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

This research summary examines how sell-side analyst reports may inform stock selection. It argues that report counts and recommendation strength alone provide limited differentiation, while target-price upside and changes in analyst views may be more…

股票市場情緒事件驅動投資組合建構
BigQuant

This article surveys six implementation choices that shape equity factor strategies: selecting proxy measures, constructing portfolios, combining factors, allocating among them, trading, and managing risk. It argues that one factor can be represented by…

股票因子投資投資組合建構交易執行
BigQuant

This report reviews market conditions relevant to Chinese quantitative equity strategies in July 2022. It tracks the number of unstable factors as a proxy for how supportive conditions may be for strategy excess returns. The report says this count stayed…

股票中國市場因子投資市場微結構
BigQuant

This brief description introduces a reinforcement-learning lecture on the theoretical foundations of dynamic programming. It says the lecture studies dynamic-programming algorithms as contraction mappings and asks when and how those mappings converge to the…

機器學習統計
BigQuant

This paper summary examines whether historical trading data can predict the next month’s cross-sectional returns of Chinese A-shares. It describes a dataset of 108 stock characteristics from 1997 to 2019 and compares traditional econometric methods with six…

中國市場股票機器學習因子投資
BigQuant

The document studies a definition of an industry leader based on analyst coverage and strong links between a stock’s fundamentals and those of its industry peers. It describes the selected stocks’ general characteristics and examines whether their price…

中國市場股票因子投資統計
BigQuant

This article introduces XGBoost as a machine-learning method for quantitative stock selection using price and volume factors. It explains boosting as a process that adds weak learners in sequence, then contrasts AdaBoost’s reweighting of misclassified…

股票機器學習因子投資統計
BigQuant

This research summary examines whether stock return synchronicity—the degree to which a stock’s returns move with common factors—signals more or less information in prices. The conventional view treats high synchronicity as evidence of less firm-specific…

股票統計市場微結構美國市場
BigQuant

The document raises a portfolio-construction question about using a stock-ranking model to select both ends of its predictions: stocks with the highest factor scores and stocks with the lowest scores. The proposed idea is to hold the two groups together as a…

股票因子投資投資組合建構機器學習
BigQuant

This analysis compares analyst forecast data from two Chinese financial data providers, examining report coverage, forecast accuracy, and the usefulness of forecast-related factors in stock selection. One provider is described as covering more stocks, while…

股票因子投資統計中國市場
BigQuant

This article introduces support vector machines for classification and regression, then applies them to A-share stock selection. It explains the maximum-margin principle for linear SVMs, slack variables for imperfectly separable observations, and kernel…

股票機器學習統計回測
BigQuant

The document outlines a factor attribution framework for evaluating active equity funds within a fund of funds (FOF). It separates returns into broad risk exposures, such as market, style, and industry effects; alpha-factor contributions from technical and…

因子投資股票投資組合建構
BigQuant

This Chinese-language note estimates potential market upside across four equity groups: the CSI Bank sector, SSE 50, CSI 500, and ChiNext. Its framework considers fundamental trends, whether expected earnings growth supports current valuation, and the risk…

股票中國市場因子投資統計
BigQuant

This review summarizes research comparing highly rated ESG stocks with other stocks in US and developed international markets. It examines individual securities and randomly formed portfolios using MSCI ESG classifications and a Fama-French five-factor model…

股票因子投資投資組合建構風險管理
BigQuant

This Chinese-language event listing outlines a dynamic trading approach for timing exchange-traded funds. It identifies three components: selecting a pool of highly liquid ETFs, ranking candidates with multiple momentum dimensions, and adjusting the approach…

股票動能技術指標交易執行
BigQuant

This Chinese equity market report summarizes sector performance, index and industry valuations, market breadth, fund positioning, and an intermediate-term trend model. It reports that building materials, agriculture and forestry, utilities, light…

股票中國市場動能技術指標
BigQuant

This short Chinese-language note defines quantitative investing as using programs to invest based on collecting and analyzing substantial market data. It presents automation as a way to respond to market changes more quickly, follow a consistent process, and…

機器學習統計回測風險管理
BigQuant

The research summary argues that conventional earnings multiples may be weak valuation tools for property developers because project-based results can be uneven and past earnings may not predict future performance well. It proposes using inventory as a…

股票中國市場因子投資回測
BigQuant

This research summary examines China’s medical imaging equipment market and United Imaging’s position as a domestic supplier. It presents demand growth as supported by low equipment availability relative to developed markets and policy efforts to expand…

股票中國市場因子投資風險管理
BigQuant

This tutorial explains applying principal component analysis to stock returns to identify dominant co-movement patterns. It standardizes historical returns, estimates a rolling correlation matrix, and decomposes it into eigenvalues and eigenvectors. The…

股票中國市場機器學習統計
BigQuant

The document introduces TRIX, a technical indicator built by applying an exponential moving average to the closing price three times in succession. It also defines a companion line by taking a simple moving average of the resulting triple-smoothed series.…

技術指標股票
BigQuant

This research summary describes a method for predicting which stocks will attract institutional attention when other firms make scheduled announcements or when macroeconomic news arrives. It measures past attention spikes using news searches and reading…

股票事件驅動市場情緒統計
BigQuant

The article presents six discretionary rules for short-term trading: exit when a closing price falls below its five-day moving average, use a two-day moving average to judge the near-term trend, wait for preset entry conditions, and follow sell signals…

技術指標趨勢追蹤風險管理部位規模