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
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 article introduces alpha and beta through market and multifactor models, describing alpha as return unexplained by modeled risk exposures. It explains how active portfolios might seek positive alpha while keeping factor exposures aligned with a…

因子投資投資組合建構統計風險管理
BigQuant

This document explains the PB-ROE framework as a valuation relationship: higher expected return on equity is associated with higher price-to-book multiples, with log PB described as linearly related to expected ROE. It reviews the theoretical basis and…

股票因子投資統計回測
BigQuant

This document profiles the China Securities Consumer Leaders Index, which selects 50 large, higher-quality companies from the discretionary and staple consumer sectors across the Shanghai and Shenzhen markets. It is intended to represent leading consumer…

股票中國市場因子投資
BigQuant

This study describes using the CCK model to identify herding in Chinese equity indices. Herding is associated with constituents moving in the same direction: their return correlations rise while the cross-sectional dispersion of returns falls. The analysis…

股票統計中國市場回測
BigQuant

This forum exchange addresses an error encountered when adding a code-list module to a factor analysis workflow. The reply explains that the code-list module returns a dictionary rather than a DataSource object, which is the type expected by the factor…

因子投資股票統計
BigQuant

This forum question compares the first dates that three rolling SQL calculations return values: a moving average, a standard deviation, and a regression slope, each configured with a 40-observation window. The example applies them to stock data and reports…

統計股票
BigQuant

Maximum drawdown measures the largest percentage decline from a previous peak to a later trough over a chosen observation period. The document gives the formula and explains that the peak must come before the trough, then walks through a stock price sequence…

統計風險管理
BigQuant

A user asks about an error in a shared quantitative strategy. The response points to a mismatch between the data universe and the requested features: index data does not provide certain return and price fields that are available for stocks, futures, or…

機器學習統計
BigQuant

This article discusses the difficulties faced by quantitative index-enhancement funds after a period of rapid product launches and asset growth. It reports that some funds failed to generate positive alpha, lagged their benchmarks, or experienced declines in…

股票因子投資風險管理投資組合建構
BigQuant

This brief BigQuant post reports a test combining rolling model training with LightGBM and an experimental factor described as “暗流涌动” (roughly, hidden currents). The author says the factor's standalone effect is not prominent, but it may contribute something…

機器學習因子投資回測
BigQuant

This short BigQuant support note addresses a rolling-training workflow failure. It explains that a custom module was continuing to read data from an earlier module instead of receiving data that changed with the rolling time window. As a result, a later…

機器學習回測
BigQuant

This article explains sharp intraday stock rallies through changes in order book liquidity. It argues that price movement depends less on aggregate figures for aggressive buying and selling than on whether market buys consume the resting sell orders ahead of…

股票市場微結構交易執行中國市場
BigQuant

This note proposes an equity factor that adds cross-sectional percentile ranks for year-over-year growth in recent net profit, the negative of a ten-period turnover sum, and the negative of total market capitalization. The intended interpretation is that…

中國市場股票因子投資回測
BigQuant

This commodity research framework organizes iron ore price drivers into fundamental supply, demand, and inventory factors, alongside a separate sentiment category. It discusses practical handling of slower and irregularly updated fundamental data, including…

大宗商品期貨趨勢追蹤統計
BigQuant

The report groups stocks into seven broad sleeves, including financials, technology and media, consumer, cyclical, manufacturing, healthcare, and Hong Kong equities. It examines active domestic equity fund allocations, noting shifts away from consumer stocks…

股票中國市場回測
BigQuant

This research summary describes a method for grouping stocks with similar price behavior so that an investor can substitute one holding for another within a group. It builds on a grouping genetic algorithm, representing groups, stocks, and portfolio…

股票機器學習投資組合建構統計
BigQuant

The note examines an attempted A-share stock-selection strategy that combined dividend yield and price-to-sales signals with equal scoring weights while retaining both screens. The author reports that the combined strategy backtested substantially worse than…

股票因子投資回測中國市場
BigQuant

This brief BigQuant support exchange addresses a runtime error stating that a NoneType value is not iterable. The answer attributes the problem to data containing missing or abnormal values, such as absent factor values or gaps in the underlying data. It…

統計回測
BigQuant

This Chinese equity screen combines a daily price-range condition, a reversal pattern, and opening-auction activity. It first filters for stocks whose high-to-low range exceeds one percent, then looks for a reversal, and finally ranks qualifying names by…

股票動能技術指標交易執行
BigQuant

More Chan Theory is presented as a practical simplification of Chan-style price analysis. It drops the traditional recursive pen-and-segment hierarchy, using two levels: the current-level pivot and lower-level segments. The method uses MA5 and MA34 to help…

技術指標趨勢追蹤突破中國市場
BigQuant

This programming note explains how to keep a rolling cache of recent bars for use in strategies that calculate time-series indicators from live data. A bounded array is updated from bar callbacks, and strategy logic waits until the cache is initialized…

技術指標交易執行高頻交易
BigQuant

This research note organizes convertible-bond factors into three groups: factors from the underlying stock, factors describing the bond-stock relationship, and the convertible bond’s own price and volume behavior. It reports that earnings yield and…

固定收益選擇權因子投資回測
BigQuant

This research overview presents a framework for studying high-frequency equity factors, emphasizing both incremental information and the economic logic behind observed returns. It uses linear models, factor statistics, and portfolio backtests to assess a…

股票高頻交易因子投資均值回歸
BigQuant

The article describes a workflow for finding S&P 500 healthcare companies that develop or use AI. It filters the index by industry, gathers recent company news, and uses a large language model to summarize products, technologies, and research activity.…

股票機器學習投資組合建構市場情緒