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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

A user asks why backtest results change when the number of historical days fetched before a test is increased, even when the strategy calculates a moving average such as a ten-period average. The question assumes that fetching at least the indicator’s…

回測股票統計
BigQuant

This article explains Reflex and Trendflex, two price indicators attributed to John Ehlers. Both first smooth prices with a SuperSmoother low-pass filter, then measure average distance between the smoothed price path and a reference line. The distance is…

期貨加密貨幣趨勢追蹤技術指標
BigQuant

This research report develops equity-selection factors from four types of intraday information: price behavior, price-volume relationships, pre-open auction data, and selected trading periods such as the close or high-volume intervals. It evaluates 46…

股票中國市場技術指標市場微結構
BigQuant

This article compares neural networks, decision trees, random forests, support vector machines, and a stock-ranking algorithm for equity selection. It describes broad trade-offs: neural networks can model nonlinear relationships and varied data structures,…

股票機器學習回測中國市場
BigQuant

This report examines corporate tax burdens in China at the economy, industry, and listed-company levels. It distinguishes taxes from mandatory non-tax charges, describes differences across industries, and notes that the shift from business tax to value-added…

股票中國市場統計
BigQuant

This overview explains how factor models can identify portfolio risk drivers and how factor strategies can target their associated return premia. It describes equity factors such as value, size, momentum, volatility, quality, yield, growth, and liquidity,…

因子投資多資產風險管理投資組合建構
BigQuant

This educational-session overview introduces machine-learning and deep-learning approaches to quantitative stock selection. It lists core workflow topics: defining prediction labels, engineering features, separating training, validation, and test sets, and…

機器學習股票統計回測
BigQuant

The document answers a programming question about applying a per-stock price-pattern test to stocks first selected by daily market filters. The suggested workflow reads hourly bars for the candidate instruments in one batch, then passes the shared data frame…

股票技術指標交易執行
BigQuant

The document explains the price-to-earnings ratio (P/E) as a way to relate a stock’s price to the company’s earnings per share. Comparing two stocks at the same price but with different earnings shows how the ratio distinguishes their valuations: the stock…

股票因子投資統計
BigQuant

The report explains how option prices can be used to construct volatility and skew measures for the Chinese equity market. VIX represents expected volatility over a forward period, while SKEW captures the market’s pricing of asymmetric returns and tail risk.…

選擇權波動率衍生品定價中國市場
BigQuant

The article presents a discretionary momentum setup for Chinese equities that avoids chasing rapid advances and instead looks for a shift from prior weakness to renewed strength. It characterizes a previous session with heavy trading and a contested limit-up…

中國市場股票動能突破
BigQuant

This short post introduces a template for monitoring a personally selected stock universe, aimed at individual investors who may trade manually rather than buy many stocks in batches. The stated use is to track dozens or hundreds of shares and view their…

股票中國市場
BigQuant

This summary of a Haitong Securities study examines whether the cyclically adjusted price-to-earnings ratio can predict long-run US equity returns. Historically, high CAPE readings tended to accompany weaker subsequent ten-year returns, and low readings…

股票美國市場均值回歸統計
BigQuant

This study compares loss functions for neural models that forecast five-day cumulative returns for selected Chinese A-shares. It uses a DeepAlpha DNN as the main model and compares mean squared error with absolute error, Pseudo-Huber, negative information…

機器學習股票中國市場回測
BigQuant

This research summary explains why predictive machine-learning models can mistake unstable associations for causal relationships, especially when selection bias or confounding drives observed patterns. It presents propensity-score analysis as a way to make…

股票機器學習統計中國市場
BigQuant

This lesson explains binary classification through logistic regression, using the example of predicting whether a stock will rise. It describes encoding outcomes as zero and one, interpreting the model output as a probability, and applying a 0.5 cutoff to…

機器學習統計股票
BigQuant

The document introduces a video about applying “做T” trading—buying and selling within a trading period—to a value stock, using China Yangtze Power as its example. Its stated aim is to explore whether this approach can generate returns beyond simply holding…

股票中國市場
BigQuant

The article argues that algorithmic trading can exploit retail investors’ predictable reactions to price action and news in China’s A-share market. It illustrates this with two anecdotal patterns: a sharp late-session reversal in high-flying consumer stocks…

股票中國市場市場微結構市場情緒
BigQuant

This research update describes two A-share stock-selection approaches. The product-price strategy tracks changes in listed companies’ main product prices and highlights cases where prices have risen but share prices may not yet reflect the development. The…

股票中國市場事件驅動市場情緒
BigQuant

The report builds a composite trading-heat signal from stock-specificity and market-cap-adjusted turnover, using these trading-behavior measures as proxies for speculative activity. It argues that the two inputs capture most of the useful information in a…

股票因子投資中國市場回測
BigQuant

The document explains how members access BigQuant market data through its Python SDK. It outlines installation and login, describes checking table permissions, and demonstrates querying selected daily stock fields over a date range. It also shows how to…

中國市場股票技術指標統計
BigQuant

This overview explains how quantitative strategies use factors to express hypotheses about future returns. It describes candidate signal sources such as prices, fundamentals, macroeconomic data, and text, then outlines a research process: translate an…

因子投資統計回測風險管理
BigQuant

A BigQuant support discussion addresses a user’s difficulty training a StockRanker model for individual-stock prediction. The replies recommend moving to the newer StockRanker template because the older module is no longer actively maintained. A second…

股票機器學習中國市場