokumento
FMZ live strategies
21 na dokumento
Jesse
17 na dokumento
pyfolio
16 na dokumento
Alphalens
14 na dokumento
WonderTrader
14 na dokumento
backtesting.py
11 na dokumento
Technical Analysis
9 na dokumento
QTPyLib
8 na dokumento
QuantRocket
7 na dokumento
Lumibot strategies
7 na dokumento
Awesome Quant
1 na dokumento

Maghanap sa library

50 na dokumento

vn.py

The document introduces Zhice, a strategy research workspace within VeighNa Fusion. It describes a staged workflow that takes a user's trading idea through clarification of the logic, code drafting and review, backtesting, parameter optimization, and results…

Machine learningBacktestingPamamahala ng panganib
vn.py

This example demonstrates a portfolio-strategy backtest for a pair trading strategy on two Dalian Commodity Exchange continuous contracts. It configures minute data over a specified historical interval and supplies commission rates, slippage, contract sizes,…

FuturesPairs tradingBacktestingPagpapatupad ng trade
vn.py

The document describes a software workflow for managing option volatility strategies. It covers model selection for European and American options, choosing a futures or synthetic underlying, monitoring option quotes and Greeks, and calibrating pricing…

Mga optionVolatilityPagpepresyo ng derivativesPamamahala ng panganib
vn.py

This VeighNa guide compares database choices for storing trading data, including embedded SQLite, relational systems such as MySQL and PostgreSQL, and non-SQL options such as MongoDB, InfluxDB, DolphinDB, Arctic, and LevelDB. It describes their broad storage…

Maraming assetMicrostructure ng merkadoPagpapatupad ng tradeBacktesting
vn.py

This data-preparation example builds a historical dataset for research on the CSI 300 and its constituent stocks. It retrieves the index membership history over a selected date range, converts provider-specific exchange symbols to the format used by the…

Mga merkado sa ChinaMga equityBacktesting
vn.py

This document describes a guided process for turning a trading idea into a strategy that can be reviewed and tested. It moves through defining the idea, drafting and confirming its logic, generating and checking code, running a backtest, planning parameter…

BacktestingPamamahala ng panganibPagtatakda ng laki ng posisyon
vn.py

This Python example describes a process manager for a CTA futures strategy using vn.py and the CTP gateway. A parent process checks the clock and launches a child process during configured daytime and overnight trading windows. The child creates the event…

FuturesPagpapatupad ng tradeMga merkado sa China
vn.py

This document explains a graphical workflow for researching CTA strategies with historical data. It covers downloading market data, configuring a backtest with instrument details and trading costs, and reviewing equity, drawdown, daily profit and loss, and…

BacktestingFuturesEstadistikaPamamahala ng panganib
vn.py

This notebook outlines a daily equity research workflow using CSI 300 constituents. It loads historical bars, builds an Alpha158 feature dataset, and defines training, validation, and test periods. The target is a forward VWAP return over a three-day…

Mga equityMachine learningBacktestingMga merkado sa China
vn.py

This document outlines a workflow for assembling historical data for a CSI 300 research project. It downloads historical constituent information, retrieves the index membership for each trading date, converts vendor symbols into vn.py format, and saves the…

Mga equityMga merkado sa ChinaBacktesting
vn.py

This guide explains how to use VeighNa’s CTA strategy module to load strategy classes, create instances, initialize them with historical data, and start or stop automated trading. It describes how instances can trade different futures contracts with separate…

FuturesPagpapatupad ng tradePamamahala ng panganibBacktesting
vn.py

This guidance explains why AI-generated strategy logic, code, reviews, backtests, and parameter recommendations should be treated as research aids rather than final trading decisions. Outputs may contain errors or omissions, vary across models or settings,…

Machine learningBacktestingPamamahala ng panganib
vn.py

This example runs two existing futures strategies independently, using separate instruments, date ranges, trading costs, contract sizes, and capital settings. It then adds their result data frames, removes missing rows, and passes the combined data to a…

FuturesBacktestingPagbuo ng portfolio
vn.py

This workflow demonstrates an equity prediction pipeline using CSI 300 constituent data, Alpha158 features, and a multilayer perceptron. It defines training, validation, and test periods, prepares constituent-filtered data, normalizes features using robust…

Mga merkado sa ChinaMga equityMachine learningBacktesting
vn.py

This documentation explains how to load and operate VeighNa’s CTA strategy module. It covers adding strategy instances, selecting contracts and parameters, loading historical data, restoring saved variables, subscribing to market data, and enabling automated…

FuturesPagpapatupad ng tradePamamahala ng panganib
vn.py

This reference catalogs calculation functions available in the VeighNa Elite Trader CTA module. It groups common tools by their required inputs and outputs, covering moving averages, momentum and rate-of-change measures, volatility, trend strength and…

Mga teknikal na indicatorFuturesPagpapatupad ng trade
vn.py

The document explains how historical market data supports CTA strategy initialization, backtests, parameter optimization, and research. It outlines importing externally sourced data into a local environment and recommends checking file reliability, timestamp…

BacktestingFuturesPamamahala ng panganib
vn.py

This guide describes a user interface for running execution algorithms and explains how to configure an order’s instrument, side, price, quantity, duration, interval, and open-or-close instruction. It focuses on order execution rather than deciding what to…

Pagpapatupad ng tradeMicrostructure ng merkadoFuturesPamamahala ng panganib
vn.py

This operational guide explains how to connect a VeighNa Fusion account to a CTP futures interface and check that contract lookup, market-data subscription, and order functions are working. It outlines prerequisites such as obtaining the correct broker…

FuturesPagpapatupad ng tradeMicrostructure ng merkado
vn.py

The document explains how VeighNa’s PaperAccount module simulates trading against live market data while keeping orders local. It supports limit, market, and stop orders, with configurable slippage for market and stop executions. Orders generally wait for…

Pagpapatupad ng tradeMicrostructure ng merkadoPamamahala ng panganibBacktesting
vn.py

This workflow demonstrates an end-to-end daily equity modeling process using CSI 300 constituents and vn.py’s AlphaLab tools. It loads constituent histories, builds an Alpha158 dataset, and divides observations into training, validation, and test periods.…

Mga equityMachine learningEstadistikaBacktesting
vn.py

The document explains a plugin-based pre-trade risk module for VeighNa trading systems. Its built-in rules can cap active orders and daily order, cancel, and trade counts; detect repeated identical orders; limit order size or notional value; and validate…

Pamamahala ng panganibPagpapatupad ng tradeFuturesMga merkado sa China
vn.py

The document explains how VeighNa’s RPC service lets one trading process act as a server for separate client processes. Using ZeroMQ, the server accepts requests such as market-data subscriptions, orders, cancellations, and account queries, while…

Pagpapatupad ng tradeMicrostructure ng merkadoPamamahala ng panganib
vn.py

This notebook outlines an end-to-end equity alpha research workflow for CSI 300 constituents. It loads daily constituent data, constructs an Alpha158 dataset, divides observations into training, validation, and test periods, applies missing-label removal and…

Mga equityMga merkado sa ChinaMachine learningBacktesting