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

3,481 份文件

BigQuant

The discussion addresses how to feed minute-frequency market data into an AI stock-ranking workflow. Its answer is to replace the stock ranker template’s basic feature extraction step with direct data-source extraction, because minute data does not come with…

股票機器學習高頻交易
BigQuant

This research summary reviews how unexpected U.S. monetary policy changes affected U.S.-registered stock and bond mutual funds from 2009 through early 2017. It measures policy surprises using narrow-window changes in Treasury yields around Federal Open…

多資產固定收益股票統計
BigQuant

The report estimates stock-specific volatility from residuals in CAPM, Fama-French three- and five-factor, and Carhart four-factor models, then studies its role in China’s A-share market. It describes a low-volatility portfolio that equally weights stocks in…

股票波動率因子投資投資組合建構
BigQuant

This market note evaluates several indicators for judging whether Chinese equities may be approaching a short-term bottom. It reviews northbound investor flows, fund equity exposure, and a turnover-to-volatility measure. The note reports that foreign…

股票中國市場市場情緒統計
BigQuant

The document summarizes a simplified market impact model for large investment portfolios. It builds on an Almgren-style impact function whose nonlinear power form can make portfolio optimization slow and can leave uncertainty about whether the numerical…

市場微結構投資組合建構交易執行風險管理
BigQuant

The document explains how cross-validation estimates whether a statistical or machine-learning model can predict data beyond its training sample. It describes ordinary k-fold validation, in which data is split into folds and each fold is used in turn for…

機器學習統計回測
BigQuant

This research note examines Chinese property developers through their business mix, financial statements, operating efficiency, leverage, and return on equity. It groups developers by scale and argues that inventory turnover and debt repayment capacity…

股票中國市場因子投資回測
BigQuant

This stock-selection method looks for shares with a daily high-low range above 1, turnover between 2% and 9%, and a rising five-day moving average over several consecutive observations. The combination uses price range and turnover as proxies for market…

股票技術指標動能風險管理
BigQuant

The post describes a modified Chinese stock selection strategy that combines changes in executive shareholdings or share repurchase cancellations with momentum ranking. Its author reports that backtest return and drawdown metrics look acceptable, yet spot…

中國市場股票動能事件驅動
BigQuant

This brief troubleshooting note explains why sorted results may contain duplicate entries when working with Shenwan industry classifications. The platform provides two versions of the classification: an earlier version and one revised in 2021. The revision…

股票中國市場
BigQuant

This study examines the shift from reversal toward momentum in Chinese A-shares, especially among stocks favored by institutions. It compares several ways to measure price strength: conventional lookback returns, returns excluding limit-up days, daily-rank…

股票中國市場動能因子投資
BigQuant

This report explains the structure of US retirement savings, focusing on employer defined contribution plans, defined benefit plans, and individual retirement accounts. It describes the 401(k) as a participant-directed plan supported by tax advantages and…

多資產投資組合建構美國市場
BigQuant

This Chinese-language post outlines an equity screening rule: select stocks with RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and a rising 30-day moving average. The stated rationale is to combine a momentum or…

股票技術指標動能中國市場
BigQuant

This tutorial develops the Markowitz efficient frontier from mean-variance analysis, describing the minimum-variance portfolio, the maximum-Sharpe portfolio, and combinations that form the efficient set. It explains how forecasts of asset returns and a…

投資組合建構統計風險管理回測
BigQuant

This report summary distinguishes active quantitative mutual funds from index enhancement and quantitative hedging products. Active quant funds generally face less stringent tracking error limits than index enhancement funds and typically use long-only…

股票中國市場因子投資投資組合建構
BigQuant

The article argues that quantitative funds may exclude China’s specially treated A-share stocks because of trading constraints, limited strategy capacity, weak liquidity, and severe downside risks. It says restrictions on financing and securities lending…

股票中國市場風險管理市場微結構
BigQuant

The study examines whether news and social-media sentiment relate to intraday stock liquidity and returns. It combines stock-linked news sentiment with minute-level Twitter and StockTwits measures, then uses regressions and event studies to analyze liquidity…

股票均值回歸市場情緒回測
BigQuant

The note explains how to interpret the rank_amount and rank_amount_20 features in a stock data set. It corrects the assumption that a 20-day rank is an integer from 1 to 20: the described rank_amount value is a cross-sectional percentile, comparing each…

股票統計
BigQuant

This guide explains how to configure a genetic programming module to search for trading factors from supplied market data and input features. Users choose a market and data frequency, return field and horizon, time splits, fitness measure and thresholds,…

機器學習因子投資期貨股票
BigQuant

A user reported a training error despite having a dataset described as containing 115,478 rows. The discussion identifies a possible cause: at least one factor had the same value across all samples. According to the reply, the older version of the stock…

機器學習股票統計
BigQuant

This document describes a market timing model for the CSI 300 based on the Guosen Investor Sentiment Index. It adapts a risk appetite approach by comparing 28 Shenwan first-level industries. The proposed index uses the Spearman rank correlation between…

股票市場情緒中國市場統計
BigQuant

This example stock-selection strategy looks for a bullishly ordered moving-average structure: the 5-day average must exceed the 10-day, then the 20-day, 40-day, and 120-day averages. Among those stocks, it identifies a pullback when the day's low falls below…

股票中國市場趨勢追蹤技術指標
BigQuant

This report studies cross-sectional, market-neutral long-short strategies in commodity futures using inventory deviation and price momentum. The inventory signal measures how far a commodity’s stock level is from its trend; the strategy buys relatively…

大宗商品期貨動能趨勢追蹤
BigQuant

The document summarizes a research paper on predicting stock returns by modeling momentum spillovers between related companies. It argues that conventional graph neural networks depend on predefined links, such as industry or ownership, and may pass…

股票動能機器學習統計