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
Quantpedia
86 份文件
TqSdk
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
Quantopian 講座
45 份文件
Binance API docs
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

3,481 份文件

BigQuant

This study describes active risk parity as a portfolio built around a risk-parity allocation, with controlled deviations based on investment views. In its two-asset example, Chinese equities and corporate bonds are rebalanced using rolling covariance…

多資產投資組合建構風險管理動能
BigQuant

This research summary describes stock-selection factors built from tick-level aggressive buy and sell amounts. It applies an informed-trading probability model to filter noisy order flow, then forms informed sell share, informed buy share, and net informed…

股票因子投資市場微結構統計
BigQuant

This overview contrasts efficient markets, where prices are assumed to incorporate available information, with inefficient markets, where prices may diverge from estimated value. It outlines the weak, semi-strong, and strong forms of the efficient market…

統計套利配對交易市場情緒
BigQuant

This research summary examines factor weighting, orthogonalization, and timing through the relationship between composite information-coefficient weighting and Fama–MacBeth regressions. Under the stated condition that returns and factors are z-scored, it…

因子投資統計投資組合建構
BigQuant

The article describes adding a trailing stop to a stock selection and rotation workflow. Its example sells a holding when the latest price falls more than 10% from the highest price observed since purchase. It recommends tracking stop-triggered stocks,…

股票風險管理交易執行
BigQuant

This personal account discusses trading strong Chinese stocks during a broad market decline. The author describes using stock-ranking models to pursue strong stocks, next-day rebounds after pullbacks, and limit-up leaders, while emphasizing that these…

股票中國市場動能風險管理
BigQuant

This meetup compilation surveys practical topics in quantitative investing, including factor design, machine learning, strategy validation, portfolio sizing, live execution, and sector rotation. It recommends building a factor library by collecting and…

因子投資機器學習回測投資組合建構
BigQuant

The document describes a library that packages deep learning models for quantitative research, including feedforward networks, LSTMs, Transformers, TabNet, and TRA. Its quick-start workflow covers selecting a model, configuring an optimizer and loss…

機器學習股票回測
BigQuant

This A-share strategy narrows a stock universe in three stages: rank industry or concept indices by short- and medium-term momentum, select stocks with a current limit-up and a recent prior limit-up, then confirm strength after the open before buying.…

股票中國市場動能突破
BigQuant

This advice article presents five principles for surviving in stock trading: use technical analysis as context, follow established trends, keep short-term trades distinct from long-term investments, assess broad market direction, and protect capital by…

股票趨勢追蹤技術指標風險管理
BigQuant

This overview explains machine learning as a way to model patterns in data and describes how that capability may be applied to investment decisions. It outlines a workflow spanning data collection, feature creation, preprocessing, model training, model…

機器學習統計股票
BigQuant

This note describes a reproduction of a sell-side factor based on overnight stock returns, intended to capture information advantages held by informed traders. It says the research defines the factor in stages, from a traditional overnight-return measure to…

股票中國市場因子投資回測
BigQuant

The article describes a research workflow that pairs a language model’s reading of crypto news with live exchange data. The agent identifies token mentions, retrieves current prices and four-hour candles, and can consult order books when warranted. It then…

加密貨幣市場情緒技術指標市場微結構
BigQuant

This 2020 market note reviews Chinese equity style performance and outlines a short-term outlook. It reports that small-cap reversal strengthened, value began to recover, and earnings-growth exposure showed a brief rebound. Its recommendations draw on…

股票中國市場均值回歸因子投資
BigQuant

This discussion distinguishes two approaches to Chinese A-share limit-up trading: a daily model that forecasts which stocks may hit the limit the next day, and an intraday model that uses current market information to identify candidates for the remainder of…

股票中國市場動能技術指標
BigQuant

A BigQuant user reports an apparent issue when a strategy sells before buying back to close a position. In the user's tests, buybacks above half of the initial capital fail, while smaller buybacks work. The report describes varying the amount used for the…

中國市場交易執行部位規模
BigQuant

This article summarizes a study of U.S. mutual funds that links SEC N-SAR options disclosures with fund returns and characteristics. The sample covers 1998 through November 2013 and includes 106,357 filings. Cross-sectional and panel analyses compare funds…

選擇權股票風險管理統計
BigQuant

The article explains why standard stochastic gradient descent can remain inefficient when training Word2Vec on a large vocabulary. Even when an update concerns only a few words, calculating gradients across the full parameter matrices wastes work, and the…

機器學習統計
BigQuant

This brief support exchange addresses whether a strategy’s data is standardized anew each day during simulated trading. The response says that when the strategy uses parameters bound for live trading, simulated trading standardizes that day’s data. A…

統計回測
BigQuant

This document explains a reverse-doubling strategy designed for an older crypto-margined futures venue. It focuses on the strategy’s control flow: open a position, place take-profit orders, monitor both profit-taking and reverse stop triggers, cancel…

加密貨幣期貨風險管理部位規模