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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
WonderTrader
14 份文件
Alphalens
14 份文件
backtesting.py
11 份文件
Technical Analysis
9 份文件
QTPyLib
8 份文件
Lumibot strategies
7 份文件
QuantRocket
7 份文件
Awesome Quant
1 份文件

搜尋圖書館

3,481 份文件

BigQuant

The article explains a four-part decomposition of market beta based on whether market and individual stock returns are positive or negative together. The components distinguish joint losses, joint gains, and the two mixed-sign cases. Using realized…

股票統計風險管理投資組合建構
BigQuant

This summary of a 2018 brokerage study examines whether capital-flow measures can help anticipate shifts among equity investment styles. It argues that raw fund-flow observations may add little beyond price and volume because those variables move together,…

股票因子投資投資組合建構統計
BigQuant

This article warns retail equity traders that fast algorithms may exploit order-flow speed differences, bursts of retail enthusiasm, and clustered stop levels. It illustrates possible behaviors: entering ahead of slower orders, buying into a sentiment-driven…

股票中國市場市場微結構交易執行
BigQuant

This study examines whether futures-curve shape can rank commodity markets. It explains backwardation, where deferred contracts are cheaper than nearer ones, and contango, where they are more expensive. The article connects these patterns to supply, demand,…

大宗商品期貨Carry(套息)因子投資
BigQuant

This platform support thread discusses how to preserve a model after rolling training and whether the final saved artifact represents the intended result. The replies characterize rolling training as a research-stage feature rather than a direct route to…

機器學習回測
BigQuant

The post contains a proposed monthly China A-share industry-rotation backtest. It ranks second-level industries by where current price-to-earnings ratios sit within their own rolling 60-session ranges, then selects six industries with the lowest relative…

中國市場股票因子投資回測
BigQuant

The article describes turning rolling OHLC windows into sparse, binary candlestick images for a convolutional neural network. Each sample uses 32 time steps, normalized and mapped onto a 128-by-128 grid; three columns represent each candle’s open, high-low…

股票機器學習回測技術指標
BigQuant

The article presents a speculative outlook for China’s A-share market in 2026. It anticipates a gradual upward market with a spring positioning period, a stronger phase from May through September, and a sharp interim pullback that it interprets as a possible…

中國市場股票投資組合建構風險管理
BigQuant

This research digest summarizes two distinct topics. For multi-factor index construction, it contrasts a top-down approach, which combines single-factor indexes using assigned proportions, with a bottom-up approach, which optimizes holdings to increase…

因子投資投資組合建構股票市場微結構
BigQuant

This forum post describes an exploratory factor-construction exercise in the Chinese A-share market. The author says a small modification to a factor combination produced strong short-side results, then describes a revised version that removed the short…

中國市場股票因子投資統計
BigQuant

The document outlines three ways to explain portfolio results: style analysis using return regressions, benchmark-relative return decomposition, and multi-factor attribution. It describes the data each approach needs, including portfolio and benchmark…

因子投資投資組合建構風險管理統計
BigQuant

This opinion article argues that quantitative trading has different effects across market structures. It contrasts a US market it characterizes as institutionally dominated with China’s A-share market, which it portrays as retail-heavy and more driven by…

中國市場股票市場微結構市場情緒
BigQuant

This review summarizes research on whether skilled active U.S. equity fund managers add more value when prices are noisier. It measures skill mainly through portfolio selectivity, proxied by one minus a fund’s return-model R-squared, and also uses a…

股票市場情緒統計風險管理
BigQuant

This report summary describes revisions to AlphaNet, a neural network that learns stock-selection factors directly from raw price and volume data. AlphaNet v2 adds six ratio features, replaces pooling and dense layers with an LSTM to capture temporal…

股票中國市場機器學習因子投資
BigQuant

The document summarizes a study of four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a market-cap-weighted benchmark. Using monthly returns over 1999–2014, the study applies principal component…

股票因子投資統計投資組合建構
BigQuant

The document explains a cost-concentration measure for the estimated purchase costs of a selected share of investors’ holdings. It defines the measure as the difference between the upper and lower bounds of that cost interval divided by their sum. A narrower…

股票統計因子投資
BigQuant

This article outlines an event-driven strategy for Chinese equities, using quarterly reports as the trigger. It treats a published year-over-year increase of more than 30% in attributable net income as a positive event, buys qualifying stocks when reported,…

中國市場股票事件驅動回測
BigQuant

This essay focuses on how fear can affect trading decisions, including hesitation after losses, reluctance to buy near highs, and difficulty acting during market weakness. Its central idea is that traders need not eliminate fear to act consistently; they can…

股票交易執行風險管理統計
BigQuant

The report reviews the development of Smart Beta index funds in China and compares single-factor strategies in A-shares with counterparts in the US. It describes a Chinese market where offerings are relatively early-stage, commonly single-factor, and held…

股票因子投資投資組合建構中國市場
BigQuant

This report summary describes a Chinese equity ETF rotation approach built from industry indices with matching exchange-traded funds. It selects 14 industries from the broader industry classification and rotates exposure among their ETFs. The strategy is…

股票中國市場趨勢追蹤期貨
BigQuant

This strategy ranks stocks across mainland China’s A-share market using a small-cap factor and a five-period momentum measure. It combines the market-cap rank with momentum into a composite score, selects the top 50 names, and assigns equal weights. The…

中國市場股票動能因子投資
BigQuant

The article argues that quantitative trading is an execution method, not a source of returns by itself. A trading system can automate orders and support consistent discipline, but it cannot make a weak or faulty strategy profitable. It also questions the…

交易執行風險管理回測股票
BigQuant

The document reviews tactical and dynamic asset allocation, then focuses on predicting short-term movements in Chinese equity indices. It compares logistic regression, artificial neural networks, and support vector machines across different inputs and…

股票中國市場機器學習趨勢追蹤