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 note describes a stock-selection and rotation approach built around buying shares judged to be at relatively low price levels. A scoring system ranks candidates; the strategy buys higher-ranked stocks and holds five positions. As a holding rises, its…

股票均值回歸因子投資投資組合建構
BigQuant

This troubleshooting note describes a simulation failure in a single-stock AI ranking strategy: the pipeline reports that no data remains after missing values are removed, even though the strategy completes a backtest. It suggests checking whether the data…

機器學習回測交易執行
BigQuant

The document describes a buy-sentiment factor built by distinguishing aggressive purchases, which execute against sell orders already on the book, from passive purchases, which wait as limit orders for incoming sells. It argues that finer-grained market data…

股票市場情緒市場微結構因子投資
BigQuant

This research review describes a dynamic, out-of-sample process for selecting US active equity mutual funds from observable fund characteristics. It compares elastic net, random forests, gradient boosting, and linear regression. Each year, models are trained…

機器學習投資組合建構因子投資回測
BigQuant

The post argues that factor research can use information from later minutes within the same trading day when constructing a daily-frequency factor, provided the factor does not use data from the following day. It proposes examining relationships between…

股票因子投資統計回測
BigQuant

This study tests whether investors can improve a diversified global equity factor portfolio by adjusting factor weights with time-series signals or cross-sectional characteristics. It applies parameterized portfolio policies to twenty long-short equity…

股票因子投資動能投資組合建構
BigQuant

This research summary compares seven ways to identify active mutual funds with positive, negative, or zero risk-adjusted performance. It explains a factor-model benchmark and methods that adjust for multiple testing, including bootstrap and false discovery…

股票統計因子投資回測
BigQuant

The article presents market feel as a learned pattern-recognition skill, built by repeatedly observing price structure, volume changes, and trading behavior. It recommends focusing on three intraday periods, watching whether moves attract volume and support,…

股票技術指標統計中國市場
BigQuant

The report explains how the MSCI China A50 Connect Index is constructed and why its futures contract could help overseas investors manage A-share exposure. The index selects large free-float-adjusted stocks across GICS sectors, then adjusts weights to match…

期貨股票中國市場風險管理
BigQuant

This tutorial presents a workflow for evaluating a factor on Chinese equities, using the lower Bollinger Band as an example. It introduces factor analysis as a way to summarize variables and derive composite scores, then describes building daily factor data,…

因子投資股票中國市場統計
BigQuant

This research summary tests whether splitting stock volatility into components yields useful selection signals from high-frequency returns. The reported system-versus-idiosyncratic volatility split performs poorly at the one-minute sampling interval; its…

股票因子投資波動率統計
BigQuant

This BigQuant help response clarifies which data fields are available in its visual automatic stock-labeling module. It says the module directly supports only the standard open, high, low, and close price fields. A user asking about unavailable documentation…

股票機器學習統計
BigQuant

This research digest summarizes two studies. The first revisits the claim that small-cap stocks earn higher average returns than large-cap stocks, reviewing competing views about the size effect and describing simple tests with public data intended to…

股票因子投資統計
BigQuant

The document asks how to use a user-uploaded file as a feature in an LSTM trading strategy. The suggested approach is to pass the uploaded data through a data-source module and join it with the strategy’s existing data, making the added values available…

機器學習股票
BigQuant

The discussion addresses missing values from a rolling maximum over a fixed 1,000-day window when a stock has been listed for less than the full period. It proposes making the window length depend on the stock's available listing history: use the smaller of…

股票統計技術指標
BigQuant

This report examines listed Chinese securities firms as a cyclical, high-beta equity sector and presents a securities-company index as a way to track them. It describes the index as market-cap weighted, concentrated in its largest constituents, and composed…

中國市場股票回測
BigQuant

This platform discussion shows how to count Chinese stocks whose total market capitalization is below three billion yuan on each trading date. It queries daily stock-factor data for a selected date range, filters the rows by market capitalization, and groups…

股票中國市場統計
BigQuant

A user reports that custom normalization code works on its own but produces no result when run as a module. The response explains that the normalization step operates on cross-sectional data: it compares observations across securities at a given point in…

統計股票
BigQuant

This reading note summarizes two quantitative research papers. The first applies the thermal optimal path method, a nonparametric approach motivated by statistical physics, to study how stock indices and their futures lead or lag one another over time. The…

期貨股票統計機器學習
BigQuant

The supplied summary describes research on alternative data and a hiring-count signal for Chinese equities. It says overseas use of alternative data is still developing, with most applications aimed at short-term opportunities, and identifies six…

股票因子投資事件驅動回測
BigQuant

The discussion examines a sequence-window feature pipeline for stock data. If rows are filtered before a rolling window is formed, dates can disappear; a nominal three-row window may then combine observations that are not three consecutive days. The answer…

股票機器學習統計