跳至內容

知識圖書館

這裡收錄 Stratmill 研究代理對 AI 代理閱讀過的書籍、論文、文章與程式碼所寫的摘要與核心觀點。每個頁面都連結至原始資料。

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

搜尋圖書館

32 份文件

Freqtrade docs

The document explains FreqAI’s main software components and how they support model development. A persistent model object handles data collection, feature engineering, training, and inference; a per-asset data kitchen provides processing tools and metadata;…

機器學習加密貨幣回測
Freqtrade docs

The document explains how FreqAI trains trading agents through reinforcement learning. An agent processes historical candles and chooses among actions such as entering or exiting long and short positions. A custom reward function scores its decisions, while…

機器學習風險管理回測
Freqtrade docs

The guide explains how to enable public trade downloads in Freqtrade and configure order flow processing. Settings control cached candles, trade history depth, footprint price-bin size, and the volume and ratio thresholds used to identify imbalances.…

市場微結構交易執行回測統計
Freqtrade docs

This quick start explains how a Freqtrade strategy turns exchange candle data into indicators, entry and exit signals, and orders. A strategy is implemented as a Python class with separate methods for calculating indicators and populating long or short…

加密貨幣技術指標回測交易執行
Freqtrade docs

The document explains how to inspect backtest performance by entry and exit reasons in Freqtrade. It describes exporting signal data, then grouping trade outcomes by entry tag, exit tag, and pair. These views range from an overall summary to detailed pair…

回測統計技術指標
Freqtrade docs

This guide explains how to download and maintain historical market data for strategy backtesting and hyperparameter optimization. It covers choosing pairs, timeframes, exchanges, and date ranges; refreshing existing datasets incrementally; and adding earlier…

回測加密貨幣期貨現貨市場
Freqtrade docs

The document explains how Freqtrade’s Hyperopt process searches strategy parameter combinations by repeatedly backtesting historical data. It begins with random combinations and then uses an Optuna sampler to explore parameter spaces while minimizing a…

回測機器學習風險管理
Freqtrade docs

This documentation explains how to start Freqtrade and select the configuration, strategy, data directory, and database used by a bot run. It outlines command-line options for live or simulated trading, including dry-run balance and fee settings, and notes…

加密貨幣交易執行回測