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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 brief indicator note defines Leadlag as a comparison between two exponential moving averages of closing prices. It takes closing price data and two period parameters, one for the lead line and one for the lag line. The supplied pseudocode calculates…

技術指標股票
BigQuant

The article investigates why XGBoost training took far longer in some Python process setups than with joblib’s loky backend. Its experiments compare direct execution and several multiprocessing approaches, then identify the OpenMP thread limit as the key…

機器學習統計回測
BigQuant

This BigQuant backtest handler describes a daily portfolio process driven by a date-filtered prediction ranking. It allocates roughly one holding-period fraction of portfolio value to daily purchases during an initial staging phase; afterward, it can use up…

股票機器學習投資組合建構交易執行
BigQuant

This report studies whether active-buying measures derived from high-frequency trading data can help rank industries for rotation. It constructs buy-share, buy-intensity, net-buy-share, and net-buy-intensity factors using volume and turnover data from the…

中國市場股票因子投資投資組合建構
BigQuant

This research note assesses China’s consumer recovery under normalized pandemic controls, using a combination of policy text analysis and indicators of aggregate spending, passenger flows, cinema attendance, and physical store counts. It argues that…

中國市場股票事件驅動統計
BigQuant

This brief note identifies two errors in the conditions used by a stock strategy example. The first concerns a year-over-year net profit growth factor: the intended filter selects positive growth rather than negative growth. The second concerns position…

股票因子投資回測
BigQuant

The article explains why investment teams need to understand how machine-learning models produce decisions, especially when those decisions affect clients, risk controls, or deployment choices. It contrasts inherently interpretable approaches, such as linear…

機器學習統計風險管理
BigQuant

This 2020 research summary compares valuations and return drivers across large- and small-cap Chinese equity indexes. It reports that small-cap valuations were near historical medians while large-cap indexes, including the SSE 50 and CSI 100, were near…

股票中國市場因子投資統計
BigQuant

The document is a user’s question about calculating three-day and five-day moving averages within a custom feature factor on a quantitative trading platform. It asks how to use lagged close-price fields such as the current-day close, how rolling mean…

股票技術指標
BigQuant

The document defines the Sharpe ratio as a way to assess a portfolio or strategy’s excess return relative to the variability of its returns. It gives the calculation: subtract the risk-free rate from average portfolio return, then divide by the standard…

統計風險管理
BigQuant

This research summary reviews academic momentum-factor development and reports empirical findings for China’s A-share market. It says traditional momentum measures there exhibit reversal, with stronger reversal over shorter formation windows, and that…

股票中國市場動能因子投資
BigQuant

This report excerpt discusses forecasting equity factor returns as commonly used stock-selection factors fluctuate. It proposes improving and simplifying an earlier conditional-expectation timing model by framing factor timing as a regression-based…

因子投資股票統計投資組合建構
BigQuant

This research note studies post-earnings-announcement drift in Chinese A-shares: stocks reporting results above expectations may continue to earn positive abnormal returns, while those below expectations may lag. It estimates expected net profit and revenue…

股票中國市場事件驅動因子投資
BigQuant

This stock-selection proposal combines a daily price-range threshold, afternoon large-order inflows and a closing price between the Bollinger middle band and upper band. The document gives formulas for the range and band conditions, describes a…

股票技術指標波動率中國市場
BigQuant

The document raises a modeling question about predicting whether a future price move is positive using a label that takes only two values. The label compares a later close with an earlier open and assigns one class for an increase and the other for a…

機器學習統計股票
BigQuant

The document reports a discrepancy in a Chinese stock-status data table for one security on a specified historical date. A query against the table returned a status identifying the stock as *ST, while the author says the company was no longer classified that…

股票中國市場回測統計
BigQuant

The report adapts William O’Neil’s base-pattern and CANSLIM ideas to the Chinese A-share market. It combines price formations such as cup-with-handle and double bottoms with company growth measures, relative price strength, trading activity, and…

中國市場股票突破動能
BigQuant

The document explains how performance attribution can reveal the sources of a portfolio’s returns, even when portfolios have similar styles and overall results. It outlines three approaches: style analysis, which uses portfolio and benchmark returns to infer…

因子投資投資組合建構風險管理
BigQuant

This article presents a time-series momentum strategy that switches between a short lookback signal and a longer one according to market volatility. The short signal uses one month of returns and the slow signal uses twelve months; each takes a long or short…

動能機器學習波動率回測
BigQuant

This article outlines a systematic trend-following approach commonly called the Turtle method. It describes choosing liquid markets, using average true range (ATR) as a volatility measure for position sizing, and entering on Donchian channel breakouts. The…

期貨趨勢追蹤突破波動率
BigQuant

The document explains how to build trading agents within a strategy framework. It describes a workflow in which research agents gather market evidence and a dedicated trading agent can submit orders, while deterministic Python can enforce fixed execution and…

機器學習回測交易執行風險管理
BigQuant

This strategy ranks the mainland China A-share universe using company size and a price momentum measure. It removes suspended and specially treated shares, calculates a market-cap rank and the ratio of 20-day to 60-day average closing prices, and adds the…

股票中國市場因子投資動能